Evaluating Participatory Mapping Software 9783031195938, 9783031195945

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Charla M. Burnett  Editor

Evaluating Participatory Mapping Software

Evaluating Participatory Mapping Software

Charla M. Burnett Editor

Evaluating Participatory Mapping Software

Editor Charla M. Burnett Organizing Together Consultancy Lansing, MI, USA

ISBN 978-3-031-19593-8    ISBN 978-3-031-19594-5 (eBook) https://doi.org/10.1007/978-3-031-19594-5 © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 This work is subject to copyright. All rights are solely and exclusively licensed by the Publisher, whether the whole or part of the material is concerned, specifically the rights of translation, reprinting, reuse of illustrations, recitation, broadcasting, reproduction on microfilms or in any other physical way, and transmission or information storage and retrieval, electronic adaptation, computer software, or by similar or dissimilar methodology now known or hereafter developed. The use of general descriptive names, registered names, trademarks, service marks, etc. in this publication does not imply, even in the absence of a specific statement, that such names are exempt from the relevant protective laws and regulations and therefore free for general use. The publisher, the authors, and the editors are safe to assume that the advice and information in this book are believed to be true and accurate at the date of publication. Neither the publisher nor the authors or the editors give a warranty, expressed or implied, with respect to the material contained herein or for any errors or omissions that may have been made. The publisher remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. This Springer imprint is published by the registered company Springer Nature Switzerland AG The registered company address is: Gewerbestrasse 11, 6330 Cham, Switzerland

This book is dedicated to the environmental and social activists who have lost their lives challenging the authority of oppressive regimes and the indigenous people of the world who have been colonized and robbed of their culture and history. However altruistic, participatory mapping software has had a transformational impact on economic and political power structures and remains a powerful tool for social change. I hope this edited volume helps build activists and indigenous peoples’ capacity to effectively choose software and manage participatory mapping projects that challenge local to global injustices.

Foreword

The study of cartography and the practice of map-making have changed dramatically over the last 60 years. This has largely been facilitated by the proliferation and availability of digital geospatial tools and the central role of the internet. Today, the creation of maps relies almost entirely on software applications and geolocating hardware. Participatory mapping is widely understood as the creation of maps by non-­ experts. These maps often do not conform to rigid cartographic principles; however, in most cases, this discrepancy does not undermine their efficacy. They are used to deliberate, document, and communicate unique perspectives of land, and the relationship between people and the places in which they live. This is particularly important when participatory mapping involves the process of map-making with vulnerable and silenced communities and individuals. Although the roots of participatory mapping are firmly situated in low-cost and easy-to-use technologies, contemporary practice has also encountered a digital turn. New digital technologies are playing an increasingly important role in amplifying and sharing geolocated community voices, concerns, and aspirations. These technologies allow communities to reach beyond their immediate geographies and express themselves to a broader audience. Furthermore, digital technologies enable communities to communicate their land-related knowledge using diverse media that in the past were impossible to leverage. Whether collecting crowdsourced data from entire populations using smartphone applications, or documenting oral histories using video and imagery, the digital map can act as a canvas to aggregate, embed, and present community information. However, practitioners and researchers have become increasingly interested in the longer-term impacts of transforming local spatial knowledge into digital media. In the same light that Brian Harley in the 1980s encouraged cartographers to think critically about the content and presentation of maps, we must think critically about the affordances and drawbacks of mapping community knowledge using digital media. The need for this reflection is even more salient when we consider the participatory nature of the practice. In Robert Chambers’ seminal article, Participatory

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mapping and geographic information systems: Whose map? Who is empowered and who disempowered? Who gains and who loses?, he encourages users to be sensitized to whose voices are represented, and even more significantly to whose voices are ignored—or actively silenced, using the tools and technologies that underpin digital participatory mapping projects. Despite more esoteric and theoretical debate related to the evolving digital practice of participatory mapping, many software applications have grown to support its practice over the past 15 years. This book provides an important and timely contribution to taking stock of contemporary digital geospatial tools and solutions and presenting nine examples of software and platforms supportive of participatory mapping initiatives. The book examines these applications using a series of key themes. These include information about each of the tool’s features, the costs, and other implementation requirements. On a pragmatic level, this will help guide practitioners to choose which tool might be most appropriate for their own needs. Furthermore, the key themes also include the ethical considerations of the software, including issues of inclusiveness, data privacy, openness, and accessibility. As well as being vital elements in choosing the correct platform, these themes are also of significance to theorists interested in examining how the foundational and guiding principles of participatory mapping have transferred from its analogue past to the present digital realm. A highlight of the book is the authorship of the individual chapters. Each is written by a team of technical specialists, developers, and researchers. This breadth of experience and perspective provides a set of examples that will resonate with multiple audiences. Collectively, these chapters provide practical advice for communities and individuals wanting to establish projects in the field. They are also of use to designers and developers and provide a greater understanding of the programming languages, frameworks, and APIs used and available. Finally, they will be of interest to academics and theorists who seek to better understand the evolving nature and application of participatory mapping. Participatory mapping is going through a profound period of change. Because of the digital turn, the documentation and communication of spatial data have never been easier. However, I feel that it is important that we not conflate simple community spatial data acquisition with participatory mapping. As this edited volume highlights, it is the underlying principles of participatory mapping that make its practice unique and valuable. It is, among other things, about aspiring to provide a voice to the silenced, to support social and spatial justice, and to challenge the powerful to better understand injustice and empathize with those less privileged. As this edited volume clearly demonstrates, these aspirations become more complex within the digital milieu, yet with sensitive development and clear ethical principles that guide implementation, digital participatory mapping tools have the potential to support social change.

Foreword

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Professor: Community, Culture and Global Studies, Director: ICER—Institute for Community Engaged Research, Director: SpICE—Spatial Information for Community Engagement Lab, I.K. Barber School of Arts and Social Sciences Jon Corbett The University of British Columbia, Okanagan Campus Syilx Okanagan Nation Territory, Kelowna, BC, Canada

Acknowledgments

I owe a great deal of gratitude to the late Gregory Brown, my mentor and friend, who put forth the funding for the creation of the International Society for Participatory Mapping (ISPM) and Rudo Kemper, who was instrumental in its development as our first President. A special thanks to the researchers, developers, and activists who helped to write the chapters within this edited volume. We would not have a book without you. You took your experience, lessons, triumphs, and failures and reflected on them critically which provided a much more thorough and honest look into these software platforms. I hope my persistent emails did not scare you away from working on future projects with me. Don’t get discouraged and always keep up the good fight to establish better policies, environmental protections, social justice, and human security.

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Contents

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Participatory Mapping and Technology������������������������������������������������    1 Charla M. Burnett, Michael McCall, and Alison D. Ollivierre

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Mapbox ����������������������������������������������������������������������������������������������������   21 Michał Rzeszewski

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Mapeo��������������������������������������������������������������������������������������������������������   41 Aliya Ryan, José María León Villalobos, and Mir Rodríguez Lombardo

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Maptionnaire��������������������������������������������������������������������������������������������   71 Marketta Kyttä, Nora Fagerholm, Vera Helene Hausner, and Anna Broberg

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Sapelli��������������������������������������������������������������������������������������������������������   93 Megan Tarrant, Marcos Moreu, Hannah M. B. Gibbs, Muki Haklay, Jerome Lewis, Megan Laws, Artemis Skarlatidou, Fabien Moustard, and Simon Hoyte

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SeaSketch��������������������������������������������������������������������������������������������������  121 Madeline Berger, Will McClintock, Chad Burt, and Tim Welch

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Sketch Map Tool��������������������������������������������������������������������������������������  149 Carolin Klonner and Jeantyl Norze

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Survey123 for ArcGIS Online ����������������������������������������������������������������  167 Sabine Hennig, Robert Vogler, and Jiří Pánek

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Terrastories����������������������������������������������������������������������������������������������  189 Christopher Martin, Rudo Kemper, Colin M. Gibson, Natalie Thornhill, Rohini Patel, and Dawn Martin-Hill

10 Ushahidi����������������������������������������������������������������������������������������������������  219 Janet Marsden and Angela Oduor Lungati

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Contents

11 Trends,  Conclusions and Recommendations for the Future of Participatory Mapping Software��������������������������������������������������������  235 Peter A. Kwaku Kyem and Charla M. Burnett Appendix A: Participatory Mapping Comparison Chart����������������������������  259 Index������������������������������������������������������������������������������������������������������������������  263

About the Editor

Charla  M.  Burnett  is a scholar and practitioner of participatory mapping using geospatial technologies. She coordinates multilateral and bilateral international development projects from proposal development to implementation and evaluation. Her policy research and program design spans migration, the environment, and conflict resolution with experience working with international organizations in the Middle East and West Africa. She currently supports Michigan State University’s International Development Research Agenda as a USAID Proposal Development Specialist for the Department of Global Innovations in Development, Engagement, and Scholarship (Global IDEAS) where she facilitates multi-college/industry program design and proposal development. Charla is also a founder of the Migration Alliance Partnership (MAP) Network and the International Society for Participatory Mapping (ISPM). As a result of these efforts, she was honored with the 2018 Excellence in Community Engagement and Leadership Award by the University of Massachusetts Boston and 2022 McCormack’s Graduate School of Public Policy and Global Affairs’ Public Service Award. In 2021, Charla co-started the Umoja House in her home city of Lansing, MI. The Umoja House is a temporary (1 day–12 months) home for migrants of all kinds, including international scholars, refugees, asylees, and internally displaced persons (DV & LGBTQA+). The project houses up to 6 migrants at a time and subsidizes housing costs for up to 12 displaced persons each year through a mutual aid model. xv

List of Contributors

Madeline Berger  is a Spatial Analyst with the McClintock Lab, supporting Ocean Use Surveys and Marine Spatial Planning around the globe. Previously, she was an Ocean Health Index at the National Center for Ecological Analysis and Synthesis. Anna Broberg  is the COO and Co-Founder of Mapita Oy, where she has a 10-year track record of close cooperation with cities in the design of community engagement processes, tools, and analyses. Her research focuses on urban planning, transportation studies, and the commercialization of digital community engagement. Chad  Burt  is the Lead Developer at McClintock Labs and SeaSketch. He is responsible for the design and development of web applications created by the McClintock Lab. Chad led the development of the MarineMap decision support tool and has created innovative data visualization applications for the National Park Service, PISCO, and Santa Barbara Coastal LTER. He also contributed content for the launch of Ocean in Google Earth. Jon Corbett  is a Professor of Human Geography in the Department of Community Culture and Global Studies at UBC Okanagan. He is also the Director of the Institute for Community Engaged Research (ICER) and the Director of the Spatial Information for Community Engagement (SpICE) Lab. Corbett helped design and launch the International Journal of Participatory Mapping. Nora  Fagerholm  is an Associate Professor in Human-Nature Interactions and Sustainability at the University of Turku. Currently, she is also an Academy Research Fellow and Principal Investigator of the Academy of Finland-funded research project “Wellbeing benefits of urban green infrastructure mapped through participation and 3D virtual landscapes.” Hannah M. B. Gibbs  was a lead researcher for a project titled Extreme Citizen Science: Analysis & Visualization funded by the European Research Council (ERC) at the University College London. They worked with communities all over the xvii

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world to help them address local issues that are important to them – from odor and noise in London to illegal logging in the Congo Basin and cattle invasion in Namibia. Colin M. Gibson  is a part-time PhD candidate in the Water Resources Engineering and International Development Studies collaborative program at the University of Guelph. He is also a Project Officer for Ohneganos, an Indigenous-led water research program based out of Six Nations of the Grand River. The program is made up of two main projects: Co-Creation of Indigenous Water Quality Tools and Ohneganos  – Indigenous Ecological Knowledge, Training, and Co-Creation of Mixed-Method Tools. Muki Haklay  is a Professor of GIScience and Co-Director of the Extreme Citizen Science (ExCiteS) research group at the University College London. His research focuses on the public access, use, and creation of environmental information, human-computer interaction (HCI), and Usability Engineering (UE) aspects of GIS. Vera Helene Hausner  is a Professor of Sustainability Science in the Department of Arctic and Marine Biology at the University of Norway. Their research focuses on environmental changes, socio-ecological systems, ecosystem-based approaches to management and climate adaptation, and new technologies and approaches for interdisciplinary and collaborative science in coastal and tundra ecosystems. Sabine Hennig  is a Senior Scientist at the Department of Geoinformatics at the Paris Lodron Universität Salzburg. She has a background in Geography and Applied Geoinformatics. Her research focuses on user-centered (map) application with special attention to usability and accessibility and special needs user groups, participatory approaches with a focus on Geo Citizen Science, and the development of GI learning materials. Simon Hoyte  is a PhD candidate of Social Anthropology at the University College London. His research investigates the interaction between three key areas: nature conservation, Indigenous peoples, and technology. Based in the Extreme Citizen Science research group (ExCiteS), he is combining techniques from participatory action research (including participatory mapping) with hunter-gatherer ethnography to address issues of forest degradation and environmental injustice among Baka hunter-gatherers in southeastern Cameroon, Central Africa. Rudo Kemper   is a geographer and technologist with over a decade of experience supporting Indigenous communities in mapping and monitoring their lands, and building digital tools that increase community self-determination, access to land rights, and land management capabilities. He's the Chief Programs Officer of Cadasta Foundation, a civic organization that promotes the use of simple digital tools and technology to help individuals, organizations, communities, and governments efficiently document, analyze, store, and share critical land and resource rights information.  

List of Contributors

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Carolin Klonner  is a Postdoctoral Researcher at the Chair of GIScience, Institute of Geography, Heidelberg University. Her research interests include the collection and visualization of participatory geographic information for disaster risk management and urban planning. In her doctoral thesis, she chose Sketch Maps for participatory mapping in order to visualize the flood risk perception of citizens. Based on this research, the Sketch Map Tool was developed within the Waterproofing Data project. It improves the information exchange between citizens, local authorities, and scientists. Peter A. Kwaku Kyem  currently works at the Department of Geography, Central Connecticut State University. Peter does research in Geoinformatics (GIS) and Geography. His research focuses on conflict resolution and the use of GIS, land tenure, and resource distribution. He is the author of “Managing Natural Resource Conflicts with Participatory Mapping” published by Springer in 2021. Marketta Kyttä  is an international leader in the use of participatory mapping to study the environmental experiences of people, especially in urban areas. Her research themes include social sustainability of the living environment, health-­ enhancing community structure, and child- and age-friendly environments. Her team also has extensive experience in the use of participatory mapping in real-life public participation projects of cities at various planning levels. Megan Laws  is a Senior Research Fellow in the Extreme Citizen Science (ExCiteS) research group at University College London. She is a specialist in the anthropology of southern Africa, and her current research concerns how new geo-spatial technologies (with a special focus on remote sensing and mobile data collection) are being used to address ecological uncertainties, and the consequences these have for people living at southern Africa’s rural margins. José María León Villalobos  is a Senior Researcher at the Center for Research in Geospatial Information Sciences (Centro Geo). His research interests focus on using transdisciplinary methodologies for knowledge co-creation, participatory approaches, and GIS for mapping local knowledge, community-based planning in agroecosystems, and local risks management and perceptions of citizens. He also coordinates the Laboratory of Territorial Analysis and Community Participation (COMULAB). Jerome  Lewis  is a Professor of Social Anthropology and Co-Director of the Extreme Citizen Science (ExCiteS) research group at the University College London. Their research focuses on hunter-gatherer and former hunter-gatherer societies, indigenous rights, participatory mapping, and representation. Janet Marsden  is a Professor of Qualitative Research and Professional Issues in Information Management and Technology. Her recent projects include serving on the Citizen’s Advisory Board for NOAA’s proposed National Marine Sanctuary in

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Lake Ontario and developing data management and computing protocols for the UREx SRN (Urban Resilience to Extremes Sustainability Research Network), a research consortium including Arizona State, Syracuse University, and other colleges and universities. Her dissertation research examines how self-organizing ad hoc emergency response based on advanced information and communications technology occurs during extreme events such as Hurricane Katrina and Superstorm Sandy. Christopher  Martin  is the Indigenous Community Mapping Facilitator for the Ohneganos Project. He has been helping to embed the Terrastories mapping software with information and knowledge about Haudenosaunee history and Six Nations of the Grand River. Chris works in education as well and blends curriculum with Indigenous and community knowledge so that Indigenous youth can be represented throughout learning. Dawn Martin-Hill   is Mohawk Wolf Clan from Six Nations of the Grand River and is the lead Principal Investigator on an Indigenous-led water research program called Ohneganos. Michael McCall  is currently a Senior Researcher in the Center for Environmental Geography of the National Autonomous University of Mexico (UNAM), after many years in the ITC (University of Twente), the Netherlands. His research and training activities and publications are in social mapping and PGIS with communities, applied to territorial claims, cultural landscapes, natural resources, participatory urban planning, children’s spaces, and assessing vulnerability. He has taught and run workshops in Africa, Asia, Europe, and Latin America. Will McClintock  is the Director of McClintock Lab and the Founder of SeaSketch. He has worked in over two dozen countries to support marine spatial planning in the form of stakeholder-friendly decision support tools and currently holds a position as Senior Fellow at the National Center for Ecological Analysis and Synthesis. Marcos Moreu  is a Researcher at the UCL’s Extreme Citizen Science (ExCiteS) research group. His work with farming and pastoralists communities in SSA focuses on linking crowdsourcing & EO, messaging & mapping, and participatory software design & mapping. In the past, as part of his mechanical engineering studies, he worked in El Salvador in WASH projects; and later on, in East Africa in capacity-­ building projects on the use of GIS and Remote Sensing for DRR. Fabien Moustard  is a PhD candidate at University College London (UCL). His research examines how to integrate local knowledge and concerns into regional, national, and planetary-scale environmental management systems. He focuses on the role technology can play for social recognition of vulnerable people who are frequently the most ecologically literate, with a particular emphasis on the Congo Basin.

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Jeantyl  Norze  is a Program Development and Evaluation Specialist who has authored and co-authored numerous publications in a variety of refereed national and international journals. Norze joined Extension at the University of Connecticut as Evaluation Specialist in January of 2022. He developed, in collaboration with his former colleagues, a needs assessment framework to guide statewide needs assessment efforts that seek to meet and understand the changing needs of the communities. Angela Oduor Lungati  is the Executive Director at Ushahidi. Angela is a technologist, community builder, and open-source software advocate who is passionate about building and using appropriate technology tools to impact the lives of marginalized groups. She has over 10 years of experience in software development, global community engagement, and non-profit organizational management. Alison  D.  Ollivierre  is a Senior Cartographer at National Geographic and the Founder/Director of Tombolo Maps & Design, internationally recognized for her award-winning cartography. She has specialized in participatory mapping since 2010, facilitating projects in the Eastern Caribbean and co-founding the International Society for Participatory Mapping (ISPM) and serving a four-year term as a Director-at-Large. Her research has uniquely focused on the value of participatory mapping in small island developing states (SIDS) and its use in addressing climate change, and she was the invited lead author for the International Encyclopedia of Geography’s Participatory Mapping chapter published by Wiley and the American Association of Geographers (AAG) in 2021. Jiří Pánek  is an Associate Professor at Palacky University. He has a Geography-­ GIS-­Development Studies background, with over 15 years of experience. He specializes in participatory approaches in mapping and using spatial tools in/for community development. He co-founded GISportal.cz (online GIS magazine) with more than 2.0M hits (in 9  years) and co-developed participatory mapping tool PocitoveMapy.cz. Rohini Patel  is a PhD candidate in the Department of History at the University of Toronto. She studies histories of science, technology, and environment, postcolonial and feminist science studies, and histories of empire and capitalism. Mir Rodríguez Lombardo  has been making maps for over a decade with a special interest in travel maps, cultural resources, and participatory rural mapping. They are a professional translator and conference interpreter, software developer, and biologist. Aliya  Ryan  is a Program Leader with Digital Democracy and has worked with diverse groups of indigenous peoples in the Amazon. She co-founded the non-profit Shinai, to an educational establishment in the Scottish Borders and marginalized minority ethnic communities in Edinburgh.

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Michał Rzeszewski  is an Associate Professor at the Faculty of Human Geography and Planning, Adam Mickiewicz University in Poznań, Poland, exploring digital geographies and geographic information systems (GIS). His scientific interests include virtual (VR) and augmented reality (AR) and the relationship between software, code, and space. He is the head of the Critical Geography Research Unit. Rzeszewski’s research focused on human spatial behavior and critical GIS. They are currently working on AR, VR, and algorithmic production of space. Artemis Skarlatidou  is a Lecturer in Citizen Science (Department of Geography, UCL) and also a member of the People Nature Lab (Department of Biosciences, UCL). Her research interests include Human-Computer Interaction (HCI) aspects of geospatial technologies for expert and public use, citizen science applications, and their visualizations. Megan Tarrant  is an environmental anthropologist focused on the study of conservation and development. Megan spent 3 years working with indigenous communities in Peru and Papua New Guinea on community-led rainforest conservation projects with the NGO “Cool Earth.” Megan is now a Research Assistant at ExCiteS in the Department of Geography at the University College London. Natalie  Thornhill  is a PhD candidate in Medical Anthropology at McMaster University. Her research focuses on complementary and alternative medicine and Indigenous wellness frameworks. Natalie is a faculty in the Department of Humanities and Social Sciences at Centennial College in Toronto, where she supports reconciliation through education. Robert Vogler  is a Senior Scientist for Geography Education and Socioeconomics Education in the Department of Sociology and Social Geography and the School of Education at the Paris Lodron Universität Salzburg. His research focuses on geomedia integration and geoinformation usage in secondary education from a “spatially-­ enabled learning” perspective based on a constructivist background. Tim Welch  is a Geospatial Developer for the SeaSketch software platform, supporting marine spatial planning projects around the world. His past roles have been in the areas of forestry, food systems, and transportation planning. He is also a resident scientist at the National Center for Ecological Analysis and Synthesis.

Abbreviations

ACR AI API AR AWS CBTa CG COO CP CSS CSV CVM DMS DELAMAN EO ERC EU GDPR ExCitS FAQ FI FOSS4G FPIC FS GIS GISP GNSS GPS GRC HCCC HCI

Accessibility Conformance Reports Artificial Intelligence Application Programming Interface Augmented Reality Amazon Web Services Centro de Bachillerato Tecnológico Agropecuario Centro Geo Chief Operations Officer Community Protocol Cascading Style Sheets Comma-Separated Values Mozambican Red Cross Degrees, Minutes, Seconds Digital Endangered Languages and Musics Archives Network Earth Observation European Research Council European Union General Data Protection Regulation Extreme Citizen Science Project Frequently Asked Questions Fishers Island Free and Open-Source Software Free Prior Informed Consent Free Software Geographic Information Systems GIS Professional Global Navigation Satellite System Global Positioning System German Red Cross Haudenosaunee Confederacy Chiefs Council Human Computer Interaction xxiii

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Abbreviations

HTML Hypertext Markup Language IHDRP Indigenous Health Research Development Program ICT Information and Communication Technology ID Identification IP Intellectual Property ISPM International Society for Participatory Mapping ITU International Telecommunication Union KML Keyhole Markup Language LCLU Land Cover and Land Use MD Mapeo Desktop MM Mapeo Mobile MPA Marine Protection Areas MSP Marine Spatial Planning NGO Nongovernmental Organization OCAP Ownership, Control, Access, and Possession OSM OpenStreetMap OSS Open-Source Software PAR Participatory Action Research PC Personal Computer PDF Portable Document Format PGIS Participatory Geographic Information Systems PPGIS Public Participation GIS PM Participatory Mapping PNS Post-Normal Science POSM Portable OpenStreetMap QGIS Quantum GIS QR Quick Response SDK Software Development Kit SPLC Southern Poverty Law Center SMA Seagrass Management Areas SMS Short Message Service SSL Secure Sockets Layer TCPS2 Tri-Council Policy Statement of Canada TEK Traditional Ecological Knowledge TEKES Finnish Funding Agency for Technology and Innovation TK Traditional Knowledge TOS Terms of Service UCSB University of California Santa Barbara UE Usability Engineering UNICAM-SUR Universidad Compensina del Sur URL Uniform Resource Locators USA United States of America USD United States Dollar USAID United States Agency for International Development USB Universal Serial Bus

Abbreviations

UTM UX/I VGI VR WCAG WMS WWF XML

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Universal Transverse Mercator User Experience Volunteer Geographic Information Virtual Reality Web Content Accessibility Guidelines Warehouse Management System World Wildlife Fund for Nature Extensible Markup Language

Chapter 1

Participatory Mapping and Technology Charla M. Burnett, Michael McCall, and Alison D. Ollivierre

Abstract  Participatory Mapping (PM) incorporates a diverse set of tools and approaches for planning, gathering, and utilizing spatial data for collective place-­ making and action. Its roots span centuries-old traditions of indigenous storytelling and local oral histories, as well as pictorial images and computer graphics and what we today recognize as maps. This edited volume prepares the reader to choose the appropriate participatory mapping software for a project or a course by providing a brief history of its origins, essential terminology, trends and gaps, and major debates. Our  purpose is to present readers with a common framework for assessing and selecting amongst alternative participatory mapping approaches and the principles used to build supporting technology. The evaluation framework outlined in this chapter lays the foundation for each of the software-focused reviews and case studies. Keywords  Technology · Maps · Evaluation · Participation

1.1 Introduction to Participatory Mapping Participatory mapping (PM) and geographic information systems (GIS) are methods and tools for collecting and analyzing spatial information for agriculture, conservation, forestry, oceans, water resources, atmospheric, environmental ­ C. M. Burnett (*) OrganizingTogether Consultancy Group, Lansing, MI, USA e-mail: [email protected] M. McCall CIGA-UNAM, National Autonomous University of Mexico, Morelia, Michoacán, Mexico e-mail: [email protected] A. D. Ollivierre Tombolo Maps & Design, Denver, CO, USA e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 C. M. Burnett (ed.), Evaluating Participatory Mapping Software, https://doi.org/10.1007/978-3-031-19594-5_1

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C. M. Burnett et al.

management, mining, petroleum, and more (Wing & Bettinger, 2008). Public participation in natural resource planning and management is regarded as a democratic right in many regions of the world and is enshrined in the United Nations Economic Commission for Europe’s 1998 Aarhus Convention (United Nations, 2001). PM incorporates a diverse set of tools and approaches combining into a methodology for planning, gathering, and utilizing spatial data for collective place-making and action. Its roots span centuries-old traditions of indigenous storytelling and local oral histories, as well as pictorial images and computer graphics and what we today recognize as maps (Wood, 1992). Over time, PM has gone through multiple epistemological changes and faced many ethical problems. Corporations, scientists, governments, NGOs, and communities have used its methods for positive social developments, but also towards social control. Its use for development has both positive and negative aspects and it is important to discuss the serious ethical considerations and to digest the lessons from its long history of practical applications. PM can always be a source of power for those who employ it, but that can be towards progressive or oppressive ends, for the latter, such as extracting resources and violating human rights. PM consists of many distinct types of methods and processes. Users often approach technical experts familiar with geodesign and work together to create a strategy for incorporating the public into the decision-making process. Geodesign is the process and practice used to guide participants through spatial reasoning and decision making by facilitators and technical experts. The facilitating team identifies appropriate stakeholders to collaborate in public meetings and workshops on PM. A myriad of different mapping tools are available today, from geospatial desktop software and internet-based web-maps, to paper and ephemeral ground mapping. PM geospatial software can enhance or restrict the decision and planning scenarios. Users, either public or private, usually outline and delimit the scope and attributes under review depending on the problem they are trying to solve. For example, environmental scientists may collect data on species migration or reproduction patterns, while cultural anthropologists may be interested in the behavioral changes caused by those changes in food production. The expectation is that if the community somehow participates in the mapping of their locale or territory, at least with some basic form of representation, it is more likely that the community’s viewpoints/needs/priorities concerning their space will be appreciated and valued by governments, corporations, and the public at large. As the practice of PM started to become more mainstream in the 1990s, research on best practices for the design and implementation of PM activities also increased. During the process of evaluation, scholars and practitioners learned to recognize that there is more to PM than just spatial data accuracy or representation and, as a result, the software and tools designed to support these projects have become more sophisticated. PM and PGIS both draw from the theoretical frameworks of Participatory Action Research (PAR) in international development. PAR is an approach to inquiry which dates to the 1940s and involves researchers and participants working together to understand a problem and find a solution. There are many definitions of this

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approach, which normally share common elements. PAR specifically focuses on social change that promotes democracy and challenges inequity in all its forms. PAR is an iterative cycle of research, action, and reflection using both qualitative and quantitative methods (Kidd & Kral, 2005). For readers interested in PAR and facilitating PM, we suggest Chevalier and Buckles (2019) Participatory Action Research: Theory Methods for Engaged Inquiry. This edited volume prepares the reader to choose the appropriate PM software for a project or a course by providing a brief history of its origins, essential terminology, trends and gaps, and major debates. Its purpose is to present readers with a common framework for assessing and selecting amongst alternative PM approaches and the principles used to build supporting technology. The evaluation framework outlined in this chapter lays the foundation for each of the software-focused reviews and case studies. There has been growing concern from scholars and practitioners that the technology overcomplicates the process and thus excludes many potential users, and, more worryingly, it can endanger communities by appropriating and sharing sensitive information. It is important that those who promote and apply this powerful tool also understand the very real risks associated with handling people’s own spatial data and the dangers of using (mapping) software without due diligence. We discuss this further later on in this chapter. It is recommended that readers take the time to review the case studies included to ground themselves in the implementation and ethical debates surrounding PM.

1.2 The Past and Future of Participatory Mapping Participatory maps and mapping refer to `maps` (representations of spatial information) that are made using ‘participatory’ processes by a community or groups of people. The umbrella term is used to encompass several techniques and tools. For the focus of this book, the chapter authors evaluate software that are defined as participatory geographic information systems (PGIS). Users might come across a dichotomy in the terminology in the field, with researchers and the practitioners in the Global North (particularly the USA) more commonly using the term public participatory geographic information systems (PPGIS), whereas the Global South is likely to use PGIS. The use of participatory spatial tools to engage people in rural development goes back to the ‘participation turn’ in the late 1970s and 1980s (Ellis & Biggs, 2001; Chambers, 2006; McCall, 2021; Warf & Sui, 2010). There are three drivers that can help explain this, including:

1.2.1 Participation and Empowerment This is a universal, activist, and progressive driver towards greater decentralization, accountability, popular democracy, and empowerment. It strengthens feelings and narratives of agency in public space, i.e., for citizens to feel more included, engaged,

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and valued. It is a key component in the core categories of ‘good governance’ and in the language of post-normal science (PNS) it is framed as the ‘democratization of expertise’, and a reaction against a long running “tendency towards assigning to experts a critical role in policymaking whilst marginalizing laypeople’ (Pecchia et  al., 2015, pp.  109–110). A PNS framing is that citizens ought to feel more included, engaged, and valued for their delivery of knowledge, and thus they should have more reason to want to be involved in decision-making (Turnhout et al., 2010; Haklay, 2013; Cavalier & Kennedy, 2016).

1.2.2 Spatial Knowledge That is, both the objective truth value of (cognitive) facts emergent in the local knowledge, as well as the cultural-political import of people’s values, interests, and priorities. PM, during its development, has learned much from the principles and experiences of feminist geography and critical cartography. In this vision, the non-­ authoritative sources of spatial information and knowledge of citizens are considered to have special value and are prioritised. This is a way of privileging ‘non-authoritative sources of information,’ i.e., the knowledge of citizens or the ordinary people. The local spatial knowledge of ordinary people relates to most elements of their lives and places as well as their livelihoods, landscapes, territories, resource management, risks, security, conflicts, etc. (Kyem, 2021; Haklay, 2013; Sletto, 2009; Vogt et al., 2016; Young & Gilmore, 2017; Fagerholm, 2014). This driver also appears in Citizen Science whose principles and practices include being respectful, open-minded, and committed towards people’s participation in scientific research (Haklay, 2013; Sieber et  al., 2016; McCall et  al., 2015; Radil & Anderson, 2019). This alternative or ‘counter’ knowledge is frequently critical of prevailing authority and therefore can disrupt oppressive social-political systems by contesting the sources and presentations of authoritative spatial information. Therefore, participatory processes in decision-making or policy may often contribute to conflicts between (hegemonic) official knowledge and people’s knowledge.

1.2.3 Technological Capacity The final driver toward the increasing use of participatory spatial tools is a primary focus of this book—the fast-growing easy access to technical capacities that enable quicker, easier, more user-friendly, and broader public involvement through the internet and Web 2.0. New smart technologies give people’s movements unprecedented possibilities of communication to reach wider audiences, mobilize new activists, and negotiate with institutional actors. Affordable, user-friendly, accessible ‘WebGIS’ includes open-source GIS software packages, alongside sophisticated

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techniques to handle the cognitive and value aspects, such as multi-criteria decision analysis and artificial intelligence (AI) (Voinov et al., 2016; Ros-Tonen et al., 2021). PM has been claimed by community organizations and leaders in grassroots efforts to empower or care for their communities, for example: crowdsourced resource mapping, needs assessment mapping exercises, and harm-reduction initiatives that map areas of safety or danger for vulnerable populations. Projects such as these point to the strength of PM as a powerful platform for collaboratively exploring and preserving local and traditional knowledge, and a highly effective way to ready that knowledge for mobilization to effect social change and address systemic inequities. In some versions such as Ushahidi, the tool is so powerful that it has been used to counter corrupt governments and processes, allowing participants to create new ways of knowing in governance structures. The number of tools built to support PM has increased rapidly in the last decade. Since 2010, more than a dozen PM geospatial software systems have been created and are now widely used around the world. Some have been developed by private corporations, some by community groups or governments, each with their own technical requirements. However, many remain difficult to use by those unfamiliar with GIS. This edited volume strives to analyze a significant range of 9 PM software under a shared common evaluative framework to create a quick reference guide for novice users, reducing the time and resources needed, and making mapping technologies more accessible and affordable to a wider audience. GIS connects data to a map by integrating location data with myriad types of descriptive information. GIS helps users understand patterns, relationships, and geographic contexts. Before the 1990s, GIS was mostly utilized by governments, including the military, private interests to monitor local populations, evaluate strategic resources, and monitor environmental changes. Early GIS software could only be used by technical experts who received extensive training. Due to their specialized knowledge, these experts often held an almost monopoly of decision-making power on the methods used to collect, manage, and analyze spatial data. The users would rarely gather input in a collaborative or participatory manner from the public, and the results were rarely subjected to local public scrutiny (Burnett, 2022).

1.3 What to Consider When Choosing a Participatory Mapping Software? More complex and technologically sophisticated tools in PM generally require more work and training. GIS technologies that increase mathematical accuracy may create a false sense of positivism and scientific knowledge. There’s some level of methodological knowledge required to use participatory mapping software. Esri ArcGIS has been the industry standard GIS desktop software for decades, but free and open-source software for geospatial (FOSS4G) alternatives, like QGIS and web-based open-data software like OpenStreetMap, are proving to be just as

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impactful (and more cost effective). However, many marginalized and underrepresented communities have specifically chosen not to work with open data platforms for fear of comprising sensitive resources. As a result, Indigenous communities have chosen to create their own data storage systems such as Mukurtu, Nunaliit, and Terrastories. To date, there is no comprehensive guide to selecting geospatial software for PM. This makes it incredibly difficult for users to choose the appropriate software for their project given the diversity of internal and external needs and factors. Investing in any specific application can have serious financial implications and might increase negative perceptions of the PM process if decided on too hastily. Evaluating Participatory Mapping Software is the first edited volume on the topic. Its authors aspire to support ethical engagement and use of PM software and to assist practitioners in choosing the best software to suit a particular project’s needs. This book is intended for colleges and universities, research institutions, NGOs, community activist groups, and individuals who are interested in working in geospatial design and engineering, environmental policy, system services, governance and public policy, natural resource management, conflict analysis and resolution, GIS and society, and community-based applications. This section outlines the methods of the evaluation framework. Not all the software reviewed were specifically created for PM, but they meet most of the users’ basic needs. Although this volume reviews to nine software, the International Society for Participatory Mapping (ISPM) has identified twenty-two software tools (see Table 1.1) that are useful for PM: ten mapping applications, seven surveying and crowdsourcing tools, and five mapping management systems that were designed for group participation and planning (ISPM, 2020). There is a wide array of geospatial tools available to help support PM. For example, Field Papers allows users to create paper maps and upload them as polygon and point layers with a QR code; Survey123 provides a more sophisticated survey than ArcGIS Collector (but can still be connected to ArcGIS); and Maptionnaire and Ushahidi are crowdsourcing data collection and analysis tools, both increasingly used in urban and disaster relief planning. Table 1.1 offers an overview of common PM software available as open source or for a fee. Sometimes no single software exists that does everything required. Multiple software must be used, or add-ons that allow for additional features. Therefore, the chapters also refer to additional platforms and add-ons that help facilitate participatory GIS.  Other applications that were not essential to the participatory process were excluded from this book. For such additions, we recommend visiting the software’s user manual and speaking to a representative. This book is meant to be a quick reference guide that will be updated periodically and offered in multiple different languages. Each chapter follows a general framework of evaluation to ensure that the information within the volume can be updated to follow the ever-changing technological environment. The evaluation themes were identified through a robust review of the literature on evaluating PM and feedback from technical experts using PM applications. This framework does not exclude volunteer geographic information (VGI) applications

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Table 1.1  List of Common Participatory Mapping Software. Published by the International Society of Participatory Mapping (ISPM) 2019

Name Collector for ArcGIS

Field Papers

GeoODK

Geopaparazzi

gvSIG Mobile

OpenDataKit (ODK)

OpenMapKit (OMK) KoBoToolbox

Sapelli

Type of Application Mobile online/ offline spatial data collection

Description of Features Basic data collection functionality; connected to ArcGIS platform and environment Paper-based field Printed maps for mapping participatory mapping exercises in the field, that can be georeferenced using a QR code. Integrated with Mapbox and OSM, custom layers are possible as well. Application built on top Mobile online/ of ODK interface with offline spatial enhanced geographical data collection capacity Application developed to Mobile online/ do very fast qualitative offline spatial engineering/geologic data collection surveys and GIS data collection; gvSIG compatibility Application built to be Mobile online/ offline spatial used with the open-­ data collection source gvSIG platform Custom forms for data Mobile online/ collection, and other offline data collection (with tools; aggregation system or hosting on geopoint service like Google Apps functionality) Extension of ODK; Mobile online/ OpenStreetMap-powered offline spatial field data collection tool data collection Suite of field data Mobile online/ collection tools offline spatial developed specifically data collection for working in humanitarian crises Mobile online/ offline spatial data collection

Licensing or Cost Proprietary commercial software

Affiliated Organization or Institution Esri

Free and open-source

Stamen Design

Free and open-source

GeoMarvel

Free and open-source

HydroloGIS

Free and open-source

gvSIG

Free and open-source

Community of developers

Free and open-source

American Red Cross

Free and open-source

Harvard Humanitarian Initiative, Brigham and Women’s Hospital Extreme Citizen Science (ExCiteS)

Free and Data collection across open-source language or literacy barriers through highly configurable icon-driven user interfaces

(continued)

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8 Table 1.1 (continued)

Name Survey123

Type of Application Mobile online/ offline spatial data collection

GIS Cloud

Mobile data collection

Crowdsource Polling and Crowdsource Reporter

Map-based tools for submitting feedback to local government

Emotional Maps Participatory mapping surveys

Maptionnaire

Participatory mapping surveys

Map Your World

Participatory mapping surveys

SeaSketch

Collaborative marine spatial planning platform

Licensing or Description of Features Cost Customizable forms for Proprietary commercial data collection akin to ODK, more sophisticated software than ArcGIS Collector; connected to ArcGIS platform and environment Free and Solution for field data collection that allows pay-as-­ you to collect points, you-go lines and polygons with pricing a smartphone; connected to GIS Cloud platform and environment Proprietary Intended to solicit commercial feedback or gauge software sentiment on local government plans, submitting problems, and to create dialogue between members of the community; connected to ArcGIS platform and environment Online web-map surveys Free (contact the focused on emotional developers) mapping of users’ relationship with their lived environment Fee structure User-friendly depending on questionnaire creation; interpretation and insight type of plan of results Free Online mapping tool targeting youth to explore issues and ideas to make change in their communities Licensing fee Using a map interface, stakeholders can generate proposals representing a range of proposals, to help make better management decisions

Affiliated Organization or Institution Esri

GIS Cloud

Esri

Palacky University Olomouc

Mapita

Map Your World

SeaSketch

(continued)

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Table 1.1 (continued)

Name Ushahidi

GIS Cloud

Mapeo

Portable OpenStreetMap (POSM)

Type of Application Custom surveys and crowdsourcing tools

Description of Features Set of tools designed to crowdsource, analyze, visualize and respond to timely data about events or crises

Crowdsourcing solution for organizations, cities, public and anonymous users. Anonymous users can submit reports, including photos and comments, of any kind using Mobile or Web App. Citizens can review existing reports, comment or vote on reports and observations submitted by others; connected to GIS Cloud platform and environment Offline map Utilizes editor and editing software flexible data structure from OpenStreetMap to enable offline mapping, collaboration, and data sharing control Hardware device POSM broadcasts a wireless signal that other loaded with offline versions devices can connect to access tools that of cloud-based ordinarily require an software internet connection, making it possible to take all parts of a mapping workflow offline; includes support for ODK, Field Papers, OpenStreetMap, and other tools Custom surveys and crowdsourcing tools

Licensing or Cost Pay-as-­ you-go pricing (with basic free option), source code on GitHub Proprietary commercial software

Free and open-source

Affiliated Organization or Institution Ushahidi

GIS Cloud

Digital Democracy

American Red Software is free and open Cross source; hardware costs ~$300

(continued)

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Table 1.1 (continued)

Name Terrastories

Trailmark

GIS Cloud

Type of Application Offline-­ compatible geostorytelling application

Description of Features Mapping content management system designed to link audiovisual content with a Mapbox-driven vector tile map; equipped with a login system for restricted access stories and mapping content; entirely functional offline, compatible with Mapbox Studio; designed for remote communities Mapping content Web-based software intended for management communities to manage system for land use and traditional traditional knowledge information; knowledge application (for iOS, Android, and Windows Mobile) for mobile data collection Online map GIS Cloud’s Map Editor editing tool is a cloud-based map tool for building and sharing your maps. It supports a number of vector and raster formats, rich GIS symbology, and has built-in collaboration capabilities for real-time editing and sharing.

Licensing or Cost Free and open-source

Affiliated Organization or Institution Amazon Conservation Team

Pay-as-­ you-go pricing (with basic free option)

Trailmark Systems

Proprietary commercial software

GIS Cloud

as a form of PM, in circumstances where its application is promoted from the bottom-­up with the intent to empower and spark political or behavioral change. The key themes include (1) general information about the tool, (2) ethics surrounding the software, (3) costs associated with its use, (4) the technical level of expertise needed to use it, (5) inclusiveness, (6) accuracy, (7) data privacy, (8), analytical capacity, (9) visualization capacity, and (10) openness, and (11) accessibility. Each chapter also includes a brief use case(s) to demonstrate a tool’s features and provide context for its use. The evaluation themes reflect common debates in the field and deserve careful reflection.

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1.3.1 General Information The first section of each chapter provides an overview of general information on the software, its developer, what type of programming and system software is used, whether there’s an application programming interface (API), general cost, and the type of data that it can collect. The goal is to provide a comparative narrative for the quick reference guide found in Annex I. The guide provides a brief overview of key aspects of participatory mapping software to help guide new and old users in selecting the right software application. There are several practical elements that can be compiled and compared quickly and updated frequently. Software and tech companies are constantly adapting, adding features, and revising their look and feel of their platforms.

1.3.2 Ethics The second section focuses on the ethical and philosophical concerns relating to that specific software system. Many ethical issues present troubling dilemmas, and lead to profound questions about empowerment and ownership (Chambers, 2006; Rambaldi et al., 2006a; Fagerholm, 2014). Ethics surrounding software are complex and require political lenses which become sources of contention for companies and the public. As practitioners, we must create space to discuss these tensions and the real safety concerns for users and communities. Ethical issues might appear to be marginal ‘optics’, such as a software company’s involvement in the extractive industries that the PM project is struggling against. Data sovereignty and data confidentiality are the most significant ethical issues in PM. Practitioners must ask themselves who owns the data after their collection. Will the data collected fall into the wrong hands to be exploited by private or government organizations? Do the spatial data have the potential to do harm later? For example, certain software companies are supporting the extraction of fossil fuels, such as ESRI’s use in the Niger Delta by petroleum companies, or they assist in military operations that violate human rights, such as Google’s role in the erasure of Palestinian roads in the West Bank (Cristiano & Distretti, 2021). If PM is supposed to empower local communities to make decisions for themselves that are sustainable, these ethical questions come into play. Rambaldi et al. (2006a) provide a comprehensive overview of the “Who” and “Whom” questions that can serve as a guide for interrogating the specific contents of projects. Asking these questions might not be able to prevent every political issue surrounding a particular context, but it will at least prepare practitioners for what might happen during a participatory mapping process. Applications of PM very often have a particular purpose and objective in reducing power inequalities and finding solutions that will meet the needs of the community at large, not just those with access and social and financial capital.

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1.3.3 Cost The cost of PM can be as limited as a few sheets of paper, or, up to several hundred thousand dollars for a custom-built GIS application. This makes it hard to choose a specific method or software without extensive research. There are many free and accessible options, such as QGIS or GeoDa, but depending on research needs, free options may not work in every context. Perhaps large amounts of data need to be stored, or highly sophisticated analyses conducted. The cost of the software is only the bare minimum consideration when thinking about costs. Some software requires very specific technical support, such as database and server management, or e.g., for environmental scientists to collect very specific species data. In addition to the financial costs, practitioners must ask themselves about the costs of using participatory GIS in terms of accessibility, equity, and usability. The more complicated and complex the software becomes; the less likely underrepresented groups will be able to participate or feel that the decision-making process is fair (Brown & Kyttä, 2018). This can introduce social strife between ‘in’ and ‘out’ groups leading to feelings of injustice and frustration (Haworth et al., 2016). In Sect. 1.3, the costs associated with specific software are explored, including additional unforeseen costs that are only appreciated with the experiences of using the tool firsthand. An issue regarding “costs” is the relative investment demanded of participants. A few hours for a rich PM volunteer might cost them a tiny portion of their salary, for a poor person, taking time out could mean losing a day’s wage or not eating. These are real concerns in selecting software because lengthy training workshops may not be an option for marginal communities. Oftentimes, practitioners do not realize the costs of their research on local populations.

1.3.4 Technical Level There are many different PM methods that range from simple (such as ground mapping) all the way to highly sophisticated and complex (such as ESRI GIS and QGIS with Python). The technical level of expertise needed for using and for adequate understanding of PM software is critical to stakeholder engagement and behavioral change adaption. Unlike large commercial software, PM software tends to have a limited number of users, usually in the order of hundreds or thousands at most. The overall goal of the users may not be to increase the software’s user base, but simply to effectively gather data from communities. Disadvantaged communities are often the focus of PM initiatives, and their users’ digital literacy might not be sufficient (Ballatore et  al., 2019). Some users will inevitably decide to use a chauffeur1, a technician, or a local NGO affiliate, to map the data given to them by stakeholder on their behalf.

 A “chauffeur” in participatory mapping is a technical expert who works with the community to assist in mapping key points and polygons when participants lack sufficient technological literacy. 1

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Although this may seem appropriate for certain PM scenarios, evidence suggests that using a chauffeur can reduce the overall understanding of how the data were collected, stored, and processed by stakeholders (Burnett, 2020). Using a chauffeur cuts participants off from the technology which can then lead to lower levels of trust and cooperation between all parties/stakeholders. PM project administrators and users note that visualizing data, especially during the analysis phase, plays a critical role in the way participants view the overall process and this influences the likelihood of acceptance (Weiner et al., 2002).

1.3.5 Inclusiveness The notion that research should actively engage and promote the inclusion of individuals and social groups affected by the outcomes has been promoted by popular education movements, PNS strategy, environmental justice activism, and in feminist research (Cavalier & Kennedy, 2016; D’Ignazio & Klein, 2020; Elwood, 2008; Elwood & Leszczynski, 2018; Radil & Anderson, 2019). Although convening institutions and project administrators are responsible for ensuring the equitable participation of community stakeholders, some PM software provides a more inclusive environment for its users. Software like SeaSketch has interactive fora that allow users to engage in conversation when not in person. Others like Maptionnaire have a reporting dashboard and teams which allow for the monitoring of specific groups’ participation. Creating features specifically designed to increase inclusiveness are important. The chapters critically review each software system for inclusivity by examining if the software application supports stakeholder mapping to provide multiple diverse ways of learning and relaying information, as well as how specific aspects of the software might inhibit engagement of stakeholders in the decision-­ making process.

1.3.6 Data Accuracy A goal of utilizing participatory GIS software instead of traditional non-­technological PM methods is to increase data accuracy and data credibility. The significance of the fuzziness of citizen scientific data was addressed by McCall (2006) in terms of interrogating the need for ‘accuracy’ in PM but is rarely embedded into design principles for PM software. Brown et  al. (2018) focused on validity-as-credibility, a perspective for PM and VGI that seeks to account for data quality based on the characteristics of citizen contributors. They explore what validity means to the human consciousness and its value compared to actual concrete physical accuracy. There have been relatively few studies that evaluate participant-related variables of data quality relating to citizen-focused data collection (Vergara-Asenjo et al., 2015). One consistent participant variable found to influence spatial data quality is participant familiarity and experience in the geographic study area (Brown, 2017). The

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chapters examine how the software applications ensure data accuracy and what specific features enable or hinder data accuracy. Perhaps this will catalyze a deeper dive into this issue by major PM software developers.

1.3.7 Data Privacy As already introduced in evaluation topic 2, data privacy is a major concern for underrepresented groups, including First Nations and indigenous peoples, because PM projects often collect and disclose information that can be used to undermine sovereignty and steal resources. Sociocultural and contextual differences have a strong impact on the perceptions of data sensitivity. Since the PM of indigenous lands and resources is increasingly seen as a precondition for securing legal recognition of indigenous land rights, sensitive traditional and local knowledge are being extracted. Increasingly, data are collected via multimodal sensors on mobile phones. A typical participatory sensing application operates in a centralized fashion (i.e., the sensor data collected by the phones of volunteers are reported to a central server for processing) (Christin et  al., 2011). Who collects, analyzes, and stores the data is extremely political. Inappropriately sharing data or not disclosing uses of the data jeopardizes the participatory process and can generate conflicts (Kyem, 2021; Brown & Raymond, 2014).

1.3.8 Analytical Capacity Many VGI applications are used in the collection of spatial data, and many of them do not have in-depth internalized analytical capacities. Such applications still require users to download a copy of the data and upload it into a third-party system, such as QGIS or Carto, to conduct queries and reasoning, measurements, transformations, descriptive summaries, optimization, and hypothesis testing. This process requires the data to pass through multiple platforms, computers, and hands to conduct the analysis, and moves stakeholders further away from the process. Stakeholders may understand how the platform works to collect data, but the results of the analyses might seem strange or incomprehensible once synthesized. Brown and Kyttä (2018) identified that achieving clarity in PM purpose and building trust in the process are the most critical issues in the field. The chapters critically evaluate each platform’s ability to conduct analyses, and they lead participants through the process of understanding the outcomes, including noting how accessible tutorials and education material are for users.

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1.3.9 Visualization Capacity PM project administrators and users note that visualizing data, especially during the analysis phase, plays a critical role in the way participants view the overall process and this influences the likelihood of acceptance (Weiner et al., 2002). It is widely accepted that visual research methods can help participants to externalize their perceptions and experiences more clearly and thus create a space for reflective dialogue (Sun et al., 2013; Reeves, 2015). PM software must adopt methods of visualization that are participatory and egalitarian. For decades, the standard for cartographic visualization was paper maps. Graphic visualization has changed drastically over time; cartographers now can create interactive maps that move and project clickable objects. For some PM project needs, paper maps may be sufficient to relay information to participants, but new ways of visualizing PM have emerged for newer applications. Mapping the spatial distribution of landscape values, land use preference differences, and combined values and preferences scoring indices make static mapping difficult (Brown & Raymond, 2014). As planning applications move towards virtual and augmented reality, pressure for GIS software applications to incorporate 3D and interactive models has increased. Each chapter includes a section that reviews the software’s visualization capacity and limitations.

1.3.10 Openness Debates around free software (FS) and open-source software (OSS) are quite common in PM. The FS movement originated in the late 1970s in response to the privatization/commercialization of software that put restrictions on users to modify (unknown source code) and share (licensing) programs (Wubishet et  al., 2013;  Thomas, 2010). Practitioners have become more sensitive to the needs of marginalized communities and Indigenous peoples. Not only are FS and OSS more cost effective, but they are also an effective way to ensure sovereignty and ownership. The ability to host open-source software on a stakeholder-owned server or decentralized system appeals to local groups who collect and manage sensitive data. OSS also allows for developers to design platforms that fit their unique requirements and crowd-source solutions among users which makes practitioners less reliant on a single company or corporation for answers.

1.3.11 Accessibility Effective participation is key to good participatory GIS practice. Cost is not the only barrier to accessing PM software. In many places around the world, citizens still struggle to access reliable internet and smartphone technology. PM facilitators must

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expect that societies most at risk and marginalized will not have access to the same level and quality of technology as privileged individuals and societies. The overall cost of connecting to the internet is high for those in developing countries and rural communities. Even though participatory applications have become more widespread, and computers are becoming more affordable and user-friendly, it is still difficult for many community-based organizations to afford to recruit experts to implement, maintain, and sustain high-tech solutions (Rambaldi et al., 2006b). A lack of accessibility to the technology leads to biases that can alter the outcome of a PM process as well as the long-term sustainability of any proposed solutions (Brown, 2017). The chapters explore the accessibility each software has for people in resource-scarce communities.

1.4 Brief Use Case(s) In addition to utilizing the above evaluation framework, each chapter provides readers with a case study illustrating how convening organizations and the public made use of the software to implement a PM project. Case studies include, but are not limited to the use of Mapbox by public consultants in the Jeżyce neighborhood in Poznań, Poland trying to gather community input on their perception of public transportation (p. 37), the Eelgrass Protection on Fishers Island, New York project which used SeaSketch and sought to create a coastal and watershed management plan to help protect eelgrass (Zostera marina) meadows surrounding Fisher’s Island, New York, (p. 140), and the case of the Ohneganos research program that co-created indigenous water quality tools using Terrastories (p. 190). The goal was to outline a diverse set of use cases that demonstrates PMs wide-ranging applicability.

1.5 Comments and Recommendations A team of technical specialists, developers, and expert researchers wrote each chapter to ensure this edited volume’s practical use in the field. The comments and recommendations section allows authors to elaborate on each specific software, lessons learned in practice, and potential pitfalls not covered by the evaluation framework.

1.6 Volume Overview This edited volume has brought together an array of technical experts, developers, research scientists, and scholars from fields as wide as environmental science, natural resource management, satellite imagery, geography, cartography, governance, conflict resolution, urban planning, computer science, mathematics, public policy,

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human rights, international law, marine and oceanic science, social science, critical theory, engineering, and international development. PM stands out as a methodological approach valued and applied by these often siloed technical and philosophical fields. Fields that stand at opposite ends of the academic spectrum have found PM and GIS to be a valuable tool in accomplishing their research and practical real-life goals. Despite its well-founded ability to bring people together to generate and benefit from their local spatial knowledge which had often been suppressed and un-valued, critiques of participatory GIS persist. This volume would not do its readers justice without being transparent and forthright about them. Critiques of participatory GIS primarily focus on claims that participatory GIS can disempower or marginalize communities through the complexity of the technology, the high associated costs, the loss of privacy and ownership of local data, and a lack of genuine community participation (Sletto, 2009; Radil & Anderson, 2019). • PM can throw up hidden latent conflicts with deep roots in unresolved inequities—sleeping dogs can be woken up (Brown & Raymond, 2014; Kyem, 2021; Haklay, 2013). • Cartographic methods frequently struggle with issues of appropriate representation. How can maps cope with metaphorical or cosmological indigenous imagery, or emotive, mental maps of any kind? (Sletto, 2009; Woods & Scanlon, 2012). • Standard GIS has a natural inclination towards positional precision (that is often a false precision), vis-à-vis representational accuracy (D’Ignazio & Klein, 2020; Elwood, 2008; McCall, 2006). • Then, the unpacking of representativity. Who is invited and involved in the mapping? Who do they ‘speak for’? because these determine what is being mapped and how the mapped products will be used (Brown, 2017; Chambers, 2006; McCall, 2021) The academic and professional planning fields are applying participatory GIS to cultivate or develop new ways of knowing and doing for communities who may have had scant opportunity to participate in decision-making. Although exciting, these promises could stir false expectations that create feelings of suspicion, divisiveness, hostility, and anger by those who did not get the outcome that they desired. PM should draw from lessons in international development and social movements theory to develop approaches that manage these expectations and prevent external institutions from setting expectations too high. As international development organizations scramble to repair broken relationships with local communities, scientists, facilitators, and scholars, they should be careful not to repeat past failures of hubris and assumptions of technological superiority. The future of PM and GIS shows great promise for promoting democracy, good governance, and transparency. Combined with new technology such as virtual and augmented reality, this could empower future generations who can participate in public development and planning from the comfort of their home. Imagine an exploratory GIS software that allows citizens to see proposed development designs of an old community space and choose or comment on them in real time. Technology

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has the power to provide citizens with access to data and decision-making features like never before, doing away with the need of representative government. It’s about finding the balance between enticing user engagement, increasing ease of use, and making it openly accessible to all. In its history, GIS has been used in warfare and the destruction of communities, while today and tomorrow, it can support communities. The outcome is truly in the hands of those who further develop and wield these powerful tools.

References Ballatore, A., McClintock, W., Goldberg, G., & Kuhn, W. (2019, June). Towards a usability scale for participatory GIS.  In The international conference on geographic information science (pp. 327–348). Springer. Brown, G. (2017). A review of sampling effects and response bias in internet participatory mapping (PPGIS/PGIS/VGI). Transactions in GIS, 21(1), 39–56. Brown, G., & Kyttä, M. (2018). Key issues and priorities in participatory mapping: Toward integration or increased specialization? Applied Geography, 95, 1–8. Brown, G., & Raymond, C. M. (2014). Methods for identifying land use conflict potential using participatory mapping. Landscape and Urban Planning, 122, 196–208. Brown, G., McAlpine, C., Rhodes, J., Lunney, D., Goldingay, R., Fielding, K., & Vass, L. (2018). Assessing the validity of crowdsourced wildlife observations for conservation using public participatory mapping methods. Biological Conservation, 227, 141–151. Burnett, C. M. (2020). Incorporating the participatory process in the design of geospatial support tools: Lessons learned from SeaSketch. Environmental Modelling & Software, 127, 104678. Burnett, C.  M. (2022). Evaluating perceptions of participatory mapping for public decision-­ making using SeaSketch (Doctoral dissertation, University of Massachusetts Boston). Cavalier, D., & Kennedy, E.  B. (Eds.). (2016). The rightful place of science: Citizen science. Consortium for Science, Policy & Outcomes. Chambers, R. (2006). Participatory mapping and geographic information systems: Whose map? Who is empowered and who disempowered? Who gains and who loses? Electronic Journal of Information Systems in Developing Countries (EJISDC), 25(1), 1–11. Chevalier, J. M., & Buckles, D. J. (2019). Participatory action research: Theory and methods for engaged inquiry. Routledge. Christin, D., Reinhardt, A., Kanhere, S. S., & Hollick, M. (2011). A survey on privacy in mobile participatory sensing applications. Journal of Systems and Software, 84(11), 1928–1946. Cristiano, F., & Distretti, E. (2021). Toward an Aesthetics by Algorithms—Palestinian Cyber and Digital Spaces at the Threshold of (In) visibility. In The Aesthetics and Politics of the Online Self (pp. 129–148). Palgrave Macmillan. D’Ignazio, C., & Klein, L. F. (2020). Data Feminism. MIT Press. Ellis, F., & Biggs, S. (2001). Evolving themes in rural development 1950s-2000s. Development Policy Review, 19(4), 437–448. Elwood, S. (2008). Volunteered geographic information: Future research directions motivated by critical, participatory, and feminist GIS. GeoJournal, 72(3–4), 173–183. Elwood, S., & Leszczynski, A. (2018). Feminist digital geographies. Gender, Place and Culture, 25(5), 629–644. Fagerholm, N. (2014). Whose knowledge, whose benefit? Ethical challenges of participatory mapping. In J. Lynn (Ed.), Fieldwork in the global south: Ethical challenges and dilemmas (pp. 158–169). Routledge.

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Haklay, M. (2013). Citizen science and volunteered geographic information: Overview and typology of participation. In Crowdsourcing Geographic Knowledge (pp. 105–122). Springer. Haworth, B., Whittaker, J., & Bruce, E. (2016). Assessing the application and value of participatory mapping for community bushfire preparation. Applied Geography, 76, 115–127. ISPM. (2020). Software and Tools. International Society of Participatory Mapping Website. Retreived from http://landscapevalues.org/ispm/software-­tools/ Kidd, S. A., & Kral, M. J. (2005). Practicing participatory action research. Journal of Counseling Psychology, 52(2), 187. Kyem, P. A. K. (2021). Managing natural resource conflicts with participatory mapping and PGIS applications. Springer. https://doi.org/10.1007/978-­3-­030-­74166-­2 McCall, M. K. (2006). Precision for whom? – Mapping ambiguity and certainty in (Participatory) GIS. Participatory Learning and Action, 54, 114–119. McCall, M. K. (2021). Participatory mapping and PGIS: Secerning facts and values, representation and representativity. IJEPR International Journal of E-Planning Research, 10(3), 105–123. McCall, M.  K., Martinez, J., & Verplanke, J. (2015). Shifting boundaries of volunteered geographic information systems and modalities: Learning from PGIS. ACME: An International Journal for Critical Geographies, 14(3), 791–826. Pecchia, A., Cinque, M., Carrozza, G., & Cotroneo, D. (2015). Industry practices and event logging: Assessment of a critical software development process. In 2015 IEEE/ACM 37th IEEE international conference on software engineering (Vol. 2, pp. 169–178). IEEE. Radil, S. M., & Anderson, M. B. (2019). Rethinking PGIS: Participatory or (post) political GIS? Progress in Human Geography, 43(2), 195–213. Rambaldi, G., Chambers, R., McCall, M., & Fox, J. (2006a). Practical ethics for PGIS practitioners, facilitators, technology intermediaries and researchers. Participatory Learning and Action, 54(1), 106–113. Rambaldi, G., Kyem, P.  A. K., McCall, M., & Weiner, D. (2006b). Participatory spatial information management and communication in developing countries. The Electronic Journal of Information Systems in Developing Countries, 25(1), 1–9. Reeves, L.  S. (2015). Visualizing participatory development communication in social change processes: Challenging the notion that visual research methods are inherently participatory. International Journal of Communication, 9, 20. Ros-Tonen, M.  A. F., Willemen, L., & McCall, M.  K. (2021). Spatial tools for integrated and inclusive landscape governance: Toward a new research agenda. Environmental Management, 68, 611–618. Sieber, R. E., Robinson, P. J., Johnson, P. A., & Corbett, J. M. (2016). Doing public participation on the geospatial web. Annals of the American Association of Geographers, 106(5), 1030–1046. Sletto, B. I. (2009). “We drew what we imagined”: Participatory mapping, performance, and the arts of landscape making. Current Anthropology, 50(4), 443–476. Sun, G. D., Wu, Y. C., Liang, R. H., & Liu, S. X. (2013). A survey of visual analytics techniques and applications: State-of-the-art research and future challenges. Journal of Computer Science and Technology, 28(5), 852–867. Thomas, B.  K. (2010). Participation in the Knowledge Society: The Free and Open-Source Software (FOSS) movement compared with participatory development. Development in Practice, 20(2), 270–276. Turnhout, E., Van Bommel, S., & Aarts, N. (2010). How participation creates citizens: Participatory governance as performative practice. Ecology and Society, 15(4), 26. United Nations. (2001). Information for Decision-making and Participation. E/CN.17/2001/19. 9th session of the Comission on Sustainable Development. Vergara-Asenjo, G., Sharma, D., & Potvin, C. (2015). Engaging stakeholders: Assessing accuracy of participatory mapping of land cover in Panama. Conservation Letters, 8(6), 432–439. Vogt, N., Pinedo-Vasquez, M., Brondízio, E. S., Rabelo, F. G., Fernandes, K., Almeida, O., et al. (2016). Local ecological knowledge and incremental adaptation to changing flood patterns in the Amazon delta. Sustainability Science, 11(4), 611–623.

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Voinov, A., Kolagani, N., McCall, M.  K., Glynn, P.  D., Kragt, M.  E., Ostermann, F.  O., et  al. (2016). Modelling with stakeholders – Next generation. Environmental Modelling & Software, 77, 196–220. Warf, B., & Sui, D. (2010). From GIS to neogeography: Ontological implications and theories of truth. Annals of GIS, 16(4), 197–209. Weiner, D., Harris, T. M., & Craig, W. J. (2002). Community participation and geographic information systems. In Community participation and geographical information systems (pp. 3–16). CRC Press. Wing, M.  G., & Bettinger, P. (2008). Geographic information systems: Applications in natural resource management. Oxford University Press. Wood, D. (1992). The power of maps. Guilford. Woods, W., & Scanlon, E. (2012). iSpot Mobile-A natural history participatory science application. Wubishet, Z. S., Bygstad, B., & Tsiavos, P. (2013). A participation paradox: Seeking the missing link between free/open source software and participatory design. Journal of Advances in Information Technology, 4(4), 181–193. Young, J., & Gilmore, M. (2017). Participatory uses of geospatial technologies to leverage multiple knowledge systems within development contexts: A case study from the Peruvian Amazon. World Development, 93, 389–401.

Chapter 2

Mapbox

Michał Rzeszewski

Abstract  Mapbox (mapbox.com) is a location platform company that provides various tools for visualizing and analyzing spatial data. It is one of the largest commercial providers of high-performance maps and navigation tools and is used by companies, government agencies, and organizations of all sizes. Mapbox supplies its users with foundational map data, navigation and geocoding capabilities, and a large variety of styling tools to customize the look of maps that can be hosted on Mapbox servers. While Mapbox excels at providing visualization capabilities, its coding libraries can be used to develop custom applications that can further extend the range of functions. Mapbox is an excellent solution to consider when looking for participatory mapping tools, mainly when: data is already gathered, and an engaging presentation is needed; a highly customized application with dynamic interaction is required; there are large datasets that need to be displayed; the single stakeholder will create data and when there is limited GIS knowledge. In addition to the above points, the Mapbox Community team (mapbox.com/community) can provide guidance and mentorship to PPGIS projects investigating whether Mapbox tools are a good fit for their needs, even in the earliest phases of a project. Keywords  Mapbox · Cities · Community participation · Citizens science · Mapping · GIS

2.1 General Information Name of Application: Mapbox.com Name of Developer: Mapbox Name of Funder: Mapbox Type of System Software: Web application M. Rzeszewski (*) Adam Mickiewicz University, Poznań, Poland e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 C. M. Burnett (ed.), Evaluating Participatory Mapping Software, https://doi.org/10.1007/978-3-031-19594-5_2

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Type of Programming Language: HTML, CSS, JavaScript, AppleScript, C++, Java, Kotlin, Objective-C, and Swift API Availability: Desktop and Mobile Features: Web mapping, hosting, data provider Cost: Free and pay-as-you go services Type of Data Collected: Geographic and Descriptive, points, lines, polygons Mapbox (mapbox.com) is a location platform company that provides a wide variety of tools for visualizing and analyzing spatial data as well as numerous web services and libraries aimed at developers that want to build location-based applications for web, mobile, and embedded systems (such as in-car navigation panels or smartwatches). Mapbox supplies foundational map data (terrain, streets, place names etc.), navigation tools (for routing and directions), geocoding tools (for place name search and to convert addresses into geospatial coordinates), styling tools to customize the look of maps, hosting for custom map data, and coding libraries to make it easier for developers to build with mapping features. Mapbox is one of the largest commercial providers of high-performance maps and navigation tools and is used by companies, government agencies, and organizations of all sizes (Fig. 2.1). Some participatory mapping projects may find that existing apps or websites might not meet all requirements or customizations that are necessary. In that case, tools that support the creation of custom applications are needed. Mapbox is one source of such tools, providing the components needed to build custom map applications. One of the features that is important for participatory mapping purposes is

Fig. 2.1  Mapbox provides maps that can be used within mobile apps such as the hiking app AllTrails

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that Mapbox provides generous technical support and account help to nonprofits and other organizations using Mapbox tools for positive social and environmental impact.

2.2 Ethics Ethical considerations are essential for every PPGIS project (Rambaldi et al., 2006) as it involves vulnerable people, data, and practices based on mutual trust. Mapbox is one of the providers that are very open and straightforward in what it is gathering about its users. Even more critical is how ownership of the data is being respected. Mapbox Terms of Service (TOS) declare that all legal rights to the uploaded content remain with the user. Users do grant some rights to Mapbox to create and distribute maps, which is necessary for Mapbox systems to serve data and map tiles to the projects that users build. Mapbox collects minimal personal data about users and when an account is deleted, Mapbox deletes user data as well. Data security is also taken seriously with SOC 2 Type 2 protocols in place. There is also an active bounty from Mapbox on HackerOne – a service that allows independent people to find and report security vulnerabilities for a prize. In its Service Terms, Mapbox also prohibits any use of their products in ways that violate fundamental human rights or civil liberties, terms that are investigated and enforced by Mapbox if evidence of violations by any user is reported or discovered.

2.3 Cost For most participatory mapping projects and projects by nonprofits or community organizations, Mapbox is free to use. Mapbox operates on a ‘pay-as-you-go’, usage-­ based pricing model with free tiers that are enough to cover most smaller-scale projects (details at https://www.mapbox.com/pricing/). The free thresholds do vary by product, so users should check the pricing information for each of the specific products needed. The browser-based map styling tool, Mapbox Studio, is free to use with two caveats. The first is that all Mapbox accounts start with 100 print exports from Studio, if more are needed a user must contact the Mapbox Sales team to purchase additional exports (or contact the Mapbox Community to request a donation of additional exports for noncommercial projects). The second potential cost comes from uploading and hosting custom data within Mapbox. As of the time of writing, any data uploads done within the Mapbox Studio interface are free, but these are limited to a maximum of 300 megabytes per file (or less, depending on file type) and a maximum of 20 uploads per month. For data uploads beyond these limits, for

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automated updates, or for further fine-grained control over the creation of data tile sets, users must use either the Uploads API or Mapbox Tiling Service, both of which may incur charges for data processing and/or data hosting. Mapbox does also provide several specialty data products, including permanent geocodes (for storing the results of geocoding queries, for example to convert addresses to coordinates and then store those results in a database); Mapbox Boundaries tile sets (curated data tile sets of administrative, political, and statistical boundaries around the world); and Mapbox Movement and Mapbox Traffic (built from anonymized and aggregated telemetry data that can be used to analyze general population movement patterns or traffic speeds). These products are not available to all accounts by default and must be purchased by contacting Mapbox Sales (https:// www.mapbox.com/pricing). The Mapbox Community team can assist with requests for discounted or donated access to specialty data products for academic or non-­ profit projects.

2.4 Technical Level Technical requirements are the most common barrier to PPGIS. When the main goal is inclusion and wider active involvement, GIS mapping solutions are often lacking since the initial knowledge barrier is high. Mapbox requirements for the technical skill level of the user vary significantly between use cases. In general, Mapbox tools can be seen as relatively friendly for newcomers. The learning curve can be described as non-linear. Simple maps require almost no cartography or GIS related knowledge but more involved applications that for example deals with any kind of user input, or even display pop-ups, require users to be able to use web or mobile programming language. There are several options for using Mapbox tools with little to no coding required: Existing tools or plug-ins, Mapbox Studio, and Mapbox ‘Impact Tool’ templates. Beyond those options, the builders of custom applications using Mapbox should expect to use web development or mobile app development skills.

2.4.1 Existing Tools or Plug-Ins that Use Mapbox Mapbox is a popular tool for the developers of other applications that may be more familiar or require no coding to use. If you use a tool that supports third-party plugins, investigate whether a Mapbox option is available. There are numerous WordPress plugins available that use Mapbox. The design tool Figma has a Mapbox plugin. Data visualization tools Tableau and Microsoft Power BI (Fig.  2.2) both integrate with Mapbox for map-based visualizations. Mapbox also has integrations to use custom Mapbox map styles within GIS software tools QGIS and ArcGIS.

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Fig. 2.2  Mapbox visualization with Microsoft Power BI

Fig. 2.3  Custom Mapbox map ‘style’ used within the Terrastories application

2.4.2 Mapbox Studio Mapbox Studio is a browser-based tool available to every Mapbox account. Within Mapbox Studio users can create custom map ‘styles’ either from scratch or by modifying a set of templates. Map styles created in Mapbox Studio can be used in many other applications that can be useful for participatory mapping projects, such as Mapeo (https://www.digital-­democracy.org/mapeo) or Terrastories (https://terrastories.app/) (Fig. 2.3).

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If your mapping project does not need interactive maps but is focused more on creating a custom map style to use elsewhere, or a map-based data visualization, or creation of a static map image or print map, then Mapbox Studio may meet your needs without requiring any coding. The interface is like graphic design software but focused on the styling of map layers. It may be familiar to those who use GIS software, except that data analysis and data manipulation capabilities are limited (in most cases, users analyze and prepare data in a GIS prior to uploading it to Mapbox Studio). Mapbox Studio has a ‘print’ option to export high resolution images of custom map styles. Within Mapbox Studio the core basemap data layers (Fig.  2.4) are available already, such as place names, national boundaries, and roads, so it is not necessary to upload all the data needed to build a map. The existing data can be styled differently, removed, or replaced with custom data (Fig. 2.5). Users can focus on making a map look exactly the way they want and adding in any custom data needed. Custom data that is uploaded to Mapbox Studio is stored as ‘tilesets’ (which are not editable after uploading) or ‘datasets’ (which remain editable after uploading). Hosting data in Mapbox Studio allows data to be stored in the cloud and may be more efficient when loading in an application (because the data is divided into map ‘tiles’ that can be loaded individually as needed instead of the entire dataset being loaded). The process of creating a map with Mapbox Studio is further divided between an approach that uses so-called map ‘components’ and a more traditional layer-based interface. The former can be more friendly for less experienced map makers while the latter is more familiar for people coming from GIS background where layer metaphor is commonly used and in which case, they may find this approach significantly faster to learn and develop (Fig.  2.6). To fully utilize the potential of the

Fig. 2.4  Example of Mapbox Studio template map styles that can be selected as a basemap

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Fig. 2.5  An example of a customized map ‘style’ in Mapbox. All linear, polygon and point features can be styled according to user needs

Fig. 2.6  Mapbox Studio interface in ‘layers’ mode that is familiar for many GIS users or designers

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Mapbox Studio environment however, it is necessary to use both layers and components. When it comes to publishing and sharing a finished map style, Mapbox has both beginner-friendly and technically demanding options, depending on the target end product. For one thing it is almost effortless to publish a “preview” map that is hosted on Mapbox servers and that can be shared through a simple URL, the only drawback being that the map will have a small overlay pointing to Mapbox webpage and cannot be further modified with interactivity. For many cases this will be enough, since it allows sharing geodata in a very fast, efficient, and aesthetically pleasing form. The intended way to use a map style is within a custom application developed for web (Mapbox GL JS) or mobile (Mapbox mobile SDKs). Mapbox Studio does also allow for print exports of static map images.

2.4.3 Mapbox Studio Dataset Editor One of the Mapbox functions that is beneficial for inexperienced amateur users is the ability to perform basic data management and editing functions within the web interface through the Mapbox Studio Dataset editor. While simple and limited to tasks like adding geometries and attribute tables, the Dataset editor performs an important service of allowing people to use geodata without needing to use GIS software at all. This is an often-overlooked aspect of tools that are supposed to be accessible for a wider public  – that geographic data use is connected to the GIS culture with all its embedded schemes, jargon, and persisting metaphors. This is an obstacle which can be avoided by using devices like Mapbox Dataset editor that allow its users to stay within a single environment. Apart from the Dataset editor, uploading or using data from external sources may require some data processing skills or understanding of basic principles of web mapping such as tile layers and tilesets. This is however well explained in online documentation that is well written and is one more reason why Mapbox can be recommended for users with various levels of technical expertise, providing they understand the skill-level required to produce the product required.

2.4.4 Mapbox ‘Impact Tools’ Templates Mapbox provides many tutorials and templates within its website and documentation. One set of templates for web applications is named ‘Impact Tools,’ created by the Mapbox Community Team to address common needs of nonprofit organizations (Fig. 2.7). These include the ‘Sheet Mapper’ template (which allows users to create data in a Google spreadsheet and have that connect ‘live’ to a web map) and the ‘Finder’ template (which is like Sheet Mapper but does not require use of a

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Fig. 2.7  Mapbox provides a variety of “Impact tools” set of templates for web applications is named ‘Impact Tools,’ created by the Mapbox Community Team to address common needs of nonprofit organization

spreadsheet and includes filters and a responsive-design interface for mobile devices). Mapbox also offers a popular free template for building interactive storytelling maps (like Esri’s ArcGIS StoryMaps) that is fully customizable and easy to host on your own webpage or server. These templates and tutorials do require some editing of code (primarily JavaScript), but they are presented as beginner-friendly, ‘low-­code’ options to get started with building a Mapbox web map.

2.4.5 Custom Applications for Web or Mobile For all other custom-built applications there is a need to have additional knowledge – either with web programming (at least basic JavaScript, HTML and CSS) or with mobile app development. Here comes into play the second part of the Mapbox ecosystem – various libraries, APIs, SDKs, and services for developers.

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Mapbox GL is the main library used to produce web maps with Mapbox. It is based on JavaScript. Therefore, to add interactions, dynamic data sources and data gathering capabilities one must be prepared to have a solid background in web development. But it must be said while Mapbox GL documentation and examples are extensive and provide ready-to-use scenarios and snippets of code that can be used without extensive coding experience. Some users may be more familiar with the open-source web map library Leaflet, which is also JavaScript based (https://leafletjs.com). Leaflet shares many similarities to Mapbox GL (which was heavily influenced by Leaflet). If building an application with Leaflet, Mapbox map styles can still be used as static tiles (the default) or vector tiles (via a Leaflet-GL binding https://github.com/mapbox/ mapbox-­gl-­leaflet). For mobile applications, Mapbox produces several Software Development Kits (SDKs): The Maps SDK for Android and iOS handles the visual map element and map interactions, and the Navigation SDK for Android and iOS handles directions and turn-by-turn navigation features. Other users may be familiar with frameworks such as React, Flutter, Angular, or Kotlin, all of which can be used with Mapbox tools.

2.5 Inclusiveness Mapbox is a global location platform and is continually expanding coverage and access to their products. Mapbox services currently support 13 global languages and 35 scripts, including right-to-left scripts. Spoken instructions for turn-by-turn navigation directions are supported for 28 languages. Developers can use several options to support language localization based on user device settings. Mapbox also supports customers who are building applications for users in low-­ bandwidth environments where data is precious. Mapbox strives to make services as efficient as possible and support multiple options to build for offline use. The Community team at Mapbox exists to support non-profit organizations, academic users, community organizations, and others building with Mapbox tools for positive social or environmental impact. The Community team has built many long-­ standing relationships with organizations active in participatory mapping and indigenous mapping. The Community team provides tailored support, discounted and donated products, pro bono volunteer time, and access to specialized tools or account permissions (such as approval to side-load map tiles between devices in limited, non-commercial cases when mapping offline in remote or rural environments).

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2.6 Data Accuracy One of the primary sources of data for Mapbox maps and navigation tools has been OpenStreetMap, which is a collaboratively built and maintained open mapping data project that anyone in the world can contribute to. This is especially useful for participatory mapping projects that might need to edit or add to the available basemap data within Mapbox for their location, as most edits in OpenStreetMap populate through to Mapbox maps. In addition, every user of every Mapbox map or service can report accuracy issues directly via the ‘Improve the map’ link on maps or at https://www.mapbox.com/contribute/. Mapbox curates its use of OpenStreetMap data to ensure data quality and combines OpenStreetMap data with other data sources to enhance accuracy and coverage. Mapbox is continuously improving and expanding data coverage and accuracy, both for commercial customers and through impact partnerships with partners like the Humanitarian OpenStreetMap Team. One of the latest developments by Mapbox has been the creation of a 3D Terrain layer which coupled with high resolution satellite imagery can be highly effective for visualizing local geographies, depending on location and accessibility of imagery.

2.7 Data Privacy Privacy and security are especially important considerations in all online solutions such as Mapbox. Security issues are dependent on the particulars of a given application as web maps can be implemented with or without the need for user registration and with a wide range of access. To accommodate many use scenarios Mapbox provides an extensive system of ‘access tokens,’ which can be set to public, secret, and temporary scopes. Tokens are in JSON Web Tokens (JWT) format and each one is a unique string encoded with unique identifier, capabilities, authorized URLs and timestamps. By using those developers can vary access to map resources for different types of users. However, it is entirely up to the developer themselves to maintain the proper security measures like token rotation and monitoring. Public tokens that are used for displaying map applications can be seen by anyone that knows where to look and it is therefore necessary to monitor account activity and usage. To improve token security, Mapbox has the option to restrict token access to particular URLs. Tilesets and map styles within a Mapbox account can be set to ‘private’ or ‘public,’ and are private by default. Setting either to ‘public’ means that another Mapbox user could use the style or tileset with their own access token, provided they know the map style URL or the tileset ID. If a map style or tileset are set to ‘private’, they can only be used in conjunction with an access token from the account within which they are stored.

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Another consideration is the privacy of the data itself. This is a more delicate subject for PPGIS (Kyem, 2021; Brown & Raymond, 2014). The use of vector tilesets and open web standards like GeoJSON means that in most cases any user of the map can gain access to the data using developer tools provided by a browser. This is a great advantage when it comes to web application design, but it also means that additional care needs to be taken when selecting what kind of data and on what level of granularity are needed. To be clear, this is not a problem directly connected to the Mapbox platform but rather a wider issue resulting from the way web mapping operates in modern browsers. One way around it would be to provide raster-based map tiles for the end user, but it will result in losing many benefits of vector-based rendering.

2.8 Analytical Capacity Possibility of analytical inquiry using Mapbox varies depending on the type of analysis desired. A frequent use of the Mapbox platform is to perform visual analysis and create map-based data visualizations. Through Mapbox Studio users can easily create choropleth maps, proportional and graduated symbol maps, dot density maps, and heatmaps. While basic, they form the staple of map-based data exploration and can help stakeholders with understanding spatial relationships that are present within the gathered data without requiring additional knowledge. A welcome addition to this is the possibility of 3D extrusion which can boost the engagement through providing additional visual stimuli. It is also possible to include simple 3D models. In addition to this, Mapbox GL JS provides some additional options such as timeline analysis or preparing swipe maps that can help with comparison of different visualizations. It is still possible to add additional analysis capabilities in applications deployed using Mapbox GL JS using other libraries like d3 or the spatial analysis library Turf JS (http://turfjs.org/). By using this library, a web map can incorporate basic client-side geoanalytical tools like buffer analysis, tessellation, or interpolation. Other Mapbox APIs, such as the Mapbox Isochrone API or Tilequery API, can be useful for analysis. Mapbox data products such Mapbox Movement or Mapbox Traffic data are designed for researchers and can be a useful resource for certain analysis projects.

2.9 Visualization Capacity Data visualization is one of the strongest features of building maps with the Mapbox platform, from a PPGIS perspective. Having readable and aesthetically pleasing maps is important since it can lead to a greater engagement of participants (Craig

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et al., 2002) and in effect a more successful participatory mapping. Mapbox offers its users several tools that help with map design and data visualizations for both amateurs and experienced cartographers. Firstly, Mapbox map ‘styles’ can be created either from scratch or starting from a set of the default styles. Template styles provide predefined colors, fonts and icons and all elements can be customized for a very distinctive visual effect. It is also easy to make additional data layers consistent with the background. Custom Mapbox styles also help to set a map apart, avoiding the look and feel of standard topographical or web maps that all look the same. At the core of Mapbox’s flexibility for visual design is the vector tile technology that underpins Mapbox maps. Mapbox uses global data tilesets, such as the Streets v8 tileset, that exist independently of any styling instruction. Styling instructions take the form of a JSON document that when combined with the underlying tilesets results in the web browser (or mobile app) rendering a styled map. Designers or data visualization professionals using Mapbox have a wide range of tools to choose from. Data can be represented with various types of layers, from standard one like lines and polygons (Fill) to 3D extrusions and heatmaps, with each type having its own unique properties. One of the features of the Mapbox Studio environment is that it is relatively straightforward to use various visualization techniques together and the process of using the same color scales and rules for similar properties like color and opacity is streamlined as they can be copied either using GUI or as a JSON code. For a web map to be usable at all scales and all region styles need to be dynamic, Mapbox allows each layer property to look differently at different zoom ranges (Style across zoom range). For example, this allows a certain layer to change color, symbol size or become transparent when it is not needed, or it is cluttering the map. Four types of thematic maps are supported by the ‘Data Visualization Component’ in Mapbox Studio: choropleths, data-driven symbols, 3D extrusions, and heatmaps. Choropleth  This is a staple of map-based data visualization. While it can be said that this method is often overused, it is nevertheless very useful for visualization of simple spatial phenomena. Mapbox GUI has a special component which is intended to create choropleth based on selected data attributes. Creating a choropleth layer requires users to source and prepare polygon data for the areas they wish to color based on data fields and attach the relevant data fields to the spatial polygons prior to uploading the data into Mapbox Studio. Data-Driven Symbols or Lines  Within Mapbox Studio components there are three default options that allow users to connect data values to the style of a given layer: data-driven circles, data-driven lines, and symbols. By choosing one of those components the value of a data attribute can influence size and color of the circle or line in case of quantitative data or style and size of the icon in case of quantitative data. Data driven styling can be also applied using layers and, in this case, almost every attribute can be dependent on the data. Creating a data-driven visualization layer requires users to source and prepare point or line data and attach the relevant data fields to the spatial data prior to uploading the data into Mapbox Studio.

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3D Extrusions  On many basemaps that are provided by Mapbox it is possible to make pseudo-3D visualization (extruded 2D polygons) of buildings on higher zoom levels which add another visual cue for the map reader. But it is also possible to extrude any kind of 2D polygonal dataset to produce compelling and informative maps. Those extrusions can be used together with color ramps and work best when associated with the initial pitch of the map that is slightly tilted. 3D extrusions, while very engaging, can be misleading and care needs to be taken not to over-use them. As with choropleth layers, creating 3D extrusion layers requires users to source and prepare polygon data with the relevant data fields they want to base their visualization on. Heatmap  This is a useful addition to the more standard visualization techniques. Heatmaps show relative density of the points and they are dynamically updated when extent and zoom of the map changes. They can be used for visualization of the data density and to reduce cluttering. The algorithm underlying the generation of density maps is extremely fast and can process large amounts of data points. One unique feature of this layer type is that, while point data is mainly used to create heatmaps, it is also possible to make heatmaps of any vector nodes (for example line vertices). While heatmaps that are statically generated (i.e. for whole dataset at once) are not well suited for variable zoom range of a web map, the dynamic Mapbox heatmap layer provides a set of tools that can make the style appropriate for a given scale (Fig. 2.8).

Fig. 2.8  Example of using heatmap layer as a background to illustrate point density without intruding into the main map content

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However, while the options can be useful there are some limitations. When it comes to styling that is based on attributes the main difficulty is that color ramps need to be constructed by hand and to do this properly one needs to have some level of knowledge of cartographic and data visualization principles. Also, when styling using data range (for example to create a choropleth) stops are also manually added. There is a visual help in the form of graphic scale but still the distribution of values must be done outside Mapbox if something more complicated than an equal values scheme is needed (which is often). It is advisable to use tools like Color Brewer 2 (https://colorbrewer.org) to construct readable and accessible colors schemes. Beside visualization of the data, recent additions to the Mapbox 3D capabilities bring such features like gradient sky layers, 3D terrain and fog. Those can be used as a means of both artistic expression and to put more context to the data being presented. Additional visualization possibilities also come with the Mapbox GL JavaScript library. By using custom code, maps created in Mapbox Studio can be displayed and their functions expanded. Firstly, various kinds of user interactions can be added: pop ups, sliders, dynamic layer switchers, user location etc. Even more importantly various kinds of map and camera movements can be introduced to create end products that go beyond the simple web map. One of the examples are so called ‘storymaps’ or ‘storytelling maps’ (Thöny et  al., 2018) that provide map designers with a tool to create data driven narration connected to a particular place. Mapbox GitHub repository includes templates for such endeavors (https://github. com/mapbox/storytelling).

2.10 Openness Mapbox has a positive reputation in geospatial and developer communities based on years of contributions to the open data community OpenStreetMap and other open-­ source mapping tools and web development libraries. While the latest versions of most core Mapbox libraries are now closed source, there are hundreds of smaller repositories and tools that are still open source. Until recently Mapbox has followed the ‘open core’ business model, wherein the main foundational components of a system are provided through open-source licenses and then fees applied when users wanted to use the end products accessed through an account and access token, such as map hosting services, API services, and proprietary data sources. In December 2020, a new version of Mapbox GL JS came with a non-open-source license which now also requires an access token even when only local data or third party is used. However, the previous versions of Mapbox GL JS remain open. This change in license led other open-source developers to create a fork of Mapbox GL JS named MapLibre (https://github.com/maplibre/maplibre-­gl-­js), which provides an alternative to the new version of Mapbox GL JS but lacks most of the newer features that makes the Mapbox ecosystem such a popular choice among web developers.

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The Mapbox platform is still a significant contributor to open-source software with many libraries, projects, code snippets and libraries accessible through the Github platform (https://github.com/mapbox). As of May 2022, there were 852 repositories listed on the Mapbox profile. Mapbox has also authored several open standards and formats focused on web mapping like MBTiles Specification and Mapbox GL Style Specification. Due to the use of open standards across the platform, together with other open formats such as GeoJSON, export and import of data in Mapbox is unhindered.

2.11 Accessibility From the pure accessibility point of view Mapbox provided many solutions that help with this aspect of map design, both from the developer and end-user perspective. The former perspective has been described in more detail in section Technical Level (p. 24) but it is worth noting that the range of tools that Mapbox exposes to the map developer allows for tailoring the final product to a wide range of possible needs (Bartling et al., 2021). This feature is used for example in various studies of web map usability (for example Wells et al., 2021). The usability from the end-user perspective is equally satisfying and the map experience is more dependent on the choices made by map designers rather than characteristic of the software itself. Mapbox Studio includes colorblind-friendly palettes for data visualizations and all map style colors, fonts, and labels are entirely customizable. The Mapbox GL JS web map and iOS mobile libraries also support voice-overs for screen readers used by people with limited vision. Mapbox services are primarily designed for use in online environments. While older versions of Mapbox tools do allow self-hosting of JavaScript libraries, styles, and map tiles and therefore to create offline applications, newer versions require access tokens to access Mapbox services. The dependency on access to the internet limits the ability to deploy systems built with the newer versions of Mapbox GL JS in situations where connectivity can pose a problem. Mapbox maps and services are optimized for mobile devices and can be used natively through applications created with Android and iOS SDKs (Software Development Kits). The extensive use of vector tiles also requires less bandwidth than raster tiles and this means that maps created with Mapbox are less demanding when it comes to internet access quality. Mapbox mobile SDKs do support offline use when connectivity is intermittent but are intended to have occasional access to the internet to cache map tiles and data for offline use. In PM in particular much attention should be given to avoid any ­possibility of digital exclusion and therefore care should be given when deploying tools that require internet connectivity. Where internet access is not a limiting factor, Mapbox can provide a solution that can be accessed with ease on a range of devices.

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2.12 Brief Use Cases The flexibility of Mapbox allows it to be used in various scenarios. An example of this can be a case of public consultations in the Jeżyce neighborhood in Poznań, Poland. Data about transportation issues was gathered through community engagement, and it was necessary to give some feedback to the people that participated and, at the same time, to allow experts to browse the data in-depth. Mapbox Studio allowed the lead author of this chapter (Michał Rzeszewski) to prepare in a short time simple point-based maps that displayed raw data and used the same data sets to create compelling multi-layered visualizations for the public. The latter was created using Mapbox Javascript libraries and added functions such as 3D buildings and layer switching. Response for Jeżyce dwellers was very positive, showing how important it is to provide good post-participatory feedback for participants (Fig. 2.9). Another example is the case of The Southern Poverty Law Center (SPLC) in the United States which wanted to rebuild their web map showing the locations of existing and renamed or removed public symbols of the Confederacy (statues, named buildings, street names etc.). The SPLC had built an extensive database of these symbols and their locations (including latitude and longitude coordinates). The first version of their web map used Google My Maps, but for the second version the SPLC wanted more control over the web map interface and map design. With help from the Mapbox Community team and pro bono volunteers from Mapbox, the SPLC used the ‘Finder’ impact tool template from Mapbox to build a new version of the application. The data from the SPLC’s database is pulled in live to the web map, and the template provided interactive pop-ups for each point as well as a

Fig. 2.9  Screenshot from a Mapbox map visualizing a participatory planning exercise for a local community at Jeżyce neighborhood – Poznań, Poland

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sidebar to display listings and filters that users could apply to narrow down what locations are shown on the map. The SPLC can also use a custom map style as the background of their new map (Fig. 2.10). A third example is the Eviction Lab website built by the firm Hyperobjekt (James Minton, Pat Sier, Noele Lusano, and Lane Olson) for Professor Matthew Desmond’s research team at Princeton University. The research built a nationwide database on evictions, and they created an interactive site for people to explore and use the tens of millions of eviction records they had collected (Fig. 2.11). The site features a custom map application built with Mapbox GL JS and several types of data visualization layers, including choropleths and data-driven circles.

2.13 Comments and Recommendations of the Authors Every technical solution that can be used in participatory mapping has its own ‘sweet spot’ where the needs and constraints of the mapping project align with the capabilities of the mapping tool. In the case of Mapbox, there are several potential ‘sweet spots’ depending on the technical expertise available and the target end product. On the one hand Mapbox tools can be used as a basic standalone mapping solution that requires little to no GIS knowledge. In this capacity Mapbox excels by providing an easy-to-use interface that can be used to design and publish engaging maps and data visualizations. When it comes to gathering data, which is equally important in many partici­ patory mappings, Mapbox does not give its users a ready to use solution.

Fig. 2.10  Screenshot from the SPLC ‘Whose Heritage’ map, which uses a customized map style, custom data layers, pop-ups, and several data filtering options

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Fig. 2.11  A screenshot from the Eviction Lab web map application, an interactive site for people to explore and use the tens of millions of evictions records they had collected

The extensive API and Javascript library capabilities give the possibility of creating custom applications that can gather and store data, even within the Mapbox own hosting services, but it requires investment in developer resources. Map styles can be used through various endpoints, even in the rasterized form of warehouse management system (WMS), which is the most common standard of distributing map content on the web and users have the option to build with Mapbox from scratch, use templates, or use Mapbox within other tools. All those characteristics make Mapbox commendable for beginners in the world of participatory web mapping. For many of the custom web map applications of Mapbox tools, it is also viable to use tools such as Leaflet (https://leafletjs.com/), or OpenDataKit (https://www. opendatakit.org/), or Esri’s Survey123 (https://survey123.arcgis.com/) (see Chapter 8, pg. 167) as part of a project, for example a data collection tool, and then use Mapbox to produce the final presentation of results in polished and engaging interactive map or data visualization. This kind of multi software mashups are common in internet based mapping solutions and are made relatively easy in case of the Mapbox due to its inherent flexibility. Mapbox is a good solution to consider when looking for custom mapping tools, especially when:

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A highly customized application (for web or mobile) is needed; Data is already available or collected; Engaging visualization is important; Dynamic interaction with content is required; Performance (e.g., map loading time) is important; There are large datasets that need to be displayed; Data will be created by the single stakeholder; There is limited GIS knowledge; and/or A team has developer resources.

In addition to above points, the Mapbox Community team (mapbox.com/community) can provide guidance and mentorship to PPGIS projects that are investigating whether Mapbox tools are a good fit for their needs, even in the earliest phases of a project. Acknowledgements  This text would not be possible without the kind help of Marena Brinkhurst, who contributed extensively with her knowledge of the Mapbox platform and community tools.

References Bartling, M., Havas, C. R., Wegenkittl, S., Reichenbacher, T., & Resch, B. (2021). Modeling patterns in map use contexts and mobile map design usability. ISPRS International Journal of Geo-Information, 10(8), 527. https://doi.org/10.3390/ijgi10080527 Brown, G., & Raymond, C. M. (2014). Methods for identifying land use conflict potential using participatory mapping. Landscape and Urban Planning, 122, 196–208. Craig, W. J., Harris, T. M., & Weiner, D. (2002). Community participation and geographical information systems. CRC Press. Kyem, P. A. K. (2021). Managing natural resource conflicts with participatory mapping and PGIS applications. Springer. https://doi.org/10.1007/978-­3-­030-­74166-­2 Rambaldi, G., Chambers, R., McCall, M., & Fox, J. (2006). Practical ethics for PGIS practitioners, facilitators, technology intermediaries and researchers. Participatory Learning and Action, 54(1), 106–113. Thöny, M., Schnürer, R., Sieber, R., Hurni, L., & Pajarola, R. (2018). Storytelling in interactive 3D geographic visualization systems. ISPRS International Journal of Geo-Information, 7(3), 123. https://doi.org/10.3390/ijgi7030123 Wells, J., Grant, R., Chang, J., & Kayyali, R. (2021). Evaluating the usability and acceptability of a geographical information system (GIS) prototype to visualise socio-economic and public health data. BMC Public Health, 21(1), 2151. https://doi.org/10.1186/s12889-­021-­12072-­1

Chapter 3

Mapeo

Aliya Ryan, José María León Villalobos, and Mir Rodríguez Lombardo

Abstract  Mapeo was built with and for earth defenders to document environmental and human rights information and to collect data about their land. It aims to be simple to use and accessible, and the software is free, open source, and can be customized with local languages and settings. The Mapeo Mobile app is used to gather observations in the field, to take photographs and collect data attached to GPS points of significant places. The Mapeo Desktop app is used to organize data collected on mobile or GPS, to create new GIS data, and to visualize, edit data, create printed reports, and publish a map online. The Mapeo toolkit was developed within a strong values framework, to center the needs and priorities of local land defenders. The authors found Mapeo’s strengths to be prioritization of features promoting data privacy and data sovereignty such as being offline first and not dependent on a server; the inclusive design resulting from its co-creation with Indigenous partners leading to ease of use and low-tech threshold; many features increasing accessibility and inclusivity with customizations, including the possibility of translation into any language, custom icons and offline maps. Keywords  Indigenous knowledge · Open source · Offline · Environmental data management · GIS · Mapping

A. Ryan (*) Digital Democracy, Edinburgh, UK e-mail: [email protected] J. M. León Villalobos Centro de Investigación en Ciencias de Información Geoespacial A.C. (Centro Geo), Mexico City, Mexico e-mail: [email protected] M. Rodríguez Lombardo Fundación Almanaque Azul, Panama City, Panama e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 C. M. Burnett (ed.), Evaluating Participatory Mapping Software, https://doi.org/10.1007/978-3-031-19594-5_3

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3.1 General Information Name of Application: Mapeo Name of Developer: Digital Democracy (Dd) Name of Funder: The Dutch Postcode Lottery; The Knight News Challenge; The Abundance Foundation; Hivos; The Leonardo DiCaprio Foundation; One Earth; Earth Alliance; Open Society Foundation; Patrick J McGovern Foundation; Samsung; Open Technology Fund; Good Energies Foundation Type of System Software: • Mapeo Desktop (MD): Linux; Windows; Mac • Mapeo Mobile (MM): Android; iOS to be released 2022 Type of Programming Language: JavaScript API Availability: Desktop and Mobile Features: Mapeo features include: • Mapeo Desktop: Offline first; Peer-to-peer synchronization and data storage; Synchronize and manage data gathered in Mapeo Mobile; Create reports; Create webmaps; Create GIS data (points, lines, and polygons); Export data as GeoJSON, CSV, for webmap; Use customized offline basemaps; Use customized configurations. • Mapeo Mobile: Offline first; Peer-to-peer data synchronization and storage; Synchronize data gathered by other team members; Collect data according to custom categories and questions, with associated photographs, GPS points and time stamps; Use customized offline basemaps; Share evidence alerts via Whatsapp, Telegram, Email etc. Cost: Software is free, all data hosting is local so no server or management charges. Users may have costs associated with hardware or equipment for backups etc. Type of Data Collected: • Mapeo Desktop: Create points, lines, and polygons and export as GeoJSON or CSV; import GeoJSON, .shp, .gpx, and add descriptive text information; can store text and photographic media collected by Mapeo Mobile. • Mapeo Mobile: Coordinates, time and date, photographs, observation category, text information the user associates with the observation. • Coming in 2022: Mapeo Mobile will collect tracks; Mapeo Mobile will collect, store, and synchronize (including with Mapeo Desktop), video and audio media files. Overview: Mapeo was built with and for earth defenders to document environmental and human rights information and to collect data about their land. It aims to be simple to use and accessible. The software is free, open source, and can be customized with local languages and settings. The Mapeo Mobile app has been developed to gather observations in the field, to take photographs and collect data attached to GPS points of significant places. The Mapeo Desktop app has been

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developed to organize data collected on mobile or GPS, to create new GIS data, and to visualize, edit data, create printed reports, and publish a map online. The Mapeo toolkit was developed within a strong values framework, to center the needs and priorities of local land defenders. The authors found Mapeo’s strengths to be prioritization of features promoting data privacy and data sovereignty such as being offline first and not dependent on a server; the inclusive design resulting from its co-creation with Indigenous partners leading to ease of use and low-tech threshold; many features increase accessibility and inclusivity with customizations, including the possibility of translation into any language, custom icons, and offline maps.

3.2 Ethics Evaluating the ethics of the tools that are to be used in Participatory Mapping (PM) projects is an essential exercise. These may impact upon the choice of one tool over another on theoretical or intellectual grounds. For example, if convening groups do not wish to partake in perpetuating social or environmental injustices by implicit participation then they should refrain from using tools which result from inequitable or unethical development frameworks or corporations which do not share their values. However, a tool could have positive ethical impacts on the project depending on the degree to which the tool can embody, encourage and support ethical workflows. Digital Democracy (Dd) has publicized the Mapeo toolkit as a value driven tool built to respond to many of the ethical concerns inherent in other software applications, such as data extractivism, dependence, accessibility issues and data sovereignty (EDT, 2021). The term of solidarity technology is used to characterize both the development process itself, and the tool as an active object in the world (McKelvey, 2020). Technologists wishing to develop within a similar value system can follow Dd’s recommendations on Table 3.1. They also provide a good starting point for evaluating Mapeo’s ethical credentials. Since Dd focuses on ethical issues as a major driver of their development process we will first evaluate the tool using their own standards, and then reflect on how Mapeo stands in relation to some more general ethical issues regarding the field of participatory mapping.

3.2.1 Center Self Determination and Human Rights: Increase Self-Sufficiency and Reduce Dependence Participatory methods continue to be led and facilitated by people outside the community, even though the methodology is clearly more effective when ownership is taken from within (Chambers, 2006). There are also large and growing ethical

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Table 3.1  Mapeo’s ethical considerations Solidarity Technology 1. Center Self-Determination and Human Rights  • Respect. All peoples have the right to determine their future for themselves. Prioritize solutions that increase self-sufficiency and reduce dependence on outside entities.    In practice: apps should work without access to a server. If a server is required, users should be able to run their own.  • Autonomy. Read the principles of Free Prior and Informed Consent and recognize your user’s intellectual property rights. Users should be able to take their data with them.    In practice: export data into many openly accessible and flexible data formats. 2. Collaborate Through Equity and Intentional inclusion  • Lead from the Heart. Build an ecosystem of organizations and individuals and prioritize projects that enable collaboration.    In practice: Have open dialogue and refrain from a competitive mindset.  • Co-design. Design first, implement later. Instead of driving product decisions from metrics dashboards, form direct partnerships and work side-by-side in collaborative design processes.    In practice: Hire designers/UX researchers early and prioritize in-person workshops. 3. Challenge Oppression (Social & Environmental Justice)  • Consent & Safety. Data can be used as a weapon against marginalized communities.    In practice: Always ask, Do we need to store that data? What is the threat model? How long do we keep data? Have strict data retention policies and revisit them often.  • Accessibility. Create tools that are adaptable and usable across typical boundaries such as class, race, language, literacy and culture.    In practice: co-design to ensure different user needs are prioritized from the beginning. 4. Be Fearless & Creative  • Open Source. The project is open to new contributors to help steer the project.    In practice: Open source from the first day and prioritize writing documentation.  • Take a stance: Reflect on your team’s & communities’ values and decide “best practice” for yourselves. Don’t reproduce Silicon Valley practices blindly.    In practice: make it clear that user satisfaction, not profit margin, is your team’s priority. Text summarized from McKelvey (2020)

concerns about data extractivism. In some instances, communities have lost access to their own knowledge and products they created, when data is removed for analysis or project output creation (Kukutai et al., 2020). Questioning the “who and for whom” (are making decisions, managing data, and benefiting from it) provides one framework for evaluating this aspect (Rambaldi et al., 2006). The introduction of complex technology can introduce new challenges into this field: as technology complexity increases, community access to the technology decreases (Fox et al., 2005). For example, if communities are not tech literate, or technologies are expensive or complex, it reduces access for certain groups. In such cases, even if projects are initiated by members of the community, they may end up dependent upon external organizations or consultants to support the technical aspects and a result, communities continue to be disempowered from data ownership and control. Mapeo was created to directly counter this trend. Developers were given the challenge to build a tool for mapping and data collection which was simple enough

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for people with limited technical skills and experience to learn to use, to store and process the data themselves, and make their own decisions about when and how to share information (Ryan, 2018). In this regard, Mapeo grants equal access and control over data to all users.

3.2.2 Local First Software, No Need for Server Dependence Server usage can increase technical dependence. Mapeo is built using peer-to-peer technology which does not use a server to store data and functions, it is completely offline. The entire data set is stored on each device (mobile or desktop) and they are synchronized to share data. Data passes between the devices using a Wi-Fi (but not an internet dependent) network. This data storage system prioritizes collaboration and teamwork by rejecting the typical hierarchical model inherent in server systems, which may result in collectors losing access to data once it has been uploaded. Since there is no server system to build or maintain there are no associated technical needs or financial costs (McKelvey, 2019). However, there are still some dependencies within Mapeo. It does require some tech literacy, particularly when using Mapeo Desktop (MD), and although icon heavy (with icons being customizable for each project) some verbal literacy is also necessary. Non-verbally literate participants however have successfully followed along when Mapeo is used by others. As Jorge Gaba stated, “Memo, an elder from Akaro came over and wanted to learn. It was the first time he had used a computer and a mouse, and it took a little time for him to figure it out, so it was quite slow at the beginning, but then he practiced and got the hang of it” (Ryan, 2018). The level of inclusiveness, as in so much of PM, will depend on how the tool is used almost as much as the tool itself.

3.2.3 Users Should Be Able to Take Their Data with Them: Export Data into Many Openly Accessible and Flexible Data Formats Mapeo Mobile: individual observations with associated photos and information can be exported from MM to Telegram, WhatsApp, email or other apps; however whole datasets from MM can currently only be extracted by synchronizing the phone with MD. If users are relying solely on MM, then this limitation does currently present a challenge for using data in other programs. Mapeo Desktop: data from MD can be exported as GeoJSON, CSV and for a webmap. Options for exporting as .shp and other formats are in development.

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3.2.4 Collaborate Through Equity: Design First, Implement Later… Form Direct Partnerships and Work Side-by-­Side in Collaborative Design Processes The significance of there being almost no information technology built by, or from the perspective of, marginalized communities should not be underestimated. It has resulted in technologies that, by their very architecture and design choices, continue to perpetuate systemic inequalities and systems of oppression (Stone & Calderon, 2019). As Pyrou Chung (cited in Jacobi, 2020) mentions: “to fundamentally flip this approach would mean having communities design and develop their own applications without intermediaries and contractors”. Whilst Mapeo was not developed by Indigenous communities alone, the participation of Indigenous co-creators has been, and continues to be, an inherent and critical part of the process. Design workshops are carried out in the field with communities, and evaluations and feedback from users drive the roadmap (Wilson, 2021). Codesign is important not just to right structural inequalities within the tech development world, but to ensure that the applications really meet the needs of those they are designed for and promote inclusivity. Oswando Nenquimo, director of the Waorani Mapping Project, was one of the first contributors to Mapeo’s co-creation, and he reflects on the value of this process in giving his people a new voice and role. “In 2015 when we started to map with our elders, we were creating a new system and combining two worlds – that of our oral tradition with the technical world that Dd introduced us to. Together we built the open-source application Mapeo for everyone to use. We were using it then, and we are still using it to defend our lands. We hope that through Mapeo we can share something from the jungle with others, and that others, including other Indigenous people around the world can also benefit from what we helped create” (Oswando Nenquimo, cited in Jacobi, 2021).

3.2.5 Challenge Oppression: Data Sovereignty and Power Dynamics With Mapeo communities can have total control over data and decisions about if and how to share it, as it is easy for community members to learn to use, and all data is stored locally without the need for online or server storage. However, the technology itself has no way of ensuring that the communities are fully and adequately informed about the risks and dangers that could come if they take the decision to share it externally. The challenges surrounding Free Prior and Informed Consent (FPIC) goes to the center of this. Mapeo gives autonomy to communities over these decisions, and Dd provides them with guidelines to support good practices implementation and be aware of risks; however, responsibility for full FPIC falls on the user or local facilitator. Despite this weakness, any data made public from Mapeo is

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the result of the user’s own process of decision making, rather than an automatic result of the software they are using. The power dynamics which a methodology embodies, promotes, encourages, or even allows, is one of the biggest ethical challenges facing PM (Abbot et al., 1998). Any project involving technology, particularly in remote, marginalized spaces with general low-tech literacy, will likely create or entrench some systems of power. Dd has done much to counter by creating an accessible and inclusive tool and enabling Mapeo projects to be owned by the community. For example, older people or women who could tend to be excluded from tech-centric projects are still centered in the design process, and user-guides encourage intergenerational learning with knowledgeable elders accompanying younger Mapeo users on mapping trips. Building Mapeo as an offline first tool was also an ethical decision for Dd. Open access and online data is often considered a means by which the public can hold traditional holders of power to account, and in many cases it is. However for marginalized and other historically colonized peoples, there may be instances where the reverse is true, as discussed in Sect. 3.10 on Openness (p. 61).

3.3 Cost No direct costs: Mapeo is free to download and use. It comes with all which a user needs to get started including a default configuration and basic offline map. However, depending on a user’s resources and use-case there may be some indirect costs incurred.

3.3.1 Equipment Smartphones: mobile phones are becoming more and more ubiquitous; however, there are still areas of the world without mobile phone coverage, and where phones are not widely available or accessible to remote or marginalized communities. MM requires an android phone (iOS version planned for late 2022), and if users want to collect data in harsh environments they may want to invest in a phone with waterproofing and a robust casing. GPS  Some devices also have better internal GPSs than others, which may be particularly significant in areas without internet coverage. In such cases, users may wish to buy portable GPS units to gain greater positional accuracy when collecting observations points. Desktop  A basic computer is required for MD (it functions on Linux, Windows, and Mac). An external mouse may be easier to use for people less experienced with computers.

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Wi-Fi Router  If needing to synchronize data between MM or MD in an area without a Wi-Fi network, a portable Wi-Fi router is needed to create a non-internet-­ based Wi-Fi zone. This is a cheap device in the USA ($20USD) but could cost more or be hard to source in some locations. USB Storage  USB or other backup disks or devices are recommended to store copies of your Mapeo database. Other Materials  Other materials might be needed for a PM project that are not Mapeo specific, but could include weather proofing, equipment, and suitable clothing for going on treks, first aid kits etc.

3.3.2 Technical Support Mapeo should be usable without significant tech support, except for very low-tech users who might need an introduction to smartphone usage or support using applications and saving files on a computer. Technical support is more likely if users want to create their own configuration enabling a project to have custom categories, icons and data fields for collecting observations, and also to create customized background maps for both MM and MD. Dd aims to lower the tech threshold of both these processes, and some improvements will come in 2022. Mapeo contains very basic offline maps for use without the internet. However, in cases where satellite or other imagery is required, and no custom offline maps are created, access to the internet with sufficient bandwidth will be necessary to stream from online sources. This can be challenging and expensive to access in remote areas.

3.4 Technical Level PGIS seeks inclusion and active involvement of local people in the process of map-­ making. Paradoxically, the technical level and initial knowledge required to manage GIS tools is usually high and can deter people from participation, leading to digital exclusion (Rzeszewski & Kotus, 2019; Weyer et al., 2019). However, the level of technical knowledge required to use Mapeo is low, and MM in particular aims to be very easy to learn to use, even for people with no prior smartphone experience.

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3.4.1 Mapeo Mobile Collecting observations using MM requires minimal training and GIS knowledge. In the Case Study 1 in South Mexico, participants found the interface to be user-­ friendly and intuitive: I downloaded and installed MM on my mobile in order to collect points and pictures of different farming systems, and it seemed to me very practical, easy, and very simple to use. Today, most people have access to a mobile phone, so everybody can carry MM in their pocket to collect data. (Jesús, aged 29 years, Trágame Tierra group, Guerrero México) I had some prior experience creating points in google maps …but MM was much easier to use. (Sabina, aged 42 years, Centro de Bachillerato Tecnológico Agropecuario)

3.4.2 Mapeo Desktop The long-term storage and management of data with Mapeo generally happens within MD, which is used to edit, filter, create reports, and export data for other uses. MD has a higher learning threshold than MM. However, there are multiple examples demonstrating cases where communities or local organizations are managing collected data themselves within MD. For example, the Waorani mapping project (Ecuador, 2015–2019) had a team of four Indigenous coordinators, who, after receiving training themselves, traveled from village to village to carry out the mapping work. They facilitated workshops to prepare hand-drawn territory maps, and then trained teams in each village to collect the GPS points necessary for the creation of the map they wanted to defend their land from oil operations. The coordinators collated the data collected by the community teams and synchronized this with MD in the field, enabling them to work on the digital map with ongoing community participation, after the data collection had happened (Ryan, 2017). MD also has a simple interface and limited functionality in order to ensure accessibility to as many users as possible. However, its use may require prior technical knowledge and skills that vary significantly between use-cases, depending upon which parts of the app are being utilized. For example, synchronization is a more complicated concept to understand, and likewise the Territory Screen and its functionalities. Some prior computer experience may also be useful to participants to understand how to open programs, save files, navigate screens and menus, etc. For example, one of the older participants in Case Study 1, with limited technical skills, experienced some difficulties using MD: MM was easy to use but I had troubles synchronizing MM with MD … however, I do believe with more practice, I’ll learn how to use it properly. (Aurelia, aged 58  years, Universidad Campesina del Sur)

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3.5 Inclusiveness The UX design of much GIS software, offering multiple features, analyses, and complex functionalities, presents an environment that can be intimidating to many community users without specialist GIS training. Dd has taken a different approach to the user interface, presenting minimal options to the user, and using an uncluttered screen. The ‘Territory’ screen of MD is based on OpenStreetMap’s iD Editor (see Fig. 3.1), which was conceived as a “simple, friendly editor … designed entirely for the first timer” (OSM, 2012). MM presents users with a single large button on its screen in radical contrast to most other mobile mapping tools with their myriad menus. Dd’s Design Lead Sabella Flag explains the interface was designed for users used to manual field work rather than rapid smartphone typing (Wilson, 2021). The design choices significantly increase the reach of the application, which has been successfully used by diverse groups of users with very limited experience with smart phones (see Fig. 3.2). Even while the MD Territory screen still offers the traditional GIS feature types of creating points, lines, and areas, Mapeo considers the challenge of overcoming colonizing ontologies, such as attempts to universalize cartographic language to ensure interoperability, which can lead to the negation of Indigenous ways of describing place (Rose-Redwood et  al., 2020; Reid & Sieber, 2020). Rather, the designers of Mapeo explore how the app can be used to create maps useful, and which make sense, for Indigenous peoples, within their own perspectives. For

Fig. 3.1  Mapeo Desktop Territory Screen showing the interface with a bing online map and default configurations built in line with Openstreetmap iD Editor tool

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instance, the concept of “observation” as essentially a time and space-bound point, is extended to include multimedia attachments and local narratives such as: “I saw/ heard this, here”, whilst maintaining latitude and longitude coordinates as optional. Mapeo comes with a preconfigured set of categories and questions for features but allows projects to develop and use custom built configuration with their own categories, fields, and icons if desired. The process to customize the system, however, is still very technical and out of reach of average users. A configuration builder, which would simplify this step appears on Dd’s Mapeo roadmap for 2022 (Digital Democracy, 2022).

Fig. 3.2  Mapeo Mobile map interface, with large + button for creating new observations

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3.6 Data Accuracy High accuracy is not considered a necessity in many participatory mapping projects since practitioners are often more concerned with the quality of the information represented on the map than exact, to the meter precision (McCall, 2006). However, given that Mapeo is also built for collecting evidence of environmental and human rights violations, data accuracy and authenticity was an important issue for its developers. GPS points collected: coordinate accuracy in MM is strongly determined by the GPS capability provided by the mobile phone model used, and the conditions it is used under. It is usually possible to achieve a good level of accuracy of 5–10 m, which would be adequate for most participatory mapping projects, and the app will warn the data collector if the accuracy falls below a particular level. In the Case Study 1 (see Sect. 3.11, p. 63), participants were mostly concerned with showing the existing land uses and available farming structures on maps, and their accuracy requirements were more than met by Mapeo’s capacity. However, participants mentioned that GPS accuracy declined significantly (15–20 m) when collecting observation points in remote areas with low internet connectivity (as the GPS can improve accuracy if able to go online). Users have also related that the accuracy can be hard to get high in areas of high forest cover, or in deep ravines, where lines of sight to satellites are blocked. In such cases, as mentioned in Sect. 3.2 on Ethics (p. 43), buying a portable GPS to collect coordinates and then enter these coordinates in Mapeo through the manual entry screen, would increase accuracy if this is deemed important. The manual coordinate entry screen appears in Mapeo if the precision is low, or the GPS/location function on the phone is not working. Data collected: aside from the GPS coordinates, the data collected by Mapeo is as accurate and precise as the user makes it. Most data fields (not date or coordinates) can be edited by the creator after collection, to allow for brief notes in the field to be turned into more useful reports. Data Created: in MD Territory View, the user can create data (points, lines, and polygons) with accuracy depending on the zoom level they draw at, and the care with which they create their geometries. Dd currently limits editing to high zoom levels to facilitate better data accuracy. Background Maps: MD has a variety of online background maps available whose accuracy and coverage may vary depending on the region under study. For instance, in southern Mexico, Bing, Esri, and Mapbox services provide 25 m satellite images, allowing communities to map all the places and resources they want. However, these are only available when online, and users without capacity to create their own offline maps, could suffer if using in areas with low internet connectivity due to the undetailed nature of the default offline map which comes with Mapeo.

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3.7 Data Privacy Data privacy and security is a key issue for PM projects as they often include the collection of sensitive community data and knowledge which communities do not necessarily want to make open and public. Where projects occur in areas of conflicts over land or resources, gathering information can also present physical security risks to those collecting or managing the data, and the data itself might also be at risk of being stolen, hacked into, or seized to jeopardize the work or gain otherwise private knowledge. Trying to secure against these risks have been key in the development process of Mapeo (Wilson, 2022). Gregor MacLennan, Technical Director of Dd, has said: When implementing any security or privacy features, we need to balance them with ease of use because we have seen through experience that if a feature makes an app harder to use then people don’t use the app or don’t use the feature, and it then becomes pointless. The other outcome is that more complex features result in people losing access to data they have collected, which could end up worse for them than someone else gaining access to it (MacLennan, pers. comm).

3.7.1 Privacy of the Database Mapeo uses a peer-to-peer database in which data is only stored on devices synchronized within a particular project, rather than online or on a server. No collected data ever leaves the user’s computer or phone or is stored elsewhere unless the user moves it there. This ensures a very high level of privacy, more so than other apps including email or google drives, where users implicitly trust the internet service provider not to take or publish their personal data. With Mapeo there is no need to trust anybody outside of the PM team. Keeping data offline is important for communities for whom online access is difficult (e.g., many of the Mapeo co-creators in the Amazon basin), and for users who either do not trust Internet Service Providers, or for whom governments control the internet to such an extent that they frequently limit/cut internet access, such as in cases Dd has worked with in Southeast Asia (McKelvey, 2019). Dd currently collects bug and crash information from Mapeo if devices go online: for example, if there is an error in the app then the device will send non-­ identifying information about the state of the app when it crashed. But no collected data ever leaves Mapeo without the user initiating this, and no identifying or geolocating information is sent as part of the bug reports. Mapeo is not therefore at risk of acting as a miniature spy by sending user information to the web since “participants are actively involved in pursuing the protection of their privacy” as recommended by Christin et al. (2011). To better support users, Dd has plans to collect more user-metrics in the future, but this will only happen as the result of a transparent opt-in choice made by users and will not contain any identifying data or user-­ collected data.

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3.7.2 Security of Data, Editing and Data Authenticity Most data collected within MM can be edited after it has been saved. However, to ensure data authenticity there is no way for a user to edit the date, time, or coordinates of saved observations. Additionally, users can currently only edit data collected on the mobile they have access to, and not data synchronized with their mobile by collected on other phones. MD can edit all the data (except the date, time, and coordinates). Due to how Mapeo stores data in a cryptographically signed immutable log (like a blockchain), once something is written into the database and saved it is permanently logged there. Even if it is later edited, the audit log could be examined by a technical expert to prove whether the data had or had not been edited since its creation. This could be useful, for example, in legal cases where a certification of authenticity might be needed for evidence. Dd is currently developing a Projects feature which will enable project teams to be made up of users with different data access according to their roles. The whole database will still be present on each device (a feature of peer-to-peer) but won’t be visualized or accessible unless users have role-determined permissions.

3.7.3 Security of Local Data Storage Currently if someone has access to a device with Mapeo then they have access to the data. If users are concerned about data security, then they should create passcodes or passwords for accessing the device. Dd is in the process of developing optional passcode access for MM, to secure data if devices are seized. This is part of work done in consultation with Simply Secure, to protect people and data (Wilson, 2022). However, one of the main challenges encountered by Dd’s programs team is that introducing more passwords and security into the app can result in problems if passwords are forgotten and users lose access to data. Alternatively, if there are password recovery options in place, then this necessitates trusting someone else with this information, which loses the first level of privacy, currently one of Mapeo’s strengths. Most mobile phone models are automatically locked down so that data cannot be accessed from outside the app it is contained within. This provides a high level of security against someone stealing data off the phone by hacking into it, however if phones are not encrypted (usually the user’s choice) then data within apps, including Mapeo, could be at risk if the hacker had access to resources and tools such as those available to governments. Computers do not generally isolate data in the same way as phones, and data within Mapeo is therefore as secure as any other data on your computer. If someone gained access to a user’s data folder, then they would be able to remove/copy the Mapeo database folder and read the data. Protecting user

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profiles on computers with passwords or other encryption is recommended for all data security.

3.7.4 Mapeo’s Project Key and Data Encryption Mapeo instances with custom configurations contain unique Project Keys: randomized 32-character codes. The Project Keys are used to encrypt data whilst it is sent over the Wi-Fi network during database synchronizations, and also to validate other users trying to connect by synchronization: so you cannot synchronize your database unless your Mapeo configuration contains the same project key. This means that someone trying to hack into your data during the synchronization process would not be able to access it. Encrypted data currently includes all information within the database except for photos: photo encryption during synchronization will be added by Dd during a sync-refactor due to be released later in 2022. Encryption of the database when stored locally on phones and desktops is also being added to Mapeo in 2022, which will mean that anyone stealing a user’s data folder will not be able to read the data.

3.7.5 Long-Term Data Storage It was the aim of Mapeo’s developers that data could remain, in the long-term, in the hands of local communities who would retain ownership and sovereignty. The offline peer-to-peer database and the app’s ease of use were created to facilitate this. Those who have access to data in the long term will depend upon what a community decides to do with it, who they share it with etc.; trust, like so many functions of Mapeo, is decentralized to the user. When working directly with community partners Dd recommends creating project protocols about use and storage of data and copies of the database, both to ensure there are backups and valuable data is not lost, and to ensure community data sovereignty in the long term. These features and guidelines are developed alongside Mapeo’s Indigenous cocreators, including the Ogiek of Mount Elgon in Kenya, who have said the following about the importance of community ownership and offline access to data: “This software can make a big impact on the community’s struggles. Most of the time we have challenges in how we can store our findings [to] use as evidence. Sometimes, outsiders would come into the community lands, and we did not have access to data to show them what it looks like. But now using the tech of Mapeo we can have it and put it in an archive that can be used later” (Ogiek Community Member, cited in Kemper, 2021).

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3.7.6 Mapeo Websync Dd is currently building a websync option for Mapeo users. This would not act as a server, but rather like an additional (online) device within projects. It would enable users to synchronize their database with an online instance, providing backup and data security if they are unable to synchronize easily with other project members. This feature would be completely optional, as Dd knows that the entirely offline and community-controlled access to knowledge is important for many users. It would be password protected, and data would not be accessible without the unique Project Key. However, this does introduce a level of trust into the use of Mapeo, as projects utilizing this feature would be trusting Dd to not access their data, and similarly trusting Dds cloud storage company not to interfere with their data. Dd is planning on making a release of this websync platform for teams to install and manage themselves, for example on their own server. This would require more technical setup, but for users for whom backups and online synchronization such as this was needed, it would provide additional security and internal control, and remove the need for trusting anyone outside the project.

3.7.7 Physical Security of Users Threats against land defenders, including many who use PM software are, unfortunately, high and increasing year-after-year (Global Witness, 2021; Okuda, 2021). As mentioned above, Mapeo does not currently collect any user metrics that could identify users or their locations, and Dd is currently carrying out user research across three continents to understand risks and threats faced by land defenders to better meet their needs. A summary of this research will be published in 2022.

3.8 Analytical Capacity Mapeo was not built for complex data analysis, and does not contain many provisions for it, as the developers wanted to keep its user interface simple and intuitive, to maintain the tech threshold for learning low. Its goal was to offer an easy way for communities to gather spatial data, manage and edit it, and make decisions about how to share it. If users have the skills and need to do further work with the data, it can be exported into various formats to be used within other tools for ­spatial or quantitative analyses. Dd prioritizes the interoperability of Mapeo to facilitate this.

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3.9 Visualization Capacity Data which is collected or created within MM or MD can then be viewed in the apps in a variety of ways, depending on the device (mobile or computer). MM has simpler options for visualization to keep the user learning profile low, and MD has more complex options, in line with its role for data management and creation of outputs.

3.9.1 Mapeo Mobile Data collected on MM (called observations) can be seen within the app in three ways. Map View  This presents the user with a background map (can be a customized offline map, the default offline map which comes with the download, or an online map if the user has internet access) onto which the observations within the Mapeo database are displayed. The user can navigate around the map with the touch screen and click on features to see details of different observations (see Fig. 3.3). Dd is currently developing a background map configuration which will allow users to switch with ease between different background maps. Switching between maps is currently possible but is technically more complex. Observation List  This lists all the observations in order of the date they were collected. Currently there is no filtering possible within MM, although observations collected by the device being used are distinguished visually from observations collected by other devices which have then been synchronized. The user can click on an observation to open its details screen (see Fig. 3.4). Observation Detail  This is where the information stored with a particular observation/data point is visible and includes the category assigned to the observation, any photographs taken at the time it was created, answers to questions associated with the category, the location coordinates of the observation and the date and time it was created (Fig. 3.5).

3.9.2 Mapeo Desktop Observations Screen Within the Observations Screen there are three primary visualization screens: map, media, and report. Map  When Mapeo is opened observations are primarily viewed in location on top of a background map (this can be a customized offline map, default offline Mapeo map or online map). Different categories of observations can be assigned differently colored dots, to ease identification. The Dd team will introduce the category icons

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Fig. 3.3  Mapeo Mobile map interface showing a custom offline map with sensitive information blanked out

onto the map within future MD development to further improve visualization and identification of features. Observations can be selected, and their details (including category, photos, coordinates, answers to questions, date and time of creation etc.) are then displayed in a box for viewing/editing. Observations can be filtered according to any of the fields associated with them, such as date of creation, category, answers to questions etc. and filtering by multiple fields is also possible (see Fig. 3.6). For example: users can filter and get a view of only certain categories of observations within a specified date range. Data can be exported as a whole or can be exported according to any current filtering choice.

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Fig. 3.4  Mapeo Mobile observations list interface in Spanish.

Media  The media view creates thumbnail images of all the photographs contained within the set of observations. The developers created this visualization to aid communities find observations and, for example, in the case of environmental monitoring, to pick out the most impacted and important sites to include within a report. Clicking on the photograph brings up the same observation details screen mentioned above. Filtering options work the same with the Media view (Fig. 3.7). Reports  The report view creates a formatted report of the data within the current filter set (see Fig. 3.8). The first page of the report shows a map with all the observations located on it, each observation then has its own page, with a map showing its location, and the photographs and information associated with it.

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Fig. 3.5  Mapeo Mobile observation detail, custom configuration Vieira Note: The MM app only displays point data collected within MM – it does not display any data created or imported into the Territory View of MD (whether point, line, or polygon), although this data is also stored within the peer-to-peer database synchronized on the phone.

In addition to editorial control over the observations included in the report, users can also control which information fields to include/exclude in the report, and therefore keep sensitive data private. Reports can be saved as PDFs for printing or digital sharing. Webmaps  Webmap visualizations are not included within MD, as the tool is built to work entirely offline. However, data can be exported for webmap and then users who have internet access and the desire to do so can create an account in maps. mapeo.app where they can upload datasets. They can then export a set of filtered and curated observations from MD and have them appear on an online map within their account, which they can share with others (e.g. publishing to social media).

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Fig. 3.6  Mapeo Desktop Observations screen with filtering

3.9.3 Mapeo Desktop Territory The MD Territory Screen presents users with a background map on which they view their data. Users can toggle between a variety of maps, both custom offline maps if they have been created, or any online maps available (default online map is a bing satellite map, but other maps are available depending upon the location) (Fig. 3.9). Vector data from MM, in addition to GPX, KML and GeoJSON files can be imported and layered on top of background maps. However, there are minimal ways to style the data in the application itself, other than through the creation of a custom configuration which requires more advanced technical skills. Most visualizations for display or for producing finished maps will be done using other software.

3.10 Openness MM and MD are both open-source projects, available under a GPLv3 license on Dd’s GitHub repository (https://github.com/digidem/). Whilst the application is open, user data is not, and all user collected data is currently only stored locally within project phones and computers (or wherever the user sends it), with no involvement of a server or online repository. This was a decision made by the developers both to ensure flat, peer-to-peer data hierarchy, and to protect data sovereignty, avoiding the dangers involved in making public certain types of sensitive data (Fagerholm, 2014). By controlling access to their data, Mapeo users might be able to shift the traditional balance of power away from government, corporations, and others who in the

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Fig. 3.7  Mapeo Desktop Media view with filtering, data Vieira 2022

Fig. 3.8  Mapeo Desktop report view, data Vieira 2022

past have tended to extract data Indigenous peoples. In some cases, having data first and foremost private and within a closed system can be a matter of cultural life and death, and the best way of ensuring the respect of their human rights. The case of sacred burial sites bulldozed by Dakota Access LLC just days after the Standing Rock Sioux published maps identifying their location, is one devastating example of what can happen when sensitive data is made public (Buhl, 2016).

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From MM data can be exported either by synchronizing with MD, and then exported into another format, or individual observations with attached fields can be exported via WhatsApp, email, telegram etc. From MD data can be exported to GeoJSON, CSV or for a webmap. There is currently no hosted online storage, online synchronization or backup of user data unless created and stored by the user. Dd prioritized the creation of a secure offline system first. However, as described in Sect. 3.7 on Data Privacy (p. 53), a websync feature is planned for release in 2022 to give users the option of synchronizing with an encrypted online copy of their database and also to set up their own server to run a similar service.

3.11 Accessibility Wherever participation of multiple mappers and observers is desired, smartphones are often the best option. External GPS units have some advantages for rural settings (good battery life, ruggedness, and dedication to GIS – therefore less likely to get appropriated for other uses), but smartphones are becoming more ubiquitous and are inexpensive and often more intuitively designed than GPS. Therefore, MM is a useful tool for walking into the field and recording observations. Currently the iOS version of Mapeo was planned to be released by the end of in 2022 (Digital Democracy, 2022). MM and MD function entirely offline and are therefore usable in rural areas without internet and mobile coverage, including for synchronization between smartphones. MM can be installed from the Playstore, or alternatively both MM and MD

Fig. 3.9  Mapeo Desktop Territory view showing a selection of online maps

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can be downloaded from Dd’s github repository and later installed on devices offline. Mapeo comes with a basic, low resolution offline map for the entire world, to ensure it can always be used offline, although satellite and other online background maps in both MM and MD require internet access to function. The process for creating custom offline background maps is being made significantly easier in 2022. It should be noted that storing or caching satellite images from services such as Bing or Google may violate their terms of service, so it is recommended to use Landsat, other raster maps or drone orthophotos. An added advantage of the open-source nature of Mapeo is the possibility of translation into any language, including non-colonial languages and Indigenous languages, a feature rarely available for mainstream GIS software. Dd uses a Crowdin platform for facilitating translations by project members, volunteers, or external staff, which are subsequently included in official Mapeo releases (https://crowdin. com/project/mapeo-­mobile). Mapeo is designed with large buttons, and with color-blind users in mind (although more work needs to be done to make this consistent across the platform). Additional accessibility features for audio or visually impaired users are planned.

3.12 Brief Use Cases The three Case Studies below present different use cases to help readers understand the range of uses Mapeo has. Case Study 1 documents a short training and implementation exercise carried out in Southern Mexico in 2021 to support community members map land-use and farming infrastructure, mainly using MM. Case Study 2 documents the training of an Emberá Indigenous community in Darién Panama, who used MD as part of a mapping process to gain official recognition of their collective land. Case Study 3 documents an ongoing project (anonymized to protect identity of local land defenders) in which Indigenous Community members collected evidence of illegal activities occurring on their lands, using MM and MD. For other case-studies see the Mapeo website www.mapeo.app

3.12.1 Case Study 1: Mapping Farming Landscapes of Costa Grande Mexico Through Mapeo Mobile and Mapeo Desktop, Supported by José Maria León Villalobos Members of the Tragame Tierra group (TT), the Universidad Campesina del Sur (UNICAM-SUR) and from the Centro de Bachillerato Tecnológico Agropecuario (CBTa) N° 315 at the communities of Coyuca de Benítez and Tepecoacuilco de Trujano, Guerrero, Mexico wanted to map the existing land uses and available

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farming infrastructure in their communities. With the help of researchers of Centro Geo (CG), they were trained in the use of MM and MD in a five-hour workshop. The training program aimed to teach participants how to download, operate and synchronize data within Mapeo, and how to draw lines and polygons using MD. Five people from the TT group were involved in the training workshop, four males and one female aged 20–29 years, they both held bachelor’s degrees and university studies. From UNICAM-SUR were three participants, two females and one male aged 32–58 years, with bachelor to university degrees; and only one woman from CBTa participated, aged 42 years with a university degree. One week later, participants were asked to share their experiences using Mapeo, in terms of its accuracy for mapping, cost, required technical level and spatial learning perspectives. They also made recommendations on ways to improve Mapeo. Additionally, researchers assessed the outcomes and the level of participation during training and implementation phases. All participants were able to download and install MM on their phones. They collected between 10 and 15 observations for their mapping purposes. Information gathered was diverse, from places of cultural interest to civil and farming infrastructure and natural resources (types of vegetation and crops) (see Fig. 3.10). Participants used the default symbols available in MM to categorize their observed points. They also added UTM coordinates manually using the GPS, photos, as well as brief stories, and explanations about places. Only the participant from CBTa was able to install MD on her personal computer and synchronize the collected observations from MM. Using the online background maps in MD, from satellite images to maps showing elevation, streets, water streams, forest, and crop covers, the participant from CBTa located and drew new observation points (see Fig. 3.11). She added features, such as the school perimeter and infrastructure, the existing cement tanks for farming tilapia, and maize and maguey croplands in her community. Although all participants were active and widely involved in the training phase, their participation declined during the implementation phase. In general, participants developed skills for working on the Mapeo platform, but the operation of the mobile app MM became more familiar to them, allowing, they said, simple and intuitive access. On the other hand, MD requires a personal computer and sufficient bandwidth to support satellite image visualization which is not always available for poor and marginalized communities in southern Mexico. Participants also needed higher technical skills for using MD. Overall, participants improved their spatial knowledge using Mapeo. They expanded their mental map when walking paths and routes, collecting points, drawing sites and land uses. Mapeo not only enabled participants to see all the information they collected on a digital map and strengthened their spatial analysis capacity, but also made it easier to generate new knowledge on the potential uses of their territories. In addition, a sense of pride was observed among participants when they talked about using Mapeo to visualize their data on a map.

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3.12.2 Case Study 2: Mapping Collective Emberá Land in Darien, Panama, Mir Rodríguez Lombardo Pijibasal is an Emberá Indigenous community in the Darién province of Panama. As part of the “Cartografía de los bosques del pueblo” (People’s Forests Cartography) the author’s organization, Almanaque Azul, partnered with the local organization ANCAPIJI to offer technical support in their struggle for official recognition of the collective land (tierra colectiva), about half of which is primary forest adjacent to the Darién National Park, the largest terrestrial protected area in the country. As part of the project, members of the community formed a technical group to be trained in mapping in order to produce a map of the collective land and forest reserve. The first day of the workshop was done while walking with the technical team through the land. Walking the land is the main tool in our participatory mapping process. During our walk, discussions were had with the team about local resources in the forest and their relation to food production and other aspects of the economy, including tourism, as well as threats to their land. We spent the afternoon engaged in critical analysis of preexisting maps of their territory. As the day ended, we began working with computers. Computer expertise among members of the technical group was low. There were three smartphone users, one of which also had a laptop computer. MD had been pre-­ installed on Lenovo Thinkpad laptops (running Linux Mint) with a ratio of 2 to 3 participants per workstation. Both Linux and Mapeo allowed us to run a very low overhead setup with a minimal user interface if compared with Windows and any other GIS application. We set up Mapeo with various “background” layers

Fig. 3.10  Observations of the maguey (a) and maize (b) croplands in Tepecoacuilco de Trujano, Guerrero, Mexico, collected by participants using MM

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Fig. 3.11  Polygons of the maguey (a) and maize (b) croplands in tepecoacuilco de trujano, guerrero, mexico drawn by participants using MD

(1:250,000 government maps, Landsat false color images, Bing satellite images for Darién and a high-resolution drone mosaic orthophoto of the community) as well as “overlay” layers (Global Forest Watch (Hansen et al., 2013) 2018 forest loss and national protected land polygons), which appear to the user on a simple collapsible list on the right side of the screen. The group, including participants who had no to very little experience with computers, became quickly (1–2 h) accustomed to the MD user interface. Using external USB mice with scroll wheels, they were able to locate their community in satellite images and examine the surrounding areas, identify errors in the government maps (including the location of Pijbasal and a spelling mistake), identify and discuss specific tree cover loss events and look more closely at other parts of Darién and Panama. Mapeo proved to be an extremely valuable tool for the critical cartography module of the training. In subsequent sessions and over further visits, Mapeo was used for mapping. Preexisting paper maps of the collective land polygon were digitized and added as an overlay layer and data collected using mobile phones (with the open source Geopaparazzi application, this was before the development of MM) and Garmin standalone GPSs was downloaded and added. Waypoints were checked against notes and named and categorized using Mapeo’s default categories. Rivers were named during intense discussions, mixing large printouts and Mapeo. The resulting information was exported to USB and used in QGIS to produce the first iteration of a map which was discussed in later visits.

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3.12.3 Case Study 3: Monitoring Land Incursions and Illegal Activities within Indigenous Territories This case-study is anonymized to protect the identity of the Land Defenders involved, as the work has not all yet been made public. It is an ongoing project within the Amazon basin in which a group of four neighboring Indigenous communities formed an alliance in order to defend their territory from illegal poaching, logging, fishing and gold mining. They are using Mapeo to map and monitor these illegal activities, to report back their findings to the community and to make decisions about legal or other enforcement actions to take to defend their lands. When the Indigenous patrol was set up a team of 12 community members received a three-day training in MM and MD, as well as GPS, camera and camera trap usage, teamwork, and security from a local ally organization, which continues to accompany their work. They developed a custom configuration for Mapeo allowing them to create their own icons and legend and set their own questions for each type of observation (e.g. illegal fishing with dynamite, land cleared by settlers, shelter used by poachers). They also created an offline background map permitting them to see important features within the area they were monitoring, whilst they were out in the field without any mobile coverage eg. mining concessions, national park limits, small water sources etc. The land defense team now carries out regular patrols of their land, walking to areas where they suspect illegal activities are taking place and documenting any evidence, they find with Mapeo, in conjunction with other photographic, video and camera-trap evidence. This evidence is then synchronized with Mapeo Desktop, so that it can be filtered, visualized, and reports made for sharing internally to aid decision making about any enforcement actions to be carried out. Some collected evidence has been shared with local law enforcement agencies, for example to get illegal settlers removed. Other evidence is still being collected to build up a full picture of what is happening, so that the communities can agree on a collective strategy, create internal protocols and then approach the appropriate law enforcers, government agency or media, in order to take action.

3.13 Comments and Recommendations Mapeo Mobile and Desktop together offer a solution for PM designed to empower non-technical users and support collaborative workflows and data sovereignty. Its development was based on a reflexive and iterative process with Indigenous communities, in which the designers and developers self-consciously questioned the power dynamics it embodied, in addition to the specific needs and requirements of the communities it was to serve. Mapeo is a tool still in development, and some aspects the authors found deficient appear on its roadmap for this year (Digital Democracy, 2022), such as iOS,

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easier background map management, route tracking etc. However, Mapeo does not claim to be a tool which will solve all GIS needs and intends to keep its functionality limited to ensure continued ease of use and intuitive design, with more complex data analyzes to be carried out by exporting data to other programs. Based on their own use, and that of the communities and groups they have trained, the authors have the following recommendations for improving Mapeo. The iterative codesign process with users must be maintained and broadened, to ensure ongoing relevancy and reflection of local needs; more work is needed on the ability to output completed maps from MD with titles and legends etc.; guides and tutorials must be made available in more languages; the customization process of configurations and offline maps should be made easier for users with low tech skills to access. However, despite these recommendations, the authors believe Mapeo stands out in the ecosystem of PM tools due its ease of use and some of its unique and special features. Significantly amongst these is its peer-to-peer database structure, allowing for completely offline, non-server dependent data storage, and the security, privacy, and sovereignty which this offers to communities. In addition, its focus on design with and for communities, being developed from the ground up, offers a vision of an alternative design process, and the possibility of creating and incorporating non-­ colonial concepts and technologies which could serve as an example for Indigenous-­ centered technology development in other areas (video and graphics editing, music production, programming languages, mobile devices).

References Abbot, J., Chambers, R., Dunn, C., Harris, T., Merode, E. D., Porter, G., Townsend, J. and Weiner, D. (1998). Participatory GIS: opportunity or oxymoron. PLA notes., 33, 27–33. Buhl, D. (2016). Sacred burial grounds destroyed, judge halts construction on portion of Dakota Access pipeline. https://www.ecowatch.com/sacred-­burial-­grounds-­dakota-­access-­ pipeline-­1998932006.html Chambers, R. (2006). Participatory mapping and geographic information systems: Whose map? Who is empowered and who disempowered? Who gains and who loses? The Electronic Journal of Information Systems in Developing Countries, 25(1), 1–11. Christin, D., Reinhardt, A., Kanhere, S. S., & Hollick, M. (2011). A survey on privacy in mobile participatory sensing applications. Journal of Systems and Software, 84(11), 1928–1946. Digital Democracy. (2022). Mapeo roadmap. https://github.com/digidem/mapeo-­roadmap Earth Defenders Toolkit. (2021). Mapeo: Monitor and map the world around you. https://www. earthdefenderstoolkit.com/toolkit/mapeo-­monitor-­and-­document-­the-­world-­around-­you/ Fagerholm, N. (2014). Whose knowledge, whose benefit? Ethical challenges of participatory mapping. In J. Lunn (Ed.), Fieldwork in the global south: Ethical challenges and dilemmas (pp. 158–169). Routledge. Fox, J., et al. (2005). Mapping power: Ironic effects of spatial information technology in mapping communities, ethics values, practice. East-West Center. See: www.eastwestcenter.org/ Global Witness. (2021). Last line of defense: The Industries causing the climate crisis and attacks against land and environmental defenders. https://www.globalwitness.org/en/campaigns/ environmental-­activists/last-­line-­defence/

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Hansen, M. C., Potapov, P. V., Moore, R., Hancher, M., Turubanova, S. A., Tyukavina, A., Thau, D., Stehman, S.  V., Goetz, S.  J., Loveland, T.  R., Kommareddy, A., Egorov, A., Chini, L., Justice, C. O., & Townshend, J. R. G. (2013). High-resolution global maps of 21st-century forest cover change. Science, 342, 850–853. Jacobi, E. (2020). Indigenous data sovereignty in Southeast Asia, with Pyrou Chung. https:// digital-­democracy.org/indigenous-­data-­sovereignty-­in-­southeast-­asia-­with-­pyrou-­chung/ Jacobi, E. (2021). Mapeo selected as a 2021 Solver with MIT Solve. https://digital-­democracy.org/ mapeo-­selected-­as-­a-­2021-­solver-­with-­mit-­solve/ Kemper, R. (2021). Mapping Ogiek ancestral lands in Kenya using Mapeo, during a pandemic. https://digital-­democracy.org/mapping-­ogiek-­ancestral-­lands-­in-­kenya-­using-­mapeo-­during-­a-­ pandemic/ Kukutai, T., & Taylor, J. (Eds.). (2016). Indigenous data sovereignty: Towards an agenda (CAEPR research monograph, 2016/34). ANU Press. Kukutai, T., Carroll, S. R., & Walter, M. (2020). Indigenous data sovereignty. In D. Mamo (Ed.), The Indigenous world 2020 (34th ed., pp. 654–662). IWGIA. Louis, R. (2004). Indigenous Hawaiian cartographer: In search of common ground. Cartographic Perspectives, (48), 7–23. McCall, M. K. (2006). Precision for whom? Mapping ambiguity and certainty in (Participatory) GIS. Participatory Learning and Action, 54(1), 114–119. McKelvey, K. (2019). Local-first software for frontline communities. https://digital-­democracy. org/local-­first-­software-­for-­frontline-­communities/ McKelvey, K. (2020). Solidarity technology: Values for an Earth Defender’s Toolkit. https:// digital-­democracy.org/solidarity-­technology-­values-­for-­an-­earth-­defenders-­toolkit/ Okuda, I. (2021). Paying the price: A study on criminalization of land and environmental rights defenders in East Africa. https://d3o3cb4w253x5q.cloudfront.net/media/documents/ILC_ RRI_PayingthePrice_Report.pdf Open Street Map. (2012). Building a friendly editor for OpenStreetMap in JavaScript. https://blog. openstreetmap.org/2012/07/13/building-­a-­friendly-­editor-­for-­openstreetmap/ Rambaldi, G., Chambers, R., McCall, M., & Fox, J. (2006). Practical ethics for PGIS practitioners, facilitators, technology intermediaries and researchers. Participatory Learning and Action, 54(1), 106–113. Reid, G., & Sieber, R. (2020). Do geospatial ontologies perpetuate Indigenous assimilation? Progress in Human Geography, 44(2), 216–234. Rose-Redwood, R., Blu Barnd, N., Lucchesi, A. H. E., Dias, S., & Patrick, W. (2020). Decolonizing the map: Recentering Indigenous mappings. Cartographica: The International Journal for Geographic Information and Geovisualization, 55(3), 151–162. Ryan, A. (2017). Mapping Waorani territory: Update from the Ecuadorian Amazon. https://digital-­ democracy.org/mapping-­waorani-­territory-­update-­from-­the-­ecuadorian-­amazon/ Ryan, A. (2018). Our rivers are not blue: Lessons, reflections and challenges from Waorani map making in the Ecuadorian Amazon. Bulletin of the Society of Cartographers, 51, 59–60. Rzeszewski, M., & Kotus, J. (2019). Usability and usefulness of internet mapping platforms in participatory spatial planning. Applied Geography, 103, 56–69. Stone, P., & Calderon, A. (2019). Care principles: Unpacking Indigenous data governance. https:// medium.com/opendatacharter/spotlight-­care-­principles-­f475ec2bf6ec Weyer, D., Bezerra, J. C., & De Vos, A. (2019). Participatory mapping in a developing country context: Lessons from South Africa. Land, 8(9), 134. Wilson, K. (2021). Making the mindset shift: An interview with Digital Democracy lead UX Designer Sabella Flag. https://simplysecure.org/blog/making-­the-­mindset-­shift-­an-­interview-­ with-­digital-­democracy-­lead-­ux-­designer-­sabella-­flagg/ Wilson, K. (2022). Keeping everyone safe: Quick user oriented problem solving with Mapeo.https://simplysecure.org/blog/keeping-­everyone-­safe-­quick-­user-­oriented-­problem-­solving-­with-­mapeo/

Chapter 4

Maptionnaire Marketta Kyttä, Nora Fagerholm, Vera Helene Hausner, and Anna Broberg

Abstract  Maptionnaire is a community engagement platform that aims to bridge the gap between planners or decision-makers and citizens. Maptionnaire Community Engagement Platform is a modular online platform with map-based engagement at its core. The service enables the creation of community engagement activities, systematic and comprehensive data collection, analysis and reporting of data and activities. Maptionnaire service has been used in 40 countries in more than 10,000 projects. The total number of survey participants exceeds 500,000 and there are more than 10 million map-based responses by them. Maptionnaire has been used both in academic research projects and in public participation processes. The participatory planning projects vary in geographical scale stretching from nationwide surveys to those concerning single buildings. In terms of the project topics, green and blue area planning and management projects together with transportation planning projects comprise over half of the cases. In regard to the phases of the planning project, both extremes, the early initiation and the evaluation phase stand out. Cities of Helsinki, Stockholm, New York, Denver, San Francisco, Edinburgh, and Copenhagen are among the many cities that have used Maptionnaire in their community engagement processes.

M. Kyttä (*) Aalto University, Helsinki, Finland e-mail: [email protected] N. Fagerholm University of Turku, Turku, Finland e-mail: [email protected]; [email protected] V. H. Hausner The Arctic University of Norway, Oslo, Norway e-mail: [email protected] A. Broberg Mapita Oy, Helsinki, Finland e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 C. M. Burnett (ed.), Evaluating Participatory Mapping Software, https://doi.org/10.1007/978-3-031-19594-5_4

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Keywords  Public participation GIS · PPGIS · Maptionnaire · Public participation · Cities

4.1 General Information Name of Application: Maptionnaire Name of Developer: Mapita Oy Name of Funder: Finnish Funding Agency for Technology and Innovation (TEKES) funded the original soft GIS prototype of “softGIS” as part of a research project of Aalto University (former Helsinki University of Technology) in 2005. After commercialization by Mapita Oy in 2011, the technical development of the Maptionnaire service has been realized through cash flow financing. Business Finland (former TEKES) has also provided small financial support. Type of System Software: SaaS Type of Programming Language: JavaScript API Availability: Private Features: Maptionnaire features include: • • • • • • • • • • • • • •

Editor for creating and managing community engagement processes Map-based surveys (general or user’s own basemaps) Conventional surveys Picture based surveys Polling and voting tools Automated PDF creator Real-time feedback map Gamified decision making 3D Collaboration Webpage builder Participatory budgeting process support Translation tool Inbuilt analysis tool Interface for survey respondents

Cost: There are three different product levels that contain a varying set of modules. The Maptionnaire subscription can be purchased either as a set term subscription or as a continuous subscription. Prices vary according to these alternatives. Prices range from USD 950 per month for a single project to USD 50k per year for enterprise solutions. Type of Data Collected: Place-based data (points, routes, areas) typically concern: • • • •

future wishes, visions, and preferences preferences, attitudes, or values concerning current environment behavior, lifestyles, and everyday practices environmental phenomenon and problems (citizen science)

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• Other collected data typically include: Background information General knowledge about the individual Outcome variables (e.g., neighborhood satisfaction, perceived quality of life, health etc.) Overview: Maptionnaire has been designed as a community engagement platform that aims to bridge the gap between planners or decision-makers and citizens (Kahila & Kyttä, 2009). The Maptionnaire Community Engagement Platform is a modular online platform with map-based engagement at its core. The service enables the creation of community engagement activities, systematic and comprehensive data collection, analysis and reporting of data and activities. The main module includes map-based questionnaires, polls, voting tools, surveys, picture-based surveys, and more conventional survey elements, as well as analysis tools and data management functionalities. Descriptions of the solution are fetched from Maptionnaire website (https://maptionnaire.com). Maptionnaire offers a complete engagement process under one platform. Other modules include Automated PDF creator, Real-time feedback map, Gamified decision making, 3D Collaboration, and Website builder. Additionally, the service consists of an interface for survey respondents through which they can register accounts and review, manage and track their input to surveys. Maptionnaire service has been used in 40 countries in more than 10,000 projects. The total number of survey participants exceeds 500,000 and there are more than 10 million map-based responses by them. Maptionnaire has been used both in academic research projects and in public participation processes (examples at https://participatorymapping.org/). Kahila-­ Tani et al. (2019) studied a sample (n = 203) of Maptionnaire projects that were realized as part of real-life public participation projects. The analysis revealed that the studied planning projects vary: – Ingeographical scale stretching from nationwide surveys to those concerning single buildings. Most cases were related to neighborhoods while city/ municipal level cases were also common. – Interms of the project topics, green and blue area planning and management projects together with transportation planning projects comprised over half of the cases. Statutory master and regional planning cases as well as statutory detailed planning cases were also common, in total comprising about one third of the cases. Additionally, the tool has also been used e.g., for ecosystem-based management, climate resilience and adaptation planning, and for protected area management (not included in the review). – Atwhich phases of the planning project was Maptionnaire used. Participation becomes more effective if it takes place early enough in the planning process (cf. Friedmann, 1992). In the Maptionnaire cases both extremes of the planning process stand out. Early initiation has been the most common (49%), but 37% of the Maptionnaire cases have also been applied in the evaluation phase.

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In the case there is no Internet connection, the stand-alone version of Maptionnaire would be needed. The problem would, however, be the interactive maps. In principle it would be possible to realize a standalone version of Maptionnaire, but the solution would be very expensive.

4.2 Ethics In today’s world where geolocated data is produced constantly by sensors passively from space but also actively by people, it becomes important to consider how the costs and benefits from mass and multiple use of geospatial location data are distributed. This creates a new dimension of power relations. In response, EthicalGEO Initiative by the American Geographical Society has produced a common set of guidelines for responsible use of location data (https://ethicalgeo.org/ locus-­charter/). With digital platforms such as Maptionnaire, there is excitement about geo-­ referencing our human physical, biological and socio-cultural worlds and making the information accessible in the public domain. However, there are risks inherent in visualizing place-specific local knowledge and making it available for public consumption, for example when it comes to vulnerable communities. Hence, there is a need to ensure sufficient control of the participatory mapping process and outputs (Rambaldi et al., 2006) and critically assess practices through an ethical lens prior to implementation of map-based surveys. As the use of Maptionnaire is often linked to actual urban, land use, or environmental planning processes, the codes of ethics for public participation are also relevant for Maptionnaire users. For example, the International association of public participation has created a set of principles, which guides towards a responsible practice in the public participation processes (https://www.iap2.org/page/ethics). So, the ethical guidelines must be considered in all phases of the participatory planning process, from the identification of stakeholders and the definition of goals to method selection, and context sensitive application all the way to data collection and critical evaluation (https://participatory.tools/).

4.3 Costs Maptionnaire is not an open-source service. Maptionnaire service has a business model in the background: the activities of a company must be profitable. Although open access tools in principle would be ideal, in practice a skillful service provider is typically needed to tailor the open-source tool for the purposes of the client. It is unrealistic to expect that for example a city organization would include a developer network.

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In the Maptionnaire service there are three different product levels that contain a varying set of modules. The Maptionnaire subscription can be purchased either as a set term subscription or as a continuous subscription. Prices vary according to these alternatives, ranging from $950 USD per month for a single project to $50,000 USD per year for enterprise solutions.

4.4 Technical Level Maptionnaire fills all the requirements of A-level as well as AA-level of the Web Content Accessibility Guidelines (WCAG 2.1). The usability of Maptionnaire has been evaluated using three approaches: (1) Heuristic usability evaluation, (2) email surveys, and (3) implicit feedback. 1. According to Ballatore et al. (2019), in a heuristic usability evaluation, a usability expert, external to the developers’ team, reviews the products informally based on general usability and accessibility principles. Maptionnaire has been audited for its conformance with W3C’s Web Content Accessibility Guidelines (WCAG). Overall, its accessibility level was deemed high. Most accessibility problems may be caused by users’ content such as video or audio media. 2. Also, traditional email surveys can be used to study usability and to reach PPGIS users and detailed questions can be asked especially from those users, who use the product infrequently (Ballatore et al., 2019). Mladenović et al. (2021) queried Maptionnaire users who had used the service in participatory transportation planning cases. Although the number of respondents was only 21, some interesting findings concerning the usability were found. When asked whether the planners would recommend the tool to a fellow planner, with a ranking from one to ten (max), the responses varied between eight and ten, with mean being 9.33. The respondents highlighted the easiness of using the tool: easiness for residents to answer online surveys and to provide input as opposed to other methods; easiness of demonstrating plans and other visual features on a survey map; easiness of utilizing data that is already collected in a digital format; easiness of marketing web-based questionnaire using social media or other means; easiness of importing georeferenced data into GIS analysis software and easiness to develop surveys by using ready-made PPGIS tools together with different organizations within the municipality. Other identified benefits included the possibility to collect opinions beyond standard questionnaire answers, including individual experiential understanding, wishes, unexpected positive/negative effects, or more straightforward plan recommendations. The number of map answers and their statistical significance impressed many respondents, the number and depth of open answers, and the differences in answers based on location surprised them after completing the data collection and analysis processes. Some respondents also expressed their surprise with the conflicting aspects in the citizens’ answers

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and highlighted the benefit of reaching different target groups using survey customization. In addition to benefits from using Maptionnaire methodology, respondents also identified some challenges. While some experts valued a high amount of data, others found challenges in analyzing large data sets, and in particular an analysis of many open comments from citizens that has been deemed to be difficult and time consuming to analyze. Several planners identified the challenges participants face when using the survey tool, especially surveys with many georeferenced questions and map-based questions that require input in the form of route or area. Lengthy surveys or answering options might lead to respondents dropping out – there certainly are limits to what respondents can suggest based on the descriptions of hypothetical situations in the built environment. Many respondents expressed concerns that the use of digital tools might exclude some potential respondents. 3. Finally, implicit feedback (Ballatore et  al., 2019) has been gathered to learn more about the usability of Maptionnaire. Here, information can be collected e.g., about users’ page views, clicks, taps, and mouse movements. Gottwald et al. (2016) studied the usability of Maptionnaire among older adults (n = 20, mean age 70) whose general Internet skills remain limited compared to those of younger age groups. The computer screens and participants’ voices were recorded, and field notes were taken while participants completed several tasks with Maptionnaire. These tasks included answering multiple choice and open-­ ended questions, using drop-down menus, scrolling down the page, marking a place on a map, drawing a route on a map, and zooming and panning. The study found cognitive, motor, and sensor challenges among older adults when using Maptionnaire. An example of a cognitive challenge would be a difficulty in using the zooming functions, a motor challenges were related (e.g., to difficulties drawing routes and especially finishing the route by clicking twice on the same spot or double clicking). An example of a sensory challenge was the misinterpretation of the save button with ‘v’ symbol which was not recognized. Mapita developers were involved in the study, and they improved the usability of the tool based on the findings. Similarly, the mouse wheel’s zoom function was disabled to reduce the likelihood of becoming lost by accidentally zooming in or out and a neighborhood drop down menu was added. Also many other improvements were made e.g. to the font and colors used in the service. Maptionnaire is typically used by participants independently without any assistance, so therefore the usability of the service is essential. Exceptions include the use of the tool among children and young people: in projects with these target groups, data is often collected in schools where teachers and/or research assistants provide children help with answering the Maptionnaire survey (Broberg et al., 2013; Kyttä et al., 2018; Egli et al., 2020). The use of an assistant, sometimes referred to as chauffeurs, is also essential when a map survey is targeted and perhaps co-created together with people with immigrant background.

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Planners and researchers have been actively involved in the co-creative development process of the Maptionnaire service, but end users (participants) not so often. In some cases, the content of the Maptionnaire survey has been co-created with participants by involving participants in the early phases of the participatory planning process to co-developing the survey contents. This approach has been realized by some cities (e.g., cities of Hyvinkää and Helsinki, Finland). The design of the tool itself, nevertheless, has not been done together with participants.

4.5 Inclusiveness Online platforms such as Maptionnaire have the advantage of engaging a larger number of participants to collect spatial information or seek solutions across diverse, and often conflicting, segments of the society. Among the about 200 real-life Maptionnaire surveys that Kahila-Tani et al. (2019) reviewed, the survey reached on average 467 participants. Most surveys did not use incentives, which means that this online platform can reach a relatively large number of voluntary participants. Online community engagement platforms could also enrich participatory processes by addressing some of the barriers to participation, including time constraints, distance to travel, and physical disabilities. Online engagement of people in their own homes has proven particularly valuable during lockdowns such as the COVID-19 pandemics. Furthermore, those that usually do not engage as stakeholders in planning processes can voice their opinion individually and provide information anonymously during a planning process. Allowing people to map anonymously is particularly advantageous in cases where the issue at stake is conflict-filled or elites or vested interests are limiting open communication among participants. A few studies demonstrate that the features mapped by randomly selected households, or the “silent majority,” differs substantially from results deriving from traditional participatory mapping processes such as community workshops (Brown et  al., 2014), advisory councils (Engen et al., 2018), and participatory mapping based on interviews (Brown et al., 2017). Like any other survey, the inclusiveness depends upon the sampling and design. PPGIS surveys that have recruited participants through random household sampling show a varied representativeness. In some cases, socio economic and geographical representativeness has been good (Laatikainen et  al., 2015), in other cases it has been compromised (Kahila-Tani et  al., 2016). It is typically mid-aged men with higher education and income that participate in online mapping relating to natural resources and the environment (Brown, 2017). Some surveys relating to urban planning have seen an overrepresentation of women (Kyttä et al., 2011) and older adults (Kyttä et al., 2013, 2016), others, young adults (Kahila-Tani et al., 2016). Rather, it seems that the sampling and recruitment strategy matters: when comparing random household surveys and volunteer sampling, for instance, Brown (2017) found that personal invitations that are based on random sampling seem to promote good representativeness while open marketing of surveys to engage volunteers typically

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create problems with respect to unbalanced respondent profiles and the quality of the mapping process as measured by both number of features mapped and time spent on mapping (Brown, 2017). The digital divide due to varying technological skills, competencies and access to technological devices is important when using online community engagement platforms (Van Dijk, 2017). Digital literacy is among the barriers for participation among some groups, such as older adults and disadvantaged groups, with limited access to the Internet. Young people and indigenous people are often underrepresented in online platform surveys, which is partly ascribed to the relevance of survey design. The Maptionnaire tool can however also be used in facilitated workshops or surveys to help overcome this barrier, or dedicated surveys can target underrepresented groups (Fagerholm et al., 2019, 2021). The platform is also flexible and depending on the design, the participants can also add videos, texts, and options for open-ended questions where participants can ascribe meaning to mapped features. Allowing the use of different languages in the respondent interface helps attract more variable groups of people. Maptionnaire as a service entails an inbuilt translation tool that allows creating language versions of the community engagement activities. Currently, the service interface for the respondents is available in 43 languages, including languages using writing systems other than Latin alphabet (such as Hebrew or Arabic where spelling is from right to left, or Chinese and its characters). However, language options are not the only way of increasing inclusivity. In a project realized in Jyväskylä, use of short explanatory movie clips, visualizations and pictograms were tested along with the use of plain, simple Finnish language to help a diverse population in answering a survey. This was done because the inhabitants of the neighborhood of Pupuhuhta speak numerous different languages, and many were illiterate. Local activists contributed to the development of a suitable outreach strategy.

4.6 Data Accuracy There are few dedicated studies measuring the accuracy of data produced by individual users of Maptionnaire. Positional accuracy depends on the design of the Maptionnaire survey as well as the usability (as described in Sect. 4.4). In a recent experiment with users of different ages in Poland, for example, Rzeszewski and Kotus (2019) found that only 60% of participants successfully identified their homes or work location using Open Street Map as the web interface with an option available to overlay the map with a Google satellite picture. Older people faced more cognitive challenges when mapping the locations, but their familiarity with the city and the longer time spent mapping resulted in no age differences in the number of mapped locations later in the survey. This illustrates some of the challenges of evaluating positional accuracy of mapping. Accuracy of individual contributions to the map depends on digital literacy, motoric challenges of place pins, zoom or text, and the sensory qualities of the web

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interface (see Sect. 4.4), as well as familiarity with the area and time spent mapping. Software needs to be continuously developed to increase accuracy of mapped localities over time, preferably based on usability tests with participants who are likely to face the greatest challenge of placing a pin or drawing a polygon in the right location. For example, the recent update of the Maptionnaire software included several revisions that could improve accuracy based on the challenges that older participants were facing when mapping online (see Gottwald et  al., 2016). The Maptionnaire software also has several options available for enhancing the ability of users to recognize the right locations in the map. Among these are the possibility to create your own map or use topographic maps that participants are familiar with as a base layer. There are other ways of evaluating the data accuracy than observing and evaluating the individual participant’s ability to precisely locate known features on a map. For example, Laatikainen et al. (2018) used GPS tracking of 18 individual participants (55–75 years) to assess the accuracy of mapping everyday use of a city neighborhood in Helsinki. The overlap between the data from GPS tracking and participatory mapping using the Maptionnaire software was as high as 79% when estimating individual home ranges of participants. Participatory mapping using similar online platforms have identified native vegetation with an accuracy level ranging from 78% to 94% (Brown, 2012) and wildlife habitats of four species ranging between 74% and 85% (Cox et al., 2014). Brown et  al. (2018) emphasized the need to distinguish between validity-as-­ accuracy and validity-as-credibility when measuring the performance of PPGIS against a koala likelihood distribution map. Validity-as-accuracy is when the quality of the map is checked against authoritarian maps or against well-known geographic features, whereas the concepts of validity-as-credibility acknowledges that not all contributions are equal and therefore more weight needs to be given to those that have more accurate contributions. In the Koala case, for example, more accurate observations were provided by older citizens, with higher self-rated knowledge, higher education and who had lived for a long time in the area. Combining spatial data with the profile gathered from sampling unique IDs or from the survey questions in the Maptionnaire platform allows for analyzing validity-as credibility relating to mapping behavior and data quality. Data completeness is another issue for evaluating the accuracy of the data. Lack of mapping does not indicate that values, emotions, knowledge, or preferences are absent on that site. Participants familiar with the site might not have been recruited to the platform. Checking the mapping against home locations or accessibility to a site is one way of evaluating the accuracy. For example, social interactions have been shown to take place close to people’s homes (Fagerholm et al., 2019) and road and trail access matters for where the crowd are mapping place values (Muñoz et al., 2020) or preferences (Engen et al., 2018). Blindly assuming that data accuracy and map quality increases with a larger number of participants in the online mapping platform can lead to false assumptions of the distribution of values in landscapes. For example, Brown and Hausner (2017) found people to map social and recreational values close to roads whereas biodiversity, wilderness and

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ecosystem functional values were mapped at the longer distance. Pooling all these attributes together can result in absurd assumptions, such as: “given that people are mapping more closely to roads, we need to build more roads to satisfy the demand”. In other words, when evaluating the data accuracy and the spatial quality of the data the different attributes need to be treated separately. One way to assess data deriving from Maptionnaire and similar online platforms is to evaluate the map by transferring values to a comparable replication site and check for uniformity error (i.e. the spatial clustering resulting in large errors when transferring values), sampling error (i.e. the sampling error resulting from difference in sampling and response biases in those two sites) and regionalization error (i.e. when results are not generalizable because the other area is not sufficiently comparable to the other). By using land cover as a transfer medium, Brown et al. (2016), for example, found sampling and regionalization error to be low whereas uniformity error differed with respect to the cultural ecosystem services being mapped. Scenic, recreational, and cultural values transferred from one region to the other demonstrated a high accuracy as measured against primary data (92–97%), whereas provisional services such as hunting, fishing, and gathering resulted in a larger variation in estimates (73–96%) depending on the land cover map used for transferring data.

4.7 Data Privacy Europe has the strongest data privacy rules and therefore it is important to scrutinize them and consider them in relation to the data privacy of PPGIS datasets. The European Union General Data Protection Regulation (GDPR), implemented since May 2018 (European Parliament and Council, 2016) and superseding the Data Protection Directive of 1995 (European Parliament and Council, 1995), are of greatest interest here. The aim of the GDPR is to protect the rights of natural persons – in relation to the processing of their personal data and to harmonize these rights across the EU member states. The GDPR defines personal data as any information that may lead to the direct or indirect identification of a natural person. Natural persons have rights concerning their personal data (e.g., the right to be informed about the content and processing of the personal data and the right to access, rectify, or erase personal data). Maptionnaire platform is designed to accommodate the GDPR legislation. Respondents own their data, and they need to be able to access, modify and withdraw the data they have given. Any data or information produced, compiled, or created, also in collaboration with Mapita is owned by Mapita’s customers and eventually the survey respondents. Data is safely collected and stored on the platform. While the platform can be used for participatory mapping with all citizens, including vulnerable groups, the users are responsible for designing a participatory mapping project that comply with ethical standards, including how people are recruited, the survey designed, how data is stored over time and how the reporting and communication of these data is arranged.

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When making an agreement with Mapita, the control of data is agreed on. The customer is regarded as a data controller in regard to any data relating to an identified or identifiable natural person (“Personal Data”) that is included in the survey response data collected by the customer. Mapita acts as a data processor as defined in the EU General Data Protection Regulation (GDPR) and assists the customer to e.g. take appropriate technical and organizational measures to prevent unauthorized or unlawful processing, accidental loss, destruction or damage to Personal Data and in fulfilling customer’s obligation to respond to requests relating to data subjects’ statutory rights. While the use of PPGIS for data collection has been growing rapidly over the past few years, the questions regarding data sharing have arised. Because the survey creators have the primary access to the dataset, they can decide what steps to take in (possible) data sharing. Although open data add to the transparency there are significant legal and ethical challenges as PPGIS datasets typically contain sensitive personal information, which need to be protected prior to open publication. PPGIS data have special characteristics that make them different from many other sources. As described by Brown and Kyttä (2014), PPGIS surveys typically employ spatial elements to locate behaviors, functions, perceptions, or evaluations. Common to these elements is that they are in the geographic extent of the respondent’s everyday life, thus capturing the context the respondents have the most knowledge about through their lived-in experiences. Often PPGIS dataset contain, in addition to other survey elements and spatial elements, also home locations. When attempting to open PPGIS datasets one of the key challenges relates to the anonymization of home locations. Hasanzadeh et al. (2020) developed a PPGIS data anonymization strategy comprising various anonymization methods to enable the opening of PPGIS data. Using the anonymization algorithm, the home locations of the test data were displaced from their original locations and K-anonymity procedure accomplished. Thus, a context sensitive spatial anonymization method to protect individual home locations was developed while maintaining their spatial resolution for mapping purposes. The study evaluated empirically the effects of data anonymization on PPGIS data quality. The results indicated that a satisfactory level of anonymization can be reached using this approach. The anonymization procedure was also published openly so that other users can benefit from it. Although the European data protection regulations were used as the legal guidelines when anonymizing practices were developed in this study, the findings are probably applicable in other legislative systems, when necessary, modifications are considered.

4.8 Analytical Capacity The analysis possibilities in-built to Maptionnaire corresponds mainly to the first analytical phase Explore in the three-phase framework of spatial PPGIS data analysis presented by Fagerholm et al. (2021). In this article methods applied to PPGIS

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data are represented as a framework of three analytical phases: Explore, Explain, and Predict/Model. These phases graduate from basic to advanced. The Explore phase defines the exploratory and descriptive character of the analysis method (De Smith et al., 2020). The analysis does not require high expertise and can be done by non-academics such as planners and stakeholders. The Explain phase aims to look more closely at observations than the Explore phase, to explain observations by further analysis. A wide variety of PPGIS data analysis methods, typically combining spatial and non-spatial PPGIS data with other geospatial data, are categorized within this phase. To perform the analysis, often expertise in analytical methods is demanded. In the Maptionnaire analysis tools the hot spot identification can be counted as analysis of spatial patterns falling under the Explain phase. Finally, the Predict/Model phase intends to generalize mapped attributes to other places and contexts, and to understand future realities. This phase typically requires advanced expertise to perform analyses that integrate multiple data sources to predict and model PPGIS data. Users interested in advanced data analysis, such as researchers, need to seek options outside the Maptionnaire platform in GIS and statistical programs. An example of such analysis include the typical integration of other geospatial data sources to better understand the PPGIS data (Explain phase). Hence, it means that the Maptionnaire survey data needs to be downloaded from the platform. This can be done as Excel spreadsheets or csv files. The data reading requires experience to understand how the survey contents translates to a database with all relevant metadata, including response times, zoom level and background map used for map markings etc. Noteworthy is also that data collected with online map-based surveys can also include qualitative descriptions in relation to mapped sites or in terms of non-­ spatial survey questions. Such data also requires analysis as a separate effort outside the Maptionnaire platform. Furthermore, the Maptionnaire analysis window does not assess spatial data quality, which all users should be cautious about. Before starting any analysis, collected PPGIS data should be cleaned by detecting, correcting, or removing inaccurate spatial records, and organized for the actual data analysis. Such data manipulation may include value (re)classification, data (re)ordering, data queries, and removal of outliers.

4.9 Visual Capacity Visualization of information has become an integral part of decision-making processes. Maptionnaire offers a specific analytical window where collected point, line or area-based mappings can be visualized and analyzed. These possibilities are helpful particularly for planners who have a need for fast and straightforward data analysis. Collected survey data can be visualized based on specific respondent characteristics or other attribute variables collected in the survey. For example, graphs and tables are generated automatically based on the survey results and data can be

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Fig. 4.1  Maptionnaire data analysis window with filtering options. (Image Maptionnaire tutorial https://support.maptionnaire.com/hc/en-­us/articles/360012677599-­Filtering-­map-­responses)

explored on maps without the need to download the data and transfer it to another software. Visual outputs, in the form of thematic maps, can be generated to examine the spatial patterns in the data (Fig. 4.1). Users can also change the visual appearance of the map markings and even download their own background map in case the default maps are not satisfactory. For mapped point locations, it is also possible to visualize the data in heatmap style, which allows users to observe hot spots in spatial pattern of map responses. Produced map views can also be exported as image files. The tools available for data inspection and exploration within the Maptionnaire platform itself are well documented with guiding text, images, and videos in the online tutorial (https://support.maptionnaire.com/hc/en-­us/categories/360002857940). In terms of visualization, it is also noteworthy to mention that a Maptionnaire survey offers possibilities to support communicative planning and interaction between the citizens through the functionality of showing the map responses of other participants to survey respondents. This is a way in which Maptionnaire can be considered as a digital tool that facilitates communication in planning (Staffans et al., 2020).

4.10 Openness In an ideal world, PPGIS software would be open source and free for all to use. When still developed at the university, the original version of Maptionnaire, back then called the SoftGIS, was published as open-source code, free to use. Mapita Oy developed this software further, first based directly on the initial open-source code. Later, several new versions were developed and published. The current version is the third total rewrite of the application’s source code after the spin-out from Aalto University.

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4.11 Accessibility Maptionnaire can be used both with desktop and mobile devices, and the respondent interface is designed with the priority of serving mobile device users. Maptionnaire is committed to providing an open and accessible engagement platform that is available to the widest possible audience. Maptionnaire fills all the requirements of A-level as well as AA-level of the Web Content Accessibility Guidelines (WCAG 2.1). Accessibility is a top priority for Maptionnaire and the company is striving to ensure that the platform follows the highest accessibility standards and best practices. This is done, for instance, by making sure that all questionnaire elements have been coded accordingly, and that screen readers and other assistive technology can help respondents in filling out questionnaires. Maptionnaire is one of the few digital services in Finland to fulfill all the accessibility requirements. The idea of free open-source software is clearly welcomed, and many great open-source products have been developed. The usability of many services is, nevertheless, often poor, and the most successful projects are the ones where the user and the developer are one and the same. This means that the wider and more substantive use of open-source services does not take place. This threatens the entire production model of these services because the economic model sustaining the software never materializes, the underlying power relationships collapse, and the resulting under-utilization of the service prevents fulfilling the promises. (Wubishet et al., 2013). Open source PPGIS have potentially similar challenges. It is probably realistic to assume that the majority of PPGIS users might be ‘passive users’ who merely use a system and take no part in its development. The main motivation of a typical participant is probably to express her/his opinions about topical urban planning issues or her/his personal experiences. What matters then are the user interface and continuity.

4.12 Brief Use Cases Maptionnaire has been used both in real life planning and development projects as well as in academic studies. Examples of both types of user cases can be found from Mapita’s web page (https://maptionnaire.com/customer-­stories) and in the web page of Participatory Mapping Institute (https://participatorymapping.org/), that is a global network of researchers and practitioners committed to moving beyond the state-of-the-art in public participation and participatory mapping systems. Below we present a few examples of case stories from both research projects and real-life public participation cases.

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4.12.1 Case Denver: Inclusive Participation in Community Planning In 2016, the city of Denver launched Denveright, a three-year-long citywide effort for land use, mobility, and parks and recreation. This project has led to fruitful cooperation between the city’s Community Planning and Development department and Maptionnaire as one goal for the project was to increase opportunities for participation with online methods. Organizing an inclusive and meaningful participation process was the priority for Denver. It was important for the city to find a way to reach a more diverse group of residents by offering the opportunity for people to give their input online at any time of the day. With Maptionnaire it was possible for respondents to place their comments directly on the map. This was particularly important because city plans always require the use of maps. Collecting geo-located information right from the start saves a considerable amount of time. Denver’s Community Planning and Development Department handles projects from citywide planning to permitting and licenses; essentially everything construction and development related. Noticing Maptionnaire’s flexibility, they began utilizing the service in all planning projects. Denver has used Maptionnaire e.g., in the neighborhood planning process in the East Planning Area (see Fig. 4.2).

Fig. 4.2  The Maptionnaire survey of the East Planning Area of Denver, which includes the neighborhoods on either side of Colfax Avenue between Colorado Boulevard and Yosemite Street

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Fig. 4.3  Routes marked by Helsinki walkability survey respondents regarding recreational walks (left) and utility walking (right)

4.12.2 Helsinki: Walkability of the City Center The city of Helsinki has set an ambitious aim to be the most functional city in the world. One core dimension of this vision is improving walkability in the city center. The walkability project was launched in 2018 with a workshop for designing the contents of the survey together with various stakeholders who co-designed a survey with questions about e.g., the everyday movements of pedestrians, people’s wishes for improvements, and the plans the city already had underway. The survey attracted 1600 respondents to mark over 8700 routes and places on the map (Fig. 4.3). 900 responses were related to routes that need improvement in people’s opinion. The planners found that as a positive surprise. Most suggestions were related to reducing car traffic in the city center and increasing the safety of crosswalks. The survey’s results will serve as the foundation for Helsinki’s walkability development program. So far, the results have been used as background information in a study about the possibilities of building an underground collector street, in a study on the enlargement of the pedestrian areas in the city center, as well as in the visioning work for the city center.

4.12.3 Case Turku: Outdoor Recreation in a Pandemic Situation This study aimed to understand how the residents in Turku, a middle-sized city in Finland, perceived their outdoor recreation changed and how nature contributed to their subjective well-being during the early phases of the COVID-19 (Fagerholm et al., 2021). Sites of outdoor recreation and associated ecosystem service benefits were gathered through Maptionnaire. The results show that nearly half of the respondents increased outdoor recreation and most outdoor recreation sites were visited more or as often as before the pandemic. The spatial analysis revealed that the most often visited recreation sites were near forests, semi-natural areas, and

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Fig. 4.4  Statistically significant clusters of outdoor recreation sites offering multiple (hot spots) and few (cold spots) ecosystem service benefits. Percentage denotes confidence level of clusters

housing areas as well as relatively close to the respondent’s residence. Outdoor recreation increased at sites offering multiple cultural ecosystem service benefits in Turku (Fig. 4.4). Respondents had various reasons for changes in outdoor recreation behavior. For some, a shift to working remotely and changes in everyday routines led to spending time outdoors more often and for some spending less, while others avoided recreation in crowded areas due to social distancing. The results also indicate that people’s opportunities to adapt to the pandemic conditions differ greatly. Nature’s contribution to subjective well-being during COVID-19 was important regardless of respondent’s outdoor recreation behavior.

4.13 Comments and Recommendations Maptionnaire provides a lot of different options both for a practitioner aiming to realize digital public participation and for a researcher interested in place-based research on people-environment relationship. The successfulness of the project depends more on the choice of mapping design and the data collection process rather than the tool itself. Current challenges in public participation processes are depending on the application of the various public participation tools in different phases of the process and how the produced knowledge is used in planning. According to Staffans et al. (2020) two different communicative actions can be distinguished in the public participation process: Large scale participation that produces a lot of information and represents various groups of people and more intensive collaboration in groups where new ideas, knowledge and solutions are created. Planning processes can be understood as flows of communicative actions, where the knowledge needs and modes of working go hand in hand, sometimes opening up the processes and sometimes closing down the processes. Opening up means diverging and creating new, representative

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knowledge while closing down means converging and assessing the value of generated knowledge and ideas and producing solutions. Maptionnaire is at its best as a participatory tool that can reach large groups of people and that provides new knowledge about diverse and often diverging groups of citizens. Knowledge production is often linked to the early phases of a planning process and evaluation phases. Other tools, e.g., co-creation workshops, that promote deeper collaboration and help converging knowledge to workable solutions are needed to complement the toolbox of a planner. There are good, online guidelines (https://participatory. tools/) that help to design the participatory process, select the suitable set of tools, and apply the methods in data collection and analysis. Currently, research is ongoing about the ways place-based knowledge produced with Maptionnaire really informs planning decisions. It is already evident that the way PPGIS data is stored, plays an important role. In the city of Lahti (Finland) PPGIS data is stored in the same geospatial database, which is used across all sectors in the city to provide data for planning processes (Grêt-Regamey et al., 2021). This database includes more than 200 layers of conventional GIS data (e.g., land use, transport networks) and several layers of PPGIS data, thus giving PPGIS data an equal visibility and role alongside the traditional geospatial data. The city encourages all sectors to actively use the database, not only the city planning department but also other sectors, like health, social, forest, sport, and educational departments. The integration of PPGIS data with other data sources creates conditions for the city officials to make decisions and plans based on understanding the values, needs and behavior of the citizens, and linking them closely with the characteristics of the physical environment and sociocultural context. The strong and profound participatory approach Lahti has taken in their planning processes has strengthened the social capital and empowered the local community to engage in the political process which in turn has resulted in zero complaints assigned by citizens to the latest master plan produced in Lahti in 2020. Maptionnaire is in constant development. Both practitioners and researchers would benefit from an even more effective and attractive dashboard where users could immediately visualize gathered data based on user groups and mapped attributes. One of the newest features is the 3D Collaboration extension. Piloting experiences have shown interest but also some usability challenges for mapping on a 3D map, with mobile devices or with a low-quality internet connection. A timely topic would also be developing Maptionnaire in a direction that respondents’ behavior could be monitored real time and that could produce information during a longer time period based on location tracking. Establishing long-term panel studies could also need careful consideration on how the different features of the software can interact to support the long-term engagement and retention of citizens in monitoring programs. By mimicking social media tools, real-time feedback, and the possibility to see and discuss what other citizens are mapping could increase the engagement and therefore the participation on the platform over time. New possibilities of visualization using virtual reality or optimizing the tool for decision theaters is another future challenge.

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Acknowledgements  The authors are thankful for the Editor’s comments to the earlier version of this article. The work of M.K. contributes to the FinEst Twins project funded by EU H2020 grant 856602 and the NORDGREEN project (Smart planning for healthy and green Nordic cities) funded by NordForsk and the contribution of N.F. was funded by the Academy of Finland [GreenPlace, grant number 321555].

References Ballatore, A., McClintock, W., Goldberg, G., & Kuhn, W. (2019). Towards a usability scale for participatory GIS.  In P.  Kyriakidis, D.  Hadjimitsis, D.  Skarlatos, & A.  Mansourian (Eds.), AGILE conference on geographical information science: Geospatial technologies for local and regional development (pp. 1–24). Springer. Broberg, A., Salminen, S., & Kyttä, M. (2013). Physical environmental characteristics promoting independent and active transport to children’s meaningful places. Applied Geography, 38, 43–52. Brown, G. (2012). An empirical evaluation of the spatial accuracy of public participation GIS (PPGIS) data. Applied Geography, 34, 289–294. Brown, G. (2017). A review of sampling effects and response bias in internet participatory mapping (PPGIS/PGIS/VGI). Transactions in GIS, 21(1), 39–56. Brown, G., & Hausner, V. H. (2017). An empirical analysis of cultural ecosystem values in coastal landscapes. Ocean & Coastal Management, 142, 49–60. Brown, G., & Kyttä, M. (2014). Key issues and research priorities for public participation GIS (PPGIS): A synthesis based on empirical research. Applied Geography, 46, 122–136. Brown, G., Donovan, S., Pullar, D., Pocewicz, A., Toohey, R., & Ballesteros-Lopez, R. (2014). An empirical evaluation of workshop versus survey PPGIS methods. Applied Geography, 48, 42–51. Brown, G., Pullar, D., & Hausner, V. H. (2016). An empirical evaluation of spatial value transfer methods for identifying cultural ecosystem services. Ecological Indicators, 69, 1–11. Brown, G., Strickland-Munro, J., Kobryn, H., & Moore, S.  A. (2017). Mixed methods participatory GIS: An evaluation of the validity of qualitative and quantitative mapping methods. Applied Geography, 79, 153–166. Brown, G., McAlpine, C., Rhodes, J., Lunney, D., Goldingay, R., Fielding, K., et  al. (2018). Assessing the validity of crowdsourced wildlife observations for conservation using public participatory mapping methods. Biological Conservation, 227, 141–151. Cox, C., Morse, W., Anderson, C., & Marzen, L. (2014). Applying public participation geographic information systems to wildlife management. Human Dimensions of Wildlife, 19(2), 200–214. De Smith, M. J., et al. (2020). Geospatial analysis (6th ed.). The Winchelsea Press. Available from: https://www.spatialanalysisonline.com/extractv6.pdf Egli, V., Villanueva, K., Donnellan, N., Mackay, L., Forsyth, E., Zinn, C., Kyttä, M., & Smith, M. (2020). Understanding children’s neighbourhood destinations: Presenting the kids-PoND framework. Children’s Geographies, 18(4), 420–434. Engen, S., et al. (2018). Assessing local acceptance of protected area management using public participation GIS (PPGIS). Journal for Nature Conservation, 43, 27–34. European Parliament and Council (1995). Directive 95/46/EC on the protection of individuals with regard to the processing of personal data and on the free movement of such data. Official Journal L, 281, 0031–0050. European Parliament and Council (2016). Regulation (EU) 2016/679 on the protection of natural persons with regard to the processing of personal data and on the free movement of such data. Official Journal L, 119, 1–88.

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Fagerholm, N., Torralba, M., Moreno, G., Girardello, M., Herzog, F., Aviron, S., et  al. (2019). Cross-site analysis of perceived ecosystem service benefits in multifunctional landscapes. Global Environmental Change, 56, 134–147. Fagerholm, N., Raymond, C. M., Olafsson, A. S., Brown, G., Rinne, T., Hasanzadeh, K., Broberg, A., & Kyttä, M. (2021). A methodological framework for analysis of participatory mapping data in research, planning, and management. International Journal of Geographical Information Science, 35, 1848–1875. Friedmann, J. (1992). Empowerment: The politics of alternative development. Blackwell. Gottwald, S., Laatikainen, T., & Kyttä, M. (2016). Exploring the usability of PPGIS among older adults: Challenges and opportunities. International Journal of Geographical Information Science, 30, 2321–2338. Grêt-Regamey, A., Switalski, M., Fagerholm, N., Korpilo, S., Juhola, S., Kyttä, M., Käyhkö, N., McPhearson, T., Nollert, M., Rinne, T., Soininen, N., Toivonen, T., Räsänen, A., Willberg, E., & Raymond, C. M. (2021). Harnessing sensing systems towards urban sustainability transformation. NPJ Urban Sustainability, 40, 1–9. Hasanzadeh, K., Kajosaari, A., Häggman, D., & Kyttä, M. (2020). A context sensitive approach to anonymizing public participation GIS data: From development to the assessment of anonymization effects on data quality. Computers, Environment and Urban Systems, 83, 101513. Kahila, M., & Kyttä, M. (2009). SoftGIS as a bridge builder in collaborative urban planning. In S. Geertman & J. Stillwell (Eds.), Planning support systems: Best practices and new methods (pp. 389–411). Springer. Kahila-Tani, M., Broberg, A., Kyttä, M., & Tyger, T. (2016). Let the citizens map – Public participation GIS as a planning support system in Helsinki 2050 master planning process. Planning Practice and Research, 31(2), 195–214. Kahila-Tani, M., Kyttä, M., & Geertman, S. (2019). Does mapping improve public participation? Exploring the pros and cons of using public participation GIS in urban planning practices. Landscape and Urban Planning, 186, 45–55. Kyttä, M., Kahila, M., & Broberg, A. (2011). Urban infill policy and the perceived quality of the environment. Urban Design International, 16(1), 19–35. Kyttä, M., Broberg, A., Haybatollahi, M., & Schmidt-Thomé, K. (2016). Urban happiness – Context-sensitive study of the social sustainability of urban settings. Environment and Planning B: Planning and Design, 43, 34–57. Kyttä, M., Broberg, A., Tzoulas, T., & Snabb, K. (2013). Towards contextually sensitive urban densification: location-based softGIS knowledge revealing perceived residential environmental quality. Landscape and Urban Planning, 113, 30–46. Kyttä, M., Oliver, M., Ikeda, E., Ahmadi, E., Omiya, I., & Laatikainen, T. (2018). Children as urbanites: Mapping the affordances and behavior settings of urban environments for Finnish and Japanese children. Children’s Geographies, 16(3), 319–332. Laatikainen, T., Tenkanen, H., Kyttä, M., & Toivonen, T. (2015). Comparing conventional and PPGIS approaches in measuring equality of access to urban aquatic environments. Landscape and Urban Planning, 144, 22–33. Laatikainen, T. E., Hasanzadeh, K., & Kyttä, M. (2018). Capturing exposure in environmental health research: Challenges and opportunities of different activity space models. International Journal of Health Geographics, 17(1), Article number 29. Mladenović, M. N., Kyttä, M., Forss, K., & Kahila-Tani, M. (2021). What could transport planning practice learn from public participation GIS method? In M. N. Mladenović et al. (Eds.), Transport in human scale cities (pp. 202–215). Edward Elgar. Muñoz, L., Hausner, V. H., Runge, C., Brown, G., & Daigle, R. (2020). Using crowdsourced spatial data from Flickr vs. PPGIS for understanding nature’s contribution to people in Southern Norway. People and Nature, 2(2), 437–449. Rambaldi, G., Chambers, R., McCall, M., & Fox, J. (2006). Practical ethics for PGIS practitioners, facilitators, technology intermediaries and researchers. Participatory Learning and Action, 54, 106–113. http://www.ppgis.net/the-­practice/good-­practice/

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Rzeszewski, M., & Kotus, J. (2019). Usability and usefulness of internet mapping platforms in participatory spatial planning. Applied Geography, 103, 56–69. Staffans, A., Kahila-Tani, M., & Kyttä, M. (2020). Participatory urban planning in the digital era. In S. Geertman & J. Stillwell (Eds.), Handbook of planning support science (pp. 307–321). Springer International Publishing. Van Dijk, J. (2017). Digital divide: Impact of access. In The international encyclopedia of media effects (pp. 1–11). Wiley. Wubishet, Z. S., Bygstad, B., & Tsiavos, P. (2013). A participation paradox: Seeking the missing link between free/open source software and participatory design. Journal of Advances in Information Technology, 4(4), 181–193.

Chapter 5

Sapelli

Megan Tarrant, Marcos Moreu, Hannah M. B. Gibbs, Muki Haklay, Jerome Lewis, Megan Laws, Artemis Skarlatidou, Fabien Moustard, and Simon Hoyte

Abstract  Sapelli is a group of open-source applications, aimed to be used within a wider socio-technical approach which means that the software is expected to be used within a social process that considers inclusivity, equity, and risks and benefits. The software enables people with no or limited literacy as well as limited technical literacy to collect, share and analyze spatial data. Sapelli operates within the framework of an “Extreme Citizen Science” (ECS) methodology, based on co-creation and participatory design. This approach puts communities at the center of the project design process, enabling them to identify challenges they wish to address, what data to collect and how, and what analyses are required to address the challenges they have identified. The process relies on the consent and participation of participants, who shape the form and direction that the project takes. Keywords  Citizen science · Indigenous peoples · Participatory design · Open-­source · Data collection

5.1 General Information Name of Application: Sapelli Collector, Sapelli Designer, Sapelli Viewer, GeoKey, Community Maps M. Tarrant Department of Geography, University College London, London, UK Leverhulme Centre for Anthropocene Biodiversity, University of York, London, UK e-mail: [email protected]; [email protected] M. Moreu · H. M. B. Gibbs · M. Haklay (*) · M. Laws · A. Skarlatidou · F. Moustard Department of Geography, University College London, London, UK e-mail: [email protected]; [email protected]; [email protected]; [email protected]; [email protected]; [email protected] J. Lewis · S. Hoyte Department of Anthropology, University College London, London, UK e-mail: [email protected]; [email protected] © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 C. M. Burnett (ed.), Evaluating Participatory Mapping Software, https://doi.org/10.1007/978-3-031-19594-5_5

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Names of Developers: Matthias Stevens, Michalis Vitos, Julia Altenbuchner, Oliver Roick, Julius Osokinas, Joe Woodhouse and Contributions from the Open-­ Source Community Name of Funder: UK’s Engineering and Physical Sciences Research Council (EPSRC), European Research Council (ERC), European Union Horizon 2020 program Type of System Software: Android (Sapelli Collector, Sapelli Viewer), Microsoft Windows (Sapelli Designer) Type of Programming Language: Sapelli Collector (Android), Sapelli Designer (HTML/CSS/Javascript/React.JS), Sapelli Viewer (HTML/Javascript/StencilJS/ Capacitor), GeoKey (Python) API Availability: GeoKey REST API https://geokey.org.uk/developers/ Features: Icon-based data collection, map-based visualization, decision-tree filtering, Cost: Free Type of Data Collected (Geographic and Descriptive): Geographic with attribute data Overview: Sapelli translates local knowledge into datasets that can be visualized and analyzed through maps. It comprises of a unique ecosystem of tools, which include Sapelli Designer, Sapelli, Collector, and Sapelli Viewer. Figure  5.1

Fig. 5.1  The Sapelli ecosystem (February 2022)

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shows the current Sapelli ecosystem. At the bottom, the tools for creating a Sapelli project, which is uploaded to Sapelli Collector, which is connected to Community Maps (through GeoKey) and Sapelli Viewer, where the data can be visualized.

5.1.1 Sapelli Designer Sapelli Designer is the application that is used to create Sapelli project files. In most cases it will be used by administrators or, where technical ability is particularly limited, the professional researcher may be required to assist in creating the project files, sometimes referred to as a chauffeur in the literature. Prior to the creation of Sapelli Designer, all Sapelli projects were created using XML code and required a high degree of technical literacy. Projects then had to be finalized using Sapelli Packager to turn them into a usable format. Designer removes the requirement for the administrators to use XML and it has incorporated Packager so that the project is finalized automatically. Using Designer requires an understanding of how to design a project. Tutorials have been developed to assist administrators with this (see below). Participants are not expected to use Sapelli Designer and they are unlikely to need to use it.

5.1.2 Sapelli Collector Sapelli Collector is used to run Sapelli project files to collect data. Currently, to use Collector, administrators need to be able to read English. If they are not using Sapelli Viewer alongside Collector, they will also need to be able to understand .csv files to analyze the collected data. Participants need to be able load projects into smartphones by finding the projects in folders and uploading them. Data is collected by tapping on a series of icons, so users are not required to understand English. If they are not working with Viewer, which reads the data automatically, they are also required to be able export data manually. Training is provided to collectors to facilitate this, and the application is designed to be as user-friendly as possible for groups with low literacy.

5.1.3 Sapelli Viewer Sapelli Viewer has two modes, one for administrators and the other for participants. Sapelli Viewer opens with a screen that enables the user to select which of these personas they belong to. The mode for participants is most prominent, which enables

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participants to access the data they have collected directly. The administrator mode (Configuration screen, see Fig. 5.2 below) is more hidden (currently it is accessed by tapping the ExCiteS logo multiple times), which lowers the risk of participants accidentally finding themselves with access to the back-end settings of the app. The mode for administrators is used to configure settings for the app. This enables users to view their collected data on different base maps, change icons for the user interface and set up accounts for individual participants. This mode requires some basic digital literacy and English literacy. For participants, the use of Sapelli Viewer does not require any technical ability beyond opening the app and navigating the map. Sapelli Viewer is designed to enable them to view and validate the data they have collected, and to explore the data analytically, for example by looking at groupings of data based on when they were collected.

Fig. 5.2  The Sapelli Viewer screen opens to show the available projects. Tapping the ExCiteS icon in the top left takes the administrator to the admin code screen. When the admin code is entered correctly, the administrator has access to a range of settings for customizing the Sapelli viewer and creating user profiles

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5.2 Ethics Any participatory mapping project raises a range of ethical concerns. Such projects have the potential to raise expectations; extract information for the benefit of outsiders or for use against local people; to expose communities to danger or to raise tensions within a community (Brofeldt et al., 2018; Theilade et al. 2021; Chambers, 2006). The introduction of technological solutions, particularly in contexts where communities have limited prior knowledge of digital technology and the risks related to its use, can potentially exacerbate these issues. In the context of the Sapelli ecosystem, the major ethical concerns relate to the relationship that is built with participating communities, the potential consequences of data collection and the ethics surrounding data ownership. This section discusses these concerns in the context of Sapelli and the methods through which such concerns are mitigated.

5.2.1 Free, Prior and Informed Consent The Free, Prior and Informed Consent (FPIC) process is central to the realization of a Sapelli project. The process must recognize that the impacts of a Sapelli project may be positive and negative. As a result, it must be understood by the community before consent to proceed with a project can be sought. The methods of carrying out the FPIC process, and the definition of consent itself, vary according to what is most appropriate in each context. In Central Africa, for example, consent is socially constructed through ongoing negotiations which center on mutual satisfaction and can be broken if either party ceases to respect their obligations (Lewis, 2012a). In some situations, we have encountered, the process may take the form of a series of formal meetings, in others it may be more suitable to arrange informal meetings which take place over several days (Moustard et al., 2021). The outcome of these meetings can also vary. Whereas some communities may be comfortable with written contracts, in contexts where community members may be non-literate, alternative methods of documenting consent, such as sharing a feast together, can be used instead. These methods include photographs, video, and other paper methods. Consent, once granted, is not immutable and can be withdrawn by the community at any time. As communities own the data they have contributed, they have the right to request that any data is deleted, and the project facilitators must uphold this request. “Free” relates to the imperative that communities feel able to consent or refuse to participate in a project, without duress, before it commences and to negotiate the terms of their involvement. “Prior” refers to the fact that communities must be made aware of all relevant information before the process begins and the FPIC negotiation must occur before any possible consequences of the project could impact the community. “Informed” requires ensuring that all participants and stakeholders have received and thoroughly understood all the information given. This requires

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ensuring that information is created and disseminated appropriately, accounting for linguistic differences, different literacy levels and cultural understandings (Lewis et al., 2008; Lewis & Nkuintchu, 2012). In the context of conflict within the community over whether to consent, researchers should not push further, but leave with an open invitation to the community to contact us again should they have resolved their disagreements. In contexts where IPLCs may be non-literate, it is still vital that the FPIC process is synthesized in a form that thoroughly registers all the outputs of the negotiated points. In particular, the steps taken to mitigate risks, the roles and responsibilities of participants, questions concerning remuneration or other forms of support to those collecting data, data access and permissions, all require clear articulation and agreement. Although this is necessarily a document—formalized in the “Community Protocol”—it becomes a reference point for the cooperation between the community and the researchers. If necessary or appropriate, it can also be used to explain the work to local authorities. This document is updated throughout the project, or in some cases, adjusted, as different types of information come to light. For the most part, outcomes such as withdrawal of consent are avoided through paying careful attention to ensuring that the FPIC process is carried out effectively. When the community is fully informed, understands the potential risk and benefits and has created a plan for mitigation against negative outcomes it is much more likely that the project will be successful.

5.2.2 Expensive Technology Among Marginalized Communities The use and sharing of mobile technology among minoritized communities for the purposes of research or conservation often increases the presence of expensive technology in the community. Despite a global acknowledgement of the mobile revolution, Indigenous Peoples have not participated to the same extent. For many Indigenous communities, this revolution has resulted in a transformation from no access to information and communication technological (ICT) tools to access to mobile ICT tools (Donner, 2008). Described as a “leapfrog” phenomenon, in some communities exposed to this digital divide, a generation missed access to this fixed technology (Castells et  al., 2009). Appropriate practices should be established to ensure that the introduction of mobile technology is done in a culturally appropriate way, and where appropriate, mobile devices are left for other uses by the community at the end of the research process.

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5.2.3 When Mapping Becomes Transactional or Monetized Maps have nuanced and complex histories, shape action, and “convert social energy into social space” (Wood, 2010: 6). Maps are subjective and it is necessary to acknowledge that “what we know about the spatiality of the world may be a consequence of the meanings we give to maps while interacting with them, rather than an expression of a fixed cartographic reality” (Gillings et al., 2018: 15). Maps typically reflect two distinct parties, the map maker, and the map user. Expanding the audience to include and mix these two groups in a community-based mapping approach exposes the decisions made before and during map making and challenges the hegemony of map makers on the map making process. Digital mapping with Indigenous communities is sometimes criticized as a backdrop to showcase innovation and a method of extracting data. When mapping becomes transactional or monetized, there may be an increase in “strategic” mapping, where locations connected to desired future use and associated with a perceived increase in transaction or monetization, may be identified and mapped more strongly (Ramirez-Gomez et al., 2013). This may expose communities to danger or raise tensions in the community. Non-involved community members may resent those receiving money for their role in contributing data. Mapping commercially valuable resources may result in them being identified more easily by those seeking to exploit them. The ethical responsibility of researchers who use Sapelli is to ensure that tangible and intangible values are comprehended, appropriately protected from abuse or leakage, and realized through an approach which anticipates these threats and works in co-collaboration with Indigenous communities to develop mitigation strategies that secure continued access to resources, and non-conflicting strategies for data recording.

5.3 Cost One of the goals of Sapelli is to make it as open and accessible to as wide a range of users as possible. The mobile (Collector, Viewer) and desktop-based (Designer, GeoKey) applications are thus offered for free.

5.3.1 Indirect Costs There are indirect costs since much of this technology was lacking the investment in making it ready for mass-scale deployment. Therefore, there is a need to consider costs that are associated in learning how to utilize the different parts: setting up the XML for a Sapelli project; using GeoKey; and having trouble-shooting support when needed, etc. There are also costs associated with setting up a cloud server and

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installing the system on it. Finally, because the process requires a significant element of engagement with the community, there is a need to travel and spend time to carry out the process well. 5.3.1.1 Hardware While offering the software for free is a good first step in making Sapelli available to all, there are indirect costs associated with setting up and using Sapelli, which are potential barriers to use. The software requires a mobile device such as a smartphone, tablet, or laptop computer. In the case of smartphones and tablets, these devices need to have Global navigation satellite system (GNSS) connectivity, and the more up-to-date version of Android, the less likely it is the device will encounter issues running the software. Electricity supply needs to be assured through solar and batteries where infrastructure is non-existent or unreliable. This creates an upfront cost, particularly if users do not currently own or have access to this technology. 5.3.1.2 Internet The software has various capacities for online and offline use, with varying cost implications depending on the need for Wi-Fi or mobile data. Internet access in rural areas in developing countries is increasing year on year International Telecommunication Union (ITU), 2021). However, the ability to make use of this access must be considered when setting up a Sapelli project. Loading online maps or satellite imagery map tiles, and transmitting data requires internet connection and this can quickly become expensive when attempted using mobile data. Some workarounds exist. For instance: base satellite maps can be preloaded when the devices have good and free internet connection; manually removing memory cards from the phone to download results or large media files where connection is poor; phones can automatically discover when they are in cellular and send the most important or time-sensitive information as text messages to a dedicated phone connected to the internet that can relay the data further (see Fig. 5.3). This SMS functionality was used in the past but currently this functionality has been (temporarily or permanently) disabled in the latest release due to issues with Google Play Store audits. 5.3.1.3 Application Costs Sapelli Designer, Collector, and Viewer are all available for free via the Sapelli.org website or our GitHub repository. All of the apps have the capability to be used offline, once they have been downloaded, which reduces the cost of the internet or data connection required. Projects created in Designer can be uploaded to Collector

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Fig. 5.3  Sapelli data export (bottom-left) and transmission process using SMS and/or internet connectivity

without the need for an internet connection if a cabled or Bluetooth connection is available. Data can also be transferred between Collector and a repository, or vice versa, via a cable or internet connection depending on what is available. Viewer can access any data stored locally on the phone. However, if Viewer is to be used offline the necessary map tiles must be downloaded and installed prior to use. 5.3.1.4 Geokey/Community Maps (Desktop) Geokey is an open-source platform that was developed to provide server-side components to run participatory mapping projects. GeoKey provides a database-driven backend storage and the structure of the database can be defined by a web-based administration tool enabling users to easily set up and manage bespoke community mapping projects (Haklay, 2016). Community Maps is a front-end application that supports the visualizations of information in a way that supports participatory action via a simple, user- and mobile-friendly, map-based interface and is built on top of GeoKey (Ellul et al., 2009). Use of Community Maps is not free.

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5.3.2 Implications and Maintenance The software is maintained only where research funding allows it. This means that there are cost implications to addressing any bugs that appear and to maintain the software. This also results in constraints on how much can be maintained and updated at any given time. In an ideal situation the Extreme Citizen Science Research Group (UCL ExCiteS) seeks to ensure that funding and support be available for communities to continue with their research after the initial ExCiteS involvement has come to an end. This has proved difficult in many situations for several reasons: the deterioration of equipment, the withdrawal of outside partners or funders, major events that prevent visits (natural disasters, pandemic etc). Where it has worked best is in the context of long-term conservation initiatives and in the context of commercial companies with long term vested interests in maintaining good relations with the communities inhabiting their areas of influence. The researchers that carry out the community protocol are seen as custodians of the relationships with the communities and as the contact point in case further access is needed.

5.4 Technical Level Sapelli is designed to circumvent language or literacy barriers to facilitate data collection. It has been developed to be used in contexts beyond those typical of conventional western citizen science to enable people with no or limited literacy to use smartphones and tablets to collect, share, and analyze data (Lewis, 2007, 2012b). The technical ability required to use Sapelli depends on which specific application is being used, and who is using it. Broadly speaking there are two user personas involved in a Sapelli project. The first group “Administrators” are those who will be responsible for using the Sapelli software to create the project files (.sap files). The administrators require medium-to-high levels of literacy and technical computer skills. They work with the participants to collect, visualize, and analyze data. The technical ability required varies depending on which piece of software is being used. The second group “Participants” are those who will use the project to collect data. These groups are not mutually exclusive, it is possible to undertake both roles within the project. It is also important to note that these groups should both be equally engaged in decisions about what data to collect. Alongside these user groups, the role of the professional researcher is to support the community to co-­design and co-create the data collection project. They will undertake this by translating the user’s data needs into Sap. files based on the broader socio-cultural and environmental problem definition and local knowledge provided by participants.

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5.4.1 Tutorials User tutorials were initially created to guide administrators through the process of setting up a Sapelli project using XML code. These tutorials are hosted on the Sapelli.org website and are predominantly intended for people with a high level of digital literacy to support users in lower-literacy contexts. While this method offered a useful way of understanding how a project was constructed, where to look for errors, and how to troubleshoot issues, the process itself bears very little resemblance to a finished Sapelli project and thus requires a large amount of learning and an increase in digital literacy for most administrators. In designing the tutorials, the overall need and parameters were first defined. The need was identified as training materials that can be delivered and accessed remotely. The parameters were set by the constraints of working through local assistants at the time. Local assistants constitute a broad group. As a first step it was identified that most local assistants with whom the group work has access to an internet connection, albeit not necessarily a strong and consistent one. Local assistants also must have access to, and the ability to use, a mobile device and an internet browser. Recognising that people learn in different ways, it was therefore decided to develop the tutorials as both a text and video guide consisting of short videos complemented by written instructions which take the user through the steps required to set up a Sapelli project. The videos were designed to be as short as possible to ensure they would not require too much mobile data to download and view. They were also designed to work visually on both desktop and mobile devices. The sections are navigable and categorized to assist the users to self-direct their learning. A final aim was to make the participants feel as though they had a professional researcher sitting next to them, talking them through the process. Currently, these tutorials are shared on the Sapelli website (http://www.sapelli.org/).

5.5 Inclusiveness The Sapelli software, and the socio-technical process it is situated within, have been designed to extend participation in Citizen Science to groups and communities who have traditionally been disenfranchised from such research. The Sapelli apps, as standalone pieces of software, are not capable of creating inclusiveness themselves nor are they intended to do so. It is only when the software is used within the socio-­ technical process that inclusivity can begin to be achieved. Even then, the issues of inclusiveness to which Sapelli is best placed to respond relate to collaborative research rather than traditional accessibility issues. The Sapelli apps have been built to respond to community needs and, while accessibility features have not been built in ab initio, the apps have been shown to enable the engagement of a wide range of community members in the data collection process. As such, understanding who the

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stakeholders are and who is represented in the community is a vital step of any Sapelli project (Skarlatidou et al. 2019a). This section explores the elements of the Sapelli software and the accompanying methodology that have been built to increase inclusiveness in the research design and data collection process. The way that the software is used opens the possibility of including people with little or no literacy, and people with very little experience with using mobile phone technology to participate in data collection and analysis processes. This potential can be fully realized through the methods that are described in this chapter.

5.5.1 Co-design Process Sapelli projects are co-designed as part of on-going discussions with a community (Skarlatidou et al. 2019b). The design process begins by discussing with the community what issues they have identified in their local area. For example, if the mapping activity is linked to the protection of community resources in the context of imminent logging activities, the discussion often focuses on those resources most vulnerable to damage or removal and their value to the community. The organization and nature of the logging, the company’s timetable, and likely areas of activity, in addition to the resources and things that need to be protected. Whatever issues are raised are then discussed with the whole community to identify what might be possible to address using the ExCiteS approach. The community and the external researcher then explore together what aspects of the issues may present problems. Over the course of several meetings these problems are expanded upon until a consensus is reached. In some cases, information is obtained from relevant experts, including from the stakeholders identified through the stakeholder mapping process: in the example above, the social team of the logging company for instance. Following these discussions, the community begins to develop the decision tree that forms the basis of the Sapelli project. Throughout the design process, the users and their requirements remain at the forefront of the project design process. Undertaking the decision tree and icon design in a participatory manner enables communities to co-create a bespoke data collection project that appropriately addresses the issues they have raised using their ontological categories and understandings. In collaboration with the professional researcher, the community participants define the data points (indicators) that are required for documenting the issues that the community have identified. In situations where communities rely on outside agencies, for example for law enforcement or because the community wishes them to act on the data that are collected, then these outside agencies must also be present and participate in the discussions to ensure that the data the community collects can be used as evidence (e.g., size of tree stump when monitoring illegal felling). The next step in the project is to design the icons that will be used in the digital decision tree. This often starts with making drawings on the ground, or on pieces of paper. In some cases, photographs are taken and then digitally transformed into

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icons using graphics software. This latter example is undertaken by the researcher with the community’s input throughout. Before the icons become part of the project interface, they are tested with the community. The professional researcher will hold up the images and ask the community to identify what the image means. In cases where the image provokes a range of responses, the designs are edited and tested again. Once all the responses are consistent, the images are used in the creation of the Sapelli Designer project. (Fryer-Moreira & Lewis, 2021). Testing the icons with the community ensures that the icons are not likely to be misread by users who are collecting data in the field. In addition, the community has seen all the possible icons and can raise questions where they feel icons are missing or misunderstood.

5.5.2 Sapelli Designer and Collector There are a range of features built into Sapelli Designer and Sapelli Collector which assist in the creation of projects that make the data collection process inclusive and accessible for a wide range of people. Firstly, the use of icons reduces what could be a complex text-based decision tree into a simple icon-based tree. This bridges language and literacy barriers and, through the icon testing process, ensures most community members can understand the icons that are used to the extent that they can collect data. When designing a Sapelli project there is the option to add audio recordings to accompany each icon in the decision tree. Recordings can be made in the local language to identify each icon, and these are played back automatically when a participant visits the screen on which the icons are located. This use of audio complements the visual icons to make the data collection process more understandable.

5.5.3 Viewer Sapelli Viewer allows users to view and analyze the data they collect using Sapelli Collector, according to their needs, desires, and abilities. The software realizes an important step towards making data visualization and analysis accessible and inclusive, and placing the control of their data in the hands of the communities who have collected it. Sapelli Viewer supports two user personas, described in Sect. 5.4 on Technical Level (pg. 102): “Participants” and “Administrators”. Both user types can view the data they collect with Sapelli Collector as individual points on the map, or clustered points when the data are viewed at different scales (see Fig. 5.4). By default, the users can view all the data that they have collected within the project, so long as there are no privacy and security issues that restrict this functionality.

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Fig. 5.4  Data viewed as individual points on the map when zoomed in (left) vs clustered points when zoomed out (right). Note that the data displayed is not real data

5.6 Data Accuracy In Sapelli Collector, while the device’s chip set is receiving the signal from one or multiple Global Navigation Satellite System (GNSS) and the mobile network (if available) to record the coordinate information, the participant needs to describe their location. In this section, both spatial and semantics aspects related to accuracy of information are briefly addressed. In terms of spatial accuracy, this depends, among other factors, on the GNSS receiver mounted in the smartphone used, and the location (e.g. is the device under tree cover? Is there a mast nearby?). In order to “control” the inaccuracy, Sapelli allows to set a Maximum Accuracy Radius parameter to prevent the recording of coordinate information when accuracy is less than the specified value (the radius). For example, if the user is under a dense tree canopy without masts nearby and the

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max Accuracy Radius parameter is set to 30 m, but the device’s estimated accuracy is, e.g., 100  m, then Sapelli will keep searching for the location for a specified period of time. Once timed out, Sapelli can either stop searching for the location or record the less-inaccurate location, depending on the settings (see: http://www. sapelli.org/sapelli_element/location-­attributes/). As Goodchild and Li (2012) point out, any location information is recorded in an imperfect way, even when professional surveying equipment is used. Accuracy and precision expectations must be managed accordingly, and considerations should be made around for whom, and for what reasons, accuracy and precision are required (McCall, 2006). Contributions can be deleted or edited directly in Community Maps or in a Desktop GIS, where needed. In terms of map semantics, Sapelli Collector allows the user to describe a geometry (i.e., attach attribute information to a location) using pictograms, text, audio recording and/or photos. As with the spatial component of the data, where perfect accuracy is an illusion, aiming to perfectly capture and transmit knowledge about reality over space and time is also an illusion. The perception of reality and the knowledge about the location of the person who describes it needs to be converted or reduced to bits and bytes of information to be stored and shared using digital information technology. Aiming to somehow address (or acknowledge) the limitation of ICTs and the paradigm of technological information (Borgmann, 1999), the interface for describing a geometry in Sapelli is co-­ created with the community – at least, this way, the map legend is created by those who hold the situated, local, and place-based knowledge (Rambaldi, 2005). The community, with its rich contextual understanding and local knowledge, is best placed to decide what information needs to be collected, and how this information can be represented in a pictorial interface. Figure  5.5 shows an example of the

Fig. 5.5  On the left, Sapelli participatory design process – setting pictograms and groups. On the right, an example of a digitally created decision tree for recording community assets

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Fig. 5.6  Examples of the initial screen of Sapelli projects for: Illegal logging in Congo (top left), illegal poaching in Cameroon, resource management in Ethiopia, plant distribution mapping in Kenya, farming in Nigeria and animal monitoring in Namibia (bottom right)

Sapelli participatory design process for setting pictograms and groups and the resulting software decision tree for recording community assets. Below, Fig. 5.6, shows examples of the initial screen of multiple Sapelli projects co-designed in various locations with hunter-gatherers, farming, pastoralists, and agro-pastoralist communities.

5.7 Data Privacy This section briefly outlines data privacy considerations. For further information on this topic as it relates to Sapelli please see Moustard et al., 2021. The approach taken towards data sovereignty in Sapelli projects recognises, as described in Sect. 5.7, the potential negative impacts of data extraction and the subsequent misuse of information collected by indigenous peoples or local communities, particularly in white settler society contexts such as New Zealand, Australia, and North America (Kukutai & Taylor, 2016; Lovett et al., 2019). Thus, it is important to ensure that participants

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from Indigenous groups and other local communities retain full control of the data they collect. In contexts where the participants have little or no knowledge about the way data can travel and be used inappropriately, this is made more complex. In such contexts the significance of working with a trusted gatekeeper is vital. During the discussions to develop the Community Protocol (CP), the community is supported by their trusted gatekeepers and the facilitators to plan the most effective ways of using the data to achieve community objectives. Since data is often shared with outsiders, this is clearly discussed and the acceptable organizations, individuals, and modalities for doing so are noted down in the CP, as well as which types of data can be shared (see Sect. 5.2: Ethics, pg. 97). The community will often nominate a trusted gatekeeper to keep them informed about how their data are being used if they cannot verify this themselves (e.g., in the context of wildlife law enforcement). In cases where new actors request access to the data, the trusted gatekeeper or other person acceptable to the community asks permission for the new use or change of use. Only if the community gives consent will the data be used in these new ways. The GeoKey server where the data are stored was designed to facilitate this level of control and protection (see https:// geokey.org.uk/help/getting-­started-­with-­oauth.html#oauth-­grant-­types), but there are several issues that need to be considered. While the encryption of an individual record is not yet possible, the database that stores the information is set on an encrypted drive and uses a whole database encryption. Finally, a password is used to protect the GeoKey server that is linked to the Sapelli project, and only authorized users can access the data, either directly in the GeoKey UI or through Community Maps. In cases where the data is only used in the field and where data is extracted from the mobile phones in the form of files, data can be managed by the field team. In addition, in recent case studies we have explored how the use of messaging apps as the back-end technology for sharing geographic data can simplify the technical development, maintenance and implementation, and especially the concept of data ownership. Only those in the (e.g. WhatsApp) group have access to the (end-­ to-­end encrypted) data and communities can manage who gets in and out, thus reducing or eliminating the need of outsiders to manage the data. Data management and advanced GIS analysis requires time and resources, such as a desktop computer, to acquire technical knowledge. This is likely to be less relevant than the landrelated knowledge that technology is meant to unlock and protect. Thus, a system that is responsive to the local context and allows to add technical complexity incrementally based on resources available offer some advantages as well as disadvantages. Preliminary results show that, in some contexts, linking mapping to messaging (which, unlike mapping, is increasingly becoming ubiquitous) offers key advantages at the initial stages of participatory mapping projects.

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5.8 Analytical Capacity This section introduces first some background information related to understanding maps and mapping, before describing the analytical capabilities of Sapelli Viewer and Community Maps. Our research in the past years has shown that non-literate people do understand maps of their environment with little or no guidance, especially very high-­resolution aerial, or satellite imagery with key landmarks such as villages, junctions, trees, rivers etc. (Altenbuchner, 2018). On the other hand, research has also shown that when the technology does not allow the participants to visualize the data points they have collected in a map, this leads to a lack of understanding of the concept of maps and mapping and often to a lack of engagement (Moustard et  al., 2021). Viewer was developed to address this. Because it was developed some years after the Sapelli Collector, there is strong evidence for the importance of data visualization to enable participants to validate and analyze the data collected, begin to formulate an answer to their research questions, and decide how to act upon it. Furthermore, in contexts where participants have never interacted with a map before, the exploration of aerial or satellite imagery-based digital maps before starting the GNSS-based data collection process can help participants to create their own understanding and mental models of a mapping process before mapping their land. In terms of map orientation and understanding, little or no support is provided during the learning process and learning by exploration is prioritized. However, when it comes to basic analysis of the data, the analysis related functionalities in Sapelli Viewer require some training (Skarlatidou et al., forthcoming). GIS analysis concepts are less intuitive for lay people and these functionalities are introduced incrementally. Figure 5.7 shows the basic analysis capabilities of Sapelli Viewer, which include basic and advanced filtering by attributes and/or dates. On the left, when in “basic mode”, the user can select one or multiple icons and then apply or

Fig. 5.7  Sapelli Viewer interfaces for basic and advanced filtering by attribute and date

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Fig. 5.8  Screenshot showing the sign in window of the QGIS plugin for importing data from GeoKey to QGIS

cancel the filter. Basic date filtering allows the user to filter geometries using three-­ time frames: last day, last month and last season, which is very context specific and for this reason this can be customized using the administrative user screen. On the right side of Fig.  5.7, advance filtering by date allows the user to specify a date range, and the advanced mode of attribute filtering allows the user to apply a filter following the hierarchical decision tree structure of the Sapelli project used to collect data with Sapelli Collector. Similarly, data can be exported and used in other systems. For example, Mapping for Change’s Community Maps allows some basic GIS analysis operations such as filtering by attribute using check boxes or the bar, filtering by date, editing, commenting, and deleting contributions or attaching media files to specific contributions. For advanced GIS analysis and data management, a QGIS plugin was developed by Ibrahim Alhadidi to connect GeoKey with QGIS to allow editing, updating, and exporting data using QGIS (see Fig. 5.8).

5.9 Visualization Capacity Analysis and visualization are especially interconnected. In the previous section, some background information about map understanding has been introduced to explain the analysis capabilities of Sapelli. Here, some technical and design aspects related to visualization in Sapelli are provided. At the end, some research questions and future work related to analysis and visualization are outlined. The data collected with Sapelli Collector is visualized in Sapelli Viewer and can also be visualized in Community Maps, which is connected to the GeoKey server (see Fig. 5.3). Sapelli Viewer pulls the data from the local storage of the device;

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thus, the data can be visualized regardless of internet connectivity, but the map tiles (basemap) needed to provide context to understand the collected data must be uploaded into the device previously. Note that the number of map tiles (e.g., Mapbox Satellite) that can be stored in a mobile device is limited, which means that map exploration of large areas is only possible when online. Whilst internet access in rural areas in developing countries is increasing (International Telecommunication Union (ITU), 2021), a relatively high speed of transmission to load online maps or satellite imagery is a requirement to prevent serious usability issues when panning and zooming or exploring the map. The data points are clustered based on location and once unclustered the markers show the icons of the principal attribute of the geometry. When the user selects one contribution, the attribute information is displayed, and this can include the pictograms used to describe a geometry and the media files (audio and photo) attached to such geometry. Figure 5.9 shows the initial interface of Sapelli Viewer and the menu for viewing/listening to the attribute information. As of 2022, Sapelli Viewer allows the user to visualize the data collected with Sapelli Collector, but not to edit or delete contributions. In future versions, Sapelli

Fig. 5.9  Sapelli Viewer interfaces. Tapping on a data point (left) opens the attribute menu (right) which shows all the attribute data of that point. Note that the data displayed is not real data

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Viewer and Collector might be combined into one app which will allow the user to edit or delete contributions from the local storage and from a remote server. Adding the functionality of allowing users to visualize and edit the data shared by others (i.e., data transmitted to the GeoKey server) raises questions such as: Who can delete/edit a contribution? Only the contributor? Or any member of the community? Are edits anonymous? What happens when the data is deleted? Is there a back-up? Who manages this back-up? These are just a few of the questions that must be addressed before implementing this functionality, which has not yet been developed. It is important to note that, unlike in web maps where few experienced users are responsible for managing the data using mainly PCs, Sapelli Viewer aims to allow less experienced users to edit the community map using mobile devices. Another functionality that has been prototyped and tested in a Sapelli Progressive Web App prototype, but has not yet been integrated in Sapelli Viewer, is satellite imagery-based mapping. This allows the participant to map the land not only when on-site using GNSS points, but also when off-site using lines and polygons. Location information is limited in some contexts and information about area and “boundaries” can be valuable. For example, to provide information about farm size or information about (fuzzy) boundaries of grazing or hunting areas. The volume of freely available high spatial and temporal resolution Earth Observation (EO) data is increasing exponentially, and this will increase not only the quality of the basemaps used to provide contextual information to the collected data in visualization tools (Altenbuchner, 2018), but also to visualize land cover and land use (LCLU) changes. The impacts of human impacts on the Earth’s surface can now be visualized and monitored from above, sometimes in near-real time, as never before. The positive impacts of emerging synergies between citizen science and Digital Earth are widely acknowledged (Brovelli et  al., 2020). However, it is worth reiterating that the democratization of access to EO data is not a reality. Monitoring small LCLU changes at near-real time using manual image interpretation methods requires access to recent very high spatial resolution imagery (pixel size less than 1  m2). However, such imagery is currently not freely available, especially in non-urban areas in developing countries.

5.10 Openness Sapelli and GeoKey are open-source software licensed under the Apache License, Version 2.0 (http://www.apache.org/licenses/LICENSE-­2.0). • • • •

Sapelli Collector source code: https://github.com/ExCiteS/Sapelli GeoKey source code: https://github.com/ExCiteS/geokey Sapelli Viewer source code: Available soon Sapelli Designer source code: Available soon

The GeoKey website (https://geokey.org.uk/developers/) provides the necessary information to deploy GeoKey in a server, extend it or build an app on top of the

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Fig. 5.10  GeoKey, a back-end infrastructure for participatory mapping

API. As shown in Fig. 5.10, GeoKey does not provide client-side applications to collect, manage, visualize, and analyze geographic data. Instead, GeoKey provides the server-side components to set up participatory mapping projects and manage access to data that has been collected with other native or web applications built on top of the REST API, Sapelli Collector being one of them (Roick et al. 2016). In terms of exporting the data for advanced GIS analysis or for other purposes (e.g., back-ups), Sapelli Collector allows exporting the data stored locally in CSV and XML formats, as shown in Figs. 3.2 and 9.1. Similarly, all members that have administrative rights in a Sapelli project hosted in GeoKey can create temporary and permanent links to export the data in KML, CSV and GeoJSON formats, or use the QGIS plugin described in Sect. 5.8 on Analytical Capacity. Figure 5.11 below shows the UI for exporting data from within GeoKey and Sapelli Collector.

5.11 Accessibility As shown in Fig.  5.1, the Sapelli ecosystem includes mobile and desktop-based tools. The mobile-based applications Sapelli Collector and Sapelli Viewer are developed to operate under any network conditions, and they are designed to be used primarily, yet not exclusively, by non-literate users with no previous ICT and mapping experience. The desktop-based tools Community Maps and GeoKey require internet connectivity, and yet Community Maps is mobile friendly and was created with a deliberately simple design, its intended users are literate users with prior ICT experience and with an email account to set up a participatory mapping project. On the other hand, the desktop-based Progressive Web App Sapelli Designer was developed to allow users with prior ICT experience to customize Sapelli Collector projects in the field, thus Sapelli Designer works offline. As has been mentioned in Sect.

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Fig. 5.11  Screens for exporting data from GeoKey (left) and Sapelli Collector (right)

5.4, training materials and tutorials have been developed and will be updated as the technology evolves, aiming to simplify as much as possible the technical implementation of a participatory mapping project using Sapelli. Note that the software does not include functionality to support people with vision or dexterity problems.

5.12 Brief Use Case(s) The ExCiteS group has been working alongside Baka hunter-gatherers and Fang/ Bulu farmers in the periphery of the Dja Biosphere Reserve, southern Cameroon since 2016. The area is celebrated for its high biodiversity including many large mammals but is also plagued by land grabs and exclusion of communities and their knowledge in conservation efforts. Work on the ground began from an intentional place of ignorance – communities were consulted on their issues and perspectives in relation to the forest, educating project facilitators. From these discussions, which highlighted the injustice of illegal wildlife crime and interest in animal monitoring, project facilitators built Sapelli initiatives in a co-design process with a self-selected team from each village. Defining the projects’ objectives, potential risks and benefits was negotiated through an FPIC process after spending time building trust. Technological, practical, and literacy barriers were crossed by prioritizing community-leadership on the Sapelli interface and project management, resulting in icon-based, community-specific

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Sapelli apps run on simple, rugged smartphones, powered by portable solar chargers, and sending data autonomously to a database when mobile network sites were encountered. Formalizing these choices is achieved through creating community protocols in each community, a living set of mutual agreements that ensures community decisions and rights are upheld. Following a period of training and iterative alterations, community teams began collecting data. In accordance with community protocols, records along with photos and audio clips are sent to ExCiteS facilitators as well as staff at the Zoological Society of London, Cameroon. To date these totals at more than 1300 records and 1340 media photos and audio over six communities. Data are shared with the Ministry of Forestry and Wildlife where appropriate and has contributed to at least 36 arrests and 19 seizures of illegal wildlife crime, identification of forest corridors used by protected species (particularly elephants), developed skills of community members to use digital tools, the valorization of local knowledge systems, and empowerment to contribute solutions and reject involvement in trafficking. Systemic corruption and occasional technological issues hamper the project progress, but through collaborative innovation with communities, solutions are found. More information about this case study can be found in Hoyte (2021).

5.13 Comments and Recommendations A wide range of conservation projects have been carried out using Sapelli by researchers from the ExCiteS research group. As well as the project above, group members have worked with Pantaneiro fishers living in Brazilian Pantanal wetland; Maasai pastoralists in Kenya, and Ju|'hoansi rangers living in the semiarid deserts of Namibia. Details of these case studies can be found in Moustard et  al. (2021). Common threads within these case studies highlight the need for: a high level of trust between the target communities and project developers; communities’ right to choose the data they will be collecting; and researchers’ openness to include new tools that were not initially planned. As a result of these studies, a set of recommended steps for implementing an extreme citizen science project has been developed by the ExCiteS group, which enable conservation scientists to effectively create bottom-up collaborations with those living on the frontlines of conservation through community-led extreme citizen science. Comments and recommendations of the authors. Soon it is hoped that it will be possible to combine Sapelli Collector and Sapelli Viewer into one application. This will streamline the data collection, analysis, and visualization process. As part of the UCL ExCiteS Research group’s ongoing work we will continue to undertake further evaluation of the software, particularly with regards to inclusivity and the co-production of knowledge. As is likely true of any participatory mapping software outlined in this volume, Sapelli has been shown to be useful and effective in the contexts in which it has been

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developed and applied so far. The software itself, and the socio-technical approach it sits within, are based on the fundamental belief that research questions and data collection methods for conservation are most effective when they are developed in collaboration with communities and other partners who have direct, lived experience in these realities. We would encourage anyone interested in using the Sapelli software and approach in their research to download the app, familiarize themselves with the information on Sapelli.org and deploy it for their own purposes. Acknowledgements  We owe a debt of gratitude to all the people and communities who gave us their time, insight, and understanding in the development of Sapelli. We also acknowledge the funding support that we have received from funders. The research on Sapelli was kindly supported by the UK’s Engineering and Physical Sciences Research Council (award EP/I025278/1) and the European Union’s ERC Advanced Grant project European Citizen Science: Analysis and Visualisation (under Grant Agreement No 694767); Additional support was kindly provided by Esri.

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Chapter 6

SeaSketch Madeline Berger, Will McClintock, Chad Burt, and Tim Welch

Abstract  SeaSketch is software as a service (SaaS) that supports geospatial data visualization, data collection, geodesign and interactive map-based discussions. Originally developed to support marine spatial planning, SeaSketch is also used for more generalized purposes including research planning and crowdsourcing of spatial information. Like many participatory GIS applications, SeaSketch is intended to democratize planning efforts by exposing authoritative datasets through a publicly accessible web-interface, alongside tools that non-technical stakeholders may use to contribute information (such as where and how ocean space is used and valued), sketch and evaluate spatial plans (such as prospective ocean zones) and share ideas in public and private forums. Launched in 2012, SeaSketch has been used to support dozens of planning initiatives around the world but heretofore has required a license fee and some collaboration with the developers at the University of California Santa Barbara (UCSB), particularly when creating analytics and reports used to evaluate spatial plans. The latest version is published under the open-source BSD license and may be used for free, increasing potential adoption and long-term sustainability of SeaSketch projects. Keywords  GeoDesign · Marine spatial planning · Software as a service · Surveys

6.1 General Information Name of Application: SeaSketch Name of Developer: McClintock Lab Name of Funder: Waitt Family Foundation, Esri, Inc., numerous granting organizations. M. Berger · W. McClintock (*) · C. Burt · T. Welch National Center for Ecological Analysis and Synthesis, University of California Santa Barbara, Santa Barbara, CA, USA e-mail: [email protected]; [email protected]; [email protected] © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 C. M. Burnett (ed.), Evaluating Participatory Mapping Software, https://doi.org/10.1007/978-3-031-19594-5_6

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Type of System Software: Software as a Service Type of Programming Language: JavaScript, Python API Availability: Reporting tools are extensible via the SeaSketch Geoprocessing Framework Features: Map visualization, sketching spatial features, geospatial analysis, map-­ based discussion forums, spatial surveys Cost: Free Type of Data Collected: geographic features (points, lines, polygons) and associated attributes. Overview: The first version of SeaSketch (www.seasketch.org) was developed at the University of California Santa Barbara with initial financial support from the New Zealand Department of Conservation (DOC), the Tides Initiative of Canada, and Esri, Inc. Following the successful development and implementation of MarineMap for Marine Protected Area (MPA) planning in California (Merrifield et al., 2013), the developers applied similar design principles to SeaSketch for Marine Spatial Planning (MSP). Specifically, the tool was intended for the rapid deployment of a web-based application for (1) visualizing geospatial information and associated metadata, (2) contributing spatial information, such as the location and value of areas used for fishing and other anthropogenic activities, (3) sketching and evaluating zoning scenarios based on science and policy guidelines, and (4) sharing and discussing plans in map-based forums. Using the administrative dashboard, project owners could (1) add map services for data visualization, (2) configure and launch surveys for data collection, (3) create “sketch classes”, or zone elements with attributes, and (4) create discussion forums along with other customizations. Fundamentally, SeaSketch is a collaborative “geodesign” tool (McClintock, 2013) which supports the iterative sketching and analysis of plans (sketches), primarily zones that represent prospective marine spatial plans. By posting messages within forums with attached plans, users can share draft plans that in turn may be copied, modified, and re-shared with the same or other users. In this way, users collaboratively develop plans to meet a host of goals and objectives. SeaSketch 1.0 has been implemented to support MSP in dozens of countries including Barbuda (Johnson et al., 2020), Montserrat (Flower et al., 2020), the United States (Goldberg et al., 2018), Canada (McGee et al., 2021), New Zealand (Jarvis et al., 2015; Davies et al., 2018; Pohl & Funnell, 2021), Portugal (Seijo et al., 2021), Denmark (Andersen et  al., 2020), Norway, Reunion Island, Maldives, Federated States of Micronesia, Samoa, Fiji,  Bermuda and Indonesia among others.

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6.1.1 SeaSketch 2.0 In 2020, the Waitt Foundation funded the development of SeaSketch 2.0, a complete rewrite of the software service. This new version is published under the open-source BSD license and, as such, does not require a license fee. Moreover, the software architecture (Fig. 6.1) includes an open application programming interface (API) for the development and implementation of analytics and reports by third party developers, overcoming the bottleneck described previously. Other significant enhancements to the software include (1) modernized map visualization, (2) improved sketching tools, and (3) compatibility with mobile and tablet devices. The latter will significantly enhance accessibility (see Sect. 6.11 on Accessibility, (p. 139) to SeaSketch as smartphones become increasingly common. Aside from the changes in architecture and these feature enhancements, the essential functionality of SeaSketch remains the same between versions 1.0 and 2.0. As of this writing, SeaSketch version 2.0 has just been released so our experience with implementing the tool described in this chapter is almost entirely based on version 1.0.

Fig. 6.1  SeaSketch 2.0 system architecture

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6.2 Ethics SeaSketch, as a collaborative geodesign tool, was specifically developed to increase participation in planning by people with little or no technical, scientific, or planning experience. All SeaSketch projects to date have been made publicly available (i.e., exposed on the SeaSketch Projects website) to increase transparency and inclusivity in decision-making. That said, several features and aspects of implementation may reduce the number and types of users for any given project. For example, select data layers, sketching and analysis tools, forums, and surveys, may be private to a defined group of users. Privacy features such as these are essential when sensitive or proprietary data (e.g., fishing grounds, sacred locations) are needed for visualization, analysis by one group of users but public access is not warranted or granted. Likewise, users have access to a private “sandbox” (the My Plans tab) where they may sketch and analyze any potential design before choosing (or not) to share designs in a public or private forum. As such, SeaSketch features are designed to provide privacy, transparency, and collaboration tools implemented at the users’ and project owners’ discretion. SeaSketch users may be classified into those that use the application directly or by way of a facilitator, referred to as a “chauffeur.” Most of those surveyed who use SeaSketch directly have some higher education (Ballatore et al., 2019), while those who rely on chauffeurs have lower levels of formal education (Burnett, 2022). It is common for project owners and convenors to assume that those with lower educational levels will not want to or cannot use SeaSketch on their own. In fact, Burnett (2022) has shown that the use of a chauffeur negatively impacts user perceptions of the technology and planning process itself, while Currier (2018) found that even those with no prior use of laptops could complete surveys with a keen sense of accomplishment. Because it is easy to use, SeaSketch promotes inclusiveness in decision-making limited only by the willingness of project conveners to provide users with access to the tool and a modicum of training. A key ethical consideration is the time provided for - and demanded by - the use of a geodesign tool such as SeaSketch. Iterative sketching and analysis can be likened to a “hunt and peck” method of finding solutions. For example, a user might visualize a habitat layer, sketch a prospective zone over habitats in need of protection, and then run an analysis to determine if such a design met science and policy guidelines for ecosystem protection. Based on the results of that analysis, the design will be adjusted again and again until the user feels satisfied that they have done their best to achieve one or more goals. However, optimization tools such as PrioritizR (Flower et al., 2020) and tradeoff models (White et al., 2012; Lester et al., 2018) help identify solutions that meet one or more goals more optimally than any human could ever discover by way of geodesign alone. It should be noted that to respect the limited time that most participants have at their disposal, the geodesign approach inherent in SeaSketch should be combined with other tools to help users narrow the potential solution set and arrive at the best possible solutions quickly. For example, planners in the North Pacific Coast of British Columbia (McGee et al.,

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2021) combined the use of SeaSketch with Marxan (Ball et al., 2009) to help guide users in the design of marine protected areas that surrounded priority areas for conservation. Taking such an approach involves technical experts that may, in turn, decrease the sense of ownership as a result.

6.3 Cost With the release of version 2.0, SeaSketch is licensed by UCSB for free under the open-source BSD license. This means that anyone with an Internet connection and standard web browser may visit SeaSketch (www.seasketch.org), and with a few mouse-clicks, create and begin to configure a SeaSketch project. As with the previous version, map data may be hosted on third party servers and consumed by SeaSketch as map services for visualization. In addition, each project is provided with up to 500 MB of space for hosting data, reducing hosting costs and reliance on third party applications. SeaSketch 1.0 was much more costly. In most cases, a government agency, non-­ governmental organization (NGO) or private foundation provided the funding for a SeaSketch license (then $1000 USD) and partial salaries for SeaSketch developers at UCSB. A free, educational license was also issued for SeaSketch projects with limited functionality. After receiving a link to a SeaSketch project with administrative privileges, project owners (such as environmental planners at DOC) could customize and configure SeaSketch Version 1 without assistance from the developers at UCSB except in one important aspect; the analytical and reporting functions associated with zoning designs (Sect. 6.8, Analytical Capacity, pg. 135) were developed through a contract with UCSB programmers. This reliance on UCSB developers to fully utilize the analytical capabilities of SeaSketch created something of a bottleneck. Contracting can be expensive and, with only a handful of software developers available to create the analytical reports, in limited supply. Furthermore, the analytical framework for SeaSketch relied on ArcGIS Server, a proprietary software package provided by Esri, Inc., that ran on a dedicated cloud-­ based server on Amazon Web Services (AWS). SeaSketch projects that included analytical reports, therefore, necessitated a contract including ongoing AWS fees. Often, planning initiatives using SeaSketch would outlast their funding, and without AWS, their projects were severely limited in functionality. In SeaSketch 2.0, custom analytics and reports may be authored and deployed to the project administrator’s Amazon Web Services (AWS) account and typically can run under the free tier or cost up to $10 USD per month. An open application programming interface (API) is available for developers to create their own custom analytics and reports. And, as before, the McClintock Lab at UCSB may be contracted to develop and implement these reports for clients on an as-needed basis. Implementing a SeaSketch project (which may or may not include analytics), involves adding data layers, creating sketch classes, designing surveys, and

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managing discussion forums. All these activities do not require intervention or assistance from the software providers and, as such, SeaSketch can be a low- or nocost application to use.

6.4 Technical Level The technical capacity required to use SeaSketch depends on the user’s role and ultimate objective of the project administrators. For any given project, there can exist a wide range of users that interact with SeaSketch. Ballatore et  al. (2019) observed that SeaSketch users are considerably more educated than other PGIS users, with 60% of survey respondents completing school and 22% graduating from college. However, this research was conducted via a web-based survey which, naturally, did not reach many individuals that had used SeaSketch in a community workshop or facilitated setting which arguably makes up the majority of SeaSketch’s 9,000 plus users. On the other hand, Currier (2018) used SeaSketch in rural Bali, Indonesia, to investigate the changes to using Web-based tools for participatory mapping in areas where computers were uncommon and found that, in fact, “people with varying levels of experience with computers and digital maps could successfully complete, and perhaps even enjoy, a computer-based mapping survey. Perhaps the most surprising outcome was that none of the participants, including those who lacked prior experience, accepted the offer of assistance in operating the computer—they all chose to input their answers themselves. One participant’s delight upon completing the surveys—his first time using a computer—was evident when he stood up from the table, raised his arms over his head and exclaimed ‘I did it! I did it!’” (Currier, 2018, p. 59). Clearly, technical levels vary amongst SeaSketch users and their ability to use SeaSketch depends, in part, on a certain motivation to complete tasks and participate in any given mapping activity. However, these users (and their associated technical skills) can generally be grouped into four categories, listed below.

6.4.1 Stakeholders Project stakeholders are likely using SeaSketch primarily in a group setting to visually assess and discuss data and/or potential spatial designs. Depending on the project, they may also be asked to individually create and submit designs to a forum to enable upcoming meetings or discussions. Therefore, stakeholders need to have a basic level of technical proficiency, enabling them to at the very least, click between different pages of the SeaSketch project and toggle between layers on the map. They may also need to understand how to create and add to forum messages, and/or draw shapes on the map.

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For certain stakeholder groups, it is necessary to have trained chauffeurs for some of these tasks. However, rather than have assigned people to always interact with SeaSketch in place of the stakeholders, it is preferable to have a trained facilitator to aid stakeholder groups through the process (but not necessarily do it entirely for them). Training facilitators who can speak local languages and are familiar to the stakeholder groups can be helpful in building stakeholders’ confidence in using the tool, with the main goal of increasing their technical capacity and therefore engagement in the project.

6.4.2 Members of the Public Members of the public generally interact with SeaSketch as survey respondents during the data collection or survey phase of a project. This can happen in a variety of settings, with survey deployment strategy often dependent on geography, community structure, existing power structures, political climate, mobility, and project specifics (budget, timeframes, personnel). Surveys are usually available publicly through links posted on project websites, on posters, promotional videos, or flyers, allowing anyone to access the survey individually through their desktop or mobile device. Survey responses may also be collected in group settings, such as community meetings, or specific stakeholder group meetings. The setting in which a member of the public is accessing the survey affects the technical capacity needed to submit a successful response. If accessing the survey individually at home via the survey link, respondents must have enough understanding to first navigate to the survey page itself via their web browser, and then begin the survey by clicking the “Take the Survey” Button. During the survey design process, we strive to create a survey that is easily understood and accessible by all - therefore, once the respondent successfully begins the survey, we hope navigating through it is intuitive. The most important ability the respondent must possess is the ability to interpret maps and locate places on the map for their sketch’s responses.

6.4.3 Administrators Project administrators are members of the internal team that have administrative access to the SeaSketch project. Different administrators may have different roles and reasons for accessing the project, and therefore do not all need the same technical capability. Project administrators that are not core SeaSketch staff may not need much higher capability than a stakeholder, responding to forums, drawing shapes, following prompts etc. However, it is advantageous for at least one project administrator to be able to easily navigate the site, download files (tables or spatial data

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stored as shapefiles) from the site, and interpret/analyze the information contained within those files. It is also ideal for there to be at least one or two project administrators outside the SeaSketch core team with moderate to advanced geospatial data management skills, who can assist with data cleaning and publishing to the site, or at least assist with quality control of data layers uploaded by SeaSketch core team members. SeaSketch core team members are always administrators on a project, often taking the lead on initial project configuration, data management, publishing layers, cartography, and survey design. Strong geospatial data management and analysis skills are required, as well as sufficient technical capacity to work closely with developers on designing analysis and reporting capabilities, troubleshooting issues, etc. SeaSketch 1.0 required core team members to also have substantial experience using ESRI products and services, such as ArcMap to configure data and run analyses, and ESRI servers and ArcGIS Online to publish and display data, whereas the latest version does not. In SeaSketch 2.0, users may use any combination of proprietary and open source desktop GIS tools to create spatial datasets (e.g., shapefiles, flatgeobuffs, geojson), upload directly to SeaSketch and use built-in cartographic tools to stylize layers using the MapBox GL JS. 

6.4.4 Developers Developers are part of the SeaSketch core team and must possess high level technical skills in software development and spatial analysis. Specifically, developers must have strong knowledge and experience working in the scripting languages and tools supporting SeaSketch to maintain the site, build new features, and design analyses. See Sect. 6.8 on Analytical Capacity (p. 135) in this chapter for more detail, where the various tasks and responsibilities developers undertake are described. With the release of SeaSketch 2.0, third party developers with experience in JavaScript and AWS infrastructure deployments will be able to develop their own analytics and reports in SeaSketch via our geoprocessing and reporting framework API. As of the writing of this chapter, the documentation for accessing this API is under development  but may be accessed at https://github.com/seasketch/geoprocessing/wiki.

6.5 Inclusiveness SeaSketch has the capability to store and display many different forms of information, from users with a wide range of backgrounds and capabilities. This allows information from diverse groups to be incorporated into planning processes using SeaSketch.

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Users with limited technical capacity or experience using devices such as computers or smartphones may feel more comfortable answering a mapping survey on a paper print out map, also known as scale mapping (Rambaldi et  al., 2006). SeaSketch can incorporate information collected via paper maps in two different ways. First, a facilitator can hand-digitize the shape in SeaSketch. This was done extensively to incorporate ocean use survey responses from fisherman in Curacao (McClintock, unpublished). This process requires layers that appear on the paper maps to also be visible digitally on the SeaSketch interface, such as a grid or landmark layer. The second way spatial information collected from another source can be incorporated into SeaSketch is through manual upload of shapefiles into the application. This feature can also help avoid potential fatigue from respondents at a site that has engaged in previous participatory mapping projects, an issue common in areas with high biodiversity and conservation interest (Chambers, 2006).

6.5.1 Integration of Non-spatial Knowledge SeaSketch has various mechanisms for integrating nonspatial information with spatial information. Surveys can include questions that are not spatial, such as demographic questions about the respondents, general comments about specific areas, and opinions. The forum feature also helps collect narrative information on specific places, providing additional context to the spatial data on the map. This builds on traditional GIS capabilities, and it is essential for making the spatial data useful in the planning process.

6.5.2 Empowerment of Underprivileged Groups SeaSketch version 1.0 was not compatible with mobile devices such as smartphones and tablets. As such, users were required to use laptop and desktop computers which were primarily provided by process organizers in meetings, agency offices or public venues. Stakeholders that did not have a desktop or laptop computer with an internet connection, or could not attend meetings, were potentially left out of decision ­making and political participation. SeaSketch 2.0 is now compatible with smartphones and tablets (Fig.  6.2), devices that are considerably more common amongst users globally. Although it is still in the early stages of deployment (the Government of the Azores launched an ocean use survey in February 2022), we are confident that this new platform will encourage wider participation in surveys that ask stakeholders to express their values and opinions on how ocean space is used and managed.

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Fig. 6.2  A SeaSketch survey implemented by the Government of the Azores to understand how citizens value ocean spaces, shown on a mobile device. Users are encouraged to identify an (a) unlimited number of places within the coastal ocean for any given sector (such as Underwater Cultural Heritage) and assign relative values (b) for specific activities or valued resources within those areas. Users may access this survey at any time using a smartphone or tablet, without the help of facilitators

6.6 Data Accuracy Data accuracy is how close a given set of measurements are to their true value, whether they are correct or without error. For data that represent objective realities, such as the location of a seamount or harbor, data accuracy is relatively easy to evaluate or verify via direct observation. For data that represent subjective realities, such as the relative spiritual importance of one place over another, accuracy is more difficult to measure. SeaSketch uses both objective and subjective data to generate map layers used in planning.

6.6.1 Survey Tools Seasketch’s human use surveys allow members of the public to convey where and how they use the ocean resources by answering survey questions and digitizing points, lines, or polygons. To do this they must navigate an online map, accurately

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draw shapes, and allocate points to areas to indicate their relative value. There are several ways for this to be done incorrectly which can create inaccurate results or even misrepresent the user. SeaSketch mitigates these issues in the following ways: • Surveys are broken down into sections with text instructions and animations indicating how to draw shapes, to provide an easy-to-follow example for users drawing their own shapes. • Users may be required to zoom their map into a minimum level before they can draw a shape to discourage users from drawing shapes that are too large. If they attempt to draw shapes from too far out, they are instructed to zoom in. • Invalid shapes (e.g., self-crossing) are not allowed as they often require additional processing that may not fully capture what the original drawer intended. The user is notified of these problems and instructed to make corrections, rather than having the data analyst try to interpret the users’ data (see Fig. 6.3). Guide map layers are provided that let users know where they are and where they can draw, including nautical or bathymetric maps with navigation markers, coastline, the study region boundary, administrative boundaries, prohibited areas, local place name labels, etc. If users draw shapes that cross land, such as tracing shorelines, the land portion will be automatically removed (if so configured). Additionally, for projects where data accuracy is a potential issue, partners using SeaSketch often provide chauffeurs who come to public locations and guide people through the survey process. Survey results and resulting heatmaps are also reviewed

Fig. 6.3  A user answers a survey question, indicating where they fish, what gear they use, and the subjective importance of that fishing area. Here, the user is notified of having drawn an invalid geometry (self-crossing polygon). By clicking on the “Invalid Shape” button, a video is presented to the user demonstrating how to fix the shape

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by local stakeholder groups, whereafter incorrect or mistaken shapes are corrected or removed by SeaSketch analysts.

6.6.2 Sketching Tools A core feature of Seasketch is that users can sketch and evaluate shapes (e.g., prospective zones), iterate on them, group, share and discuss them with other stakeholders. This is crucial to allowing the best plan options to emerge from the group. It also creates challenges to validating, organizing, and controlling access. Several features are in place to help ensure the most accurate data possible. To name a few: • User drawn sketches are not accepted until they meet minimum requirements, and users are guided through making corrections until they get it right. Requirements include ensuring that sketches have valid names and attributes, and that sketch geometries are complete, not too small, or large, and within the project study region. • Each sketch has a unique ID and timestamp of when it was created and last edited. These can be used together to tell them apart. • Sketches can be further grouped into collections and copies or duplicates of these can be made at any time. • Each sketch and collection is owned by the user that creates them, and they alone can make changes. Collaboration is done by sharing designs through discussion forums where users can then view and copy designs into their own space to work with further. Even with these features, it can be a challenge for users to keep track of everything they create, to know which is the “latest” iteration, and to narrow down the options. Some strategies can be used to overcome this: • Administrators or representatives can be nominated to copy user submissions into new collections that represent a group and share them back with all stakeholders through a discussion forum to verify, discuss, and request corrections. • The names and descriptions of sketches can include notes or keywords. At the end of the process, final proposed boundaries may not be created in SeaSketch, but rather used as a guide to develop boundaries with greater precision in-house by the authoritative agency using a desktop GIS.

6.6.3 Reporting Analytical reports in SeaSketch allow users to assess and compare the sketches they draw (see Fig. 6.4). It is important to ensure the accuracy of the input data, the analytical methods used, and their limitations, so that reports are used properly. The

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Fig. 6.4  An example of a report from a SeaSketch project in Bermuda. A steering committee for the planning initiative called the Bermuda Ocean Prosperity Programme (BOPP), developed a list of goals and objectives for planning within the Bermuda Exclusive Economic Zone

accuracy of the final user designs and their potential to meet objectives depend on it. SeaSketch takes the following steps to ensure accurate and proper use of data in analysis: • Data Preparation. All data sources, and their pre-processing steps are documented, scripted, and made public through GitHub so that they can be verified and reproduced. Changes are clearly tracked. • Data Publishing. Prepared datasets are published such that the latest available is used. • Data Analysis. Behind each SeaSketch Report are geoprocessing functions. The code for these functions are published publicly, allowing them to be reviewed and verified. A test suite is also developed for each function to verify the accuracy of their output for different input, and to ensure the results continue to be correct as changes are made, or issues are discovered and fixed. • Data Visualization. Analytical results are presented to the user in the simplest possible form, making it clear if guidelines have been met or not, and accompanying text to interpret them.

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One key feature of SeaSketch that is seen as critical to user success but can hinder data accuracy is the speed of running reports. It is seen as critical that users receive report results quickly, (optimally within 5–10 s but no more than 1–2 min) so that they can rapidly iterate on their designs to achieve planning objectives. The idea is that faster iteration will result in increased participation and better design outcomes. To maintain this speed, sometimes algorithms are chosen that are less accurate. For example, an algorithm for computing the distance between two points may be 100× faster than another, bringing computation time from 10 min to 10 s, but have an error of up to 5%. Another algorithm may be 1000× faster but have an error of up to 20%. These tradeoffs are weighed with the project team and typically error within 5% is acceptable in SeaSketch because it’s within the range of error of the data itself, and it makes rapid iteration possible. A 20% error on the other hand would not be acceptable but may still be used if it is the only option and provides some value. One area for improvement in SeaSketch is to report the accuracy/error more clearly for each report.

6.7 Data Privacy SeaSketch is designed to respect the privacy of user information at multiple levels. Administrators have fine-grained access controls to precisely match their need to make data available to different user groups. They can create these specific user groups and grant access privileges to these groups for sensitive project data, including data layers, discussion forums, surveys (both to participate and to view results), and sketch classes. Furthermore, individual end-users can work on spatial plans in a private workspace before choosing to share with user groups or project administrators (Fig. 6.5). The SeaSketch system is designed to comply with privacy laws such as GDPR and CCPA, meaning: • Consent is always requested before sharing end-user information with project administrators • Data is never sold or shared with 3rd parties • Users can request the deletion of their accounts and data • Data is securely stored using industry best practices on Amazon Web Services Data used for visualization and analysis purposes may be hosted directly by SeaSketch or accessed from any web service of a project administrator’s choosing. Data provided by the project owners, such as map layers used for visualization or analysis, are the property of project owners, not UCSB or software developers. Data generated in SeaSketch surveys, such as ocean use survey heatmaps (Fig. 6.6), are likewise the property of the project owners. The developers of SeaSketch reserve the right to evaluate and publish usage data from the SeaSketch database (e.g., how

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Fig. 6.5  SeaSketch 2.0 survey in The Azores. Before answering surveys, users may be required to read and agree to a consent sharing and privacy agreement

many users accessed SeaSketch over time) but not for individual SeaSketch projects. Data within the SeaSketch database is accessible only to SeaSketch software developers. When a project is complete, all data collected via surveys can be delivered to the project owners upon request. Likewise, all information contained within project forums (i.e., message contents and sketches) can be exported by project owners as a single GeoJson file. And, finally, all personal information, such as names and email addresses, can be expunged from the system at the request of individuals.

6.8 Analytical Capacity SeaSketch aims to put the best available science at everyone’s fingertips to assess how well proposed designs for marine zoning meet planning objectives. Analysis is pre-packaged into a handful of reports which the user can run at any time on their designs and get results immediately. Reports are tailored for each project and locale. They are typically developed ahead of the planning process and then refined based on feedback. The expertise that all users must develop is an understanding of the planning objectives, how they are measured, and how to interpret report results in guiding their designs. SeaSketch tries to make this as easy as possible with simple visualizations, descriptive text, and references to data sources. A more general Knowledge Base is provided with help content for using SeaSketch properly.

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Fig. 6.6 (a) Heatmap of commercial fishing value created from survey responses collected in SeaSketch 1.0, displayed in a project in Bermuda. (b) Analytical reports were then developed to calculate the percent of fishing value captured by plans drawn by users, with toggles that allow users to visualize the reporting results

6.8.1 SeaSketch Reports SeaSketch Reports are developed using the SeaSketch Geoprocessing Framework. This framework provides project partners with the building blocks they need to develop their own real-time Report capability and integrate it with the SeaSketch platform including data publishing, spatial analysis, and report layout.

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6.8.2 Geoprocessing Framework The Geoprocessing Framework is specifically designed for large scale collaborative spatial planning processes where you need to be able to run analysis and generate reports quickly and simultaneously at scale, for all the user designs being created and iterated on. Using “serverless” technology, the system will scale up to handle any number of simultaneous analyses runs, and then scale back down when not in use to near zero cost. Developing and maintaining these Reports end-to-end requires expertise in spatial analysis, web UI development, and cloud hosting using Amazon Web Services. Much of this complexity has been reduced through the provided documentation on GitHub, automation scripts, templates, and a UI component library. In addition, all the reports developed by the SeaSketch team are made available publicly (https:// github.com/seasketch), providing a growing source of inspiration for others to draw on.

6.8.3 Heatmap Analysis In addition to Reports, SeaSketch can package more sophisticated analysis. One example is the Heatmap Analysis module which takes human use survey results and aggregates them into “heatmaps” of human use value to be displayed visually as map layers (Fig. 6.6a, below) and incorporated into a Human Use report summarizing the value of human use captured by user’s designs (Fig. 6.6b, below). Currently, the core heatmap module is a software library that is run standalone on someone’s computer. Heatmap results are then uploaded, styled, and published as map services, and added to SeaSketch. This requires experience working with Python and GIS datasets. A Human Use Report would then be developed using the SeaSketch Geoprocessing Framework. A template is provided for this. Plans are underway to automate this step, providing a built-in admin interface that allows Administrators to run heatmap analysis themselves, specifying the survey and run parameters. Results are then verified and published as data layers for users to view. A Human Use Survey report is published for assessing the value for each human use activity that is captured in a sketch or sketch collection.

6.9 Visualization Capacity Spatial data is visualized on SeaSketch v2.0 using mapbox-gl-js, a webgl-based map client developed by the software company MapBox. It has benefits such as the ability to display data at a high resolution, mobile compatibility, and support for visualizing data in 3d. The client also supports many different open and proprietary

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web services and enables us to more easily support direct data uploading and hosting on SeaSketch using simple vector formats. This is a new feature since the original version of SeaSketch (v1.0), which relied on ESRI data servers to host data. There are two types of map visualization on SeaSketch: Basemaps  Variety of basemaps are included that come pre-populated with information such as satellite imagery, topography, and names placed (e.g., OpenStreetMap). These maps are useful for simple user experience to zoom, pan and identify points of interest similar to what one might expect to find on Google Maps or something similar. Layer Lists  Like a conventional map portal feature, users can sort through layer lists using folder labels, which administrators create to organize layers in an intuitive way or using a search bar. The user experience is generally more complicated than using simple basemaps but Layer Lists support more complex use-cases (e.g., when a sophisticated user wishes to toggle on/off a dozen layers to find a precise location). The administrative dashboard can also be used to visualize the raw results (e.g., points, lines and/or polygons) of an ocean use survey overlaid on a basemap. The results can be sorted and edited to correct potential mistakes in data entry, then downloaded to be summarized in a desktop GIS. In the current version, the resulting heatmap must be published as a map service and added to SeaSketch before it may be visualized by users. A future release will allow administrators to flag results and reveal them to end users to visualize along with a basemap. Analytical reports may also include toggles for map layers (that may or may not be included in the layer list) so users may turn them on and off without having to search for them in the layer tree.

6.10 Openness SeaSketch is an open system, facilitating the free use and configuration of the tool as a software service and also builds on and is available as open-source software. The latest iteration of SeaSketch requires no licensing or hosting fees. Built using the software-service model, planners can simply go to the SeaSketch site and create a new project which they can fully configure to meet their needs using an administrative interface, rather than installing, configuring, and hosting a software on their own machine. As project administrators, planners may upload their own data for use in SeaSketch, link to publicly available web services, and download data from their project available in a variety of standards-based formats. The SeaSketch software consists of two major open-source components. The software service component is available under the 3-clause BSD license. While available under this license, the developers do not anticipate outside contributions

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or directly support hosting of this complex tool. Past experience with similar tools such as MarineMap has led the creators to believe that there is little demand or technical capacity to support a self-hosted tool. Rather, it is made available so that adopters may have confidence in how the software treats their data and know that they have the option to fork the codebase should the need arise. The second major software component is SeaSketch’s geoprocessing system. This package is also available under a BSD license and outside contributions are actively encouraged. The developers intend for this open system to support customization of reporting tools within SeaSketch projects by 3rd-party developers. Where in prior versions of SeaSketch the creators had to be contracted to customize analytical tools for each project, this customization can now be done using simple tools available to anyone with JavaScript development experience.

6.11 Accessibility SeaSketch is an online service, and therefore does not need to be downloaded onto a personal device to be used. The application functions on both desktop and mobile devices, however the drawing feature and analytical capabilities are much easier to use on desktop, when users are not confined to small screens and limited data availability. The mobile feature is most useful for users interacting with the survey tool, enabling respondents who do not have home internet access or access to a desktop device to participate in ocean use surveys. The survey tool may be configured for offline use, but the planning tool is currently limited to use when connected to the Internet.  Specific features and project management tasks range in how accessible they are to users depending on the users’ technical capacity. Anyone who can navigate a web browser should be able to visualize data on the map, participate in surveys, and read or respond to forums. More comfort and/or experience with web applications is needed to manage projects as an administrator, which involves adding users to the project, setting up surveys and forums, and managing sketch classes drawn by users. To create custom analytic reports, a user must have strong experience with JavaScript and Amazon Web Services. SeaSketch developers usually are heavily involved in creating and updating project analytics. However, it is an eventual goal to make adjusting the analytical framework more accessible to users who have only limited JavaScript experience, once a SeaSketch developer has set up the initial infrastructure in place. With SeaSketch 2.0, the tool is be accessible to all organizations and individuals with the technical knowledge to set up and manage projects. However, even before this version, SeaSketch has strived to be an accessible tool for resource poor organizations by providing a free license for educational projects. The SeaSketch interface has been translated into Spanish, Indonesian, Norwegian, Portuguese, Dhivehi, Kosraean, Samoan and French. In some projects, the SeaSketch interface is displayed in English, but some project contents (such as survey

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questions) have been displayed in a different language, such as Divehi in the Maldives and Portuguese in the Azores.

6.12 Brief Use Case Anthropogenic activities within the ocean such as fishing, shipping, mining, tourism, and mariculture are increasing in spatial extent and intensity, and the cumulative effects of these activities are having a negative impact on marine ecosystems globally (Halpern et al., 2008, 2015). Overlapping activities sometimes cause conflict between sectors such as transportation, recreational diving, and fishing. To promote the sustainable use of ocean resources while reducing conflicts and threats to marine ecosystems, many governments are undertaking a process called Marine Spatial Planning (MSP) which, in part, democratizes ocean zoning by maximizing stakeholder involvement at all stages (Ehler & Douvere, 2009). The Eelgrass Protection on Fishers Island, New York project sought to create a coastal and watershed management plan to help protect eelgrass (Zostera marina) meadows surrounding Fisher’s Island, NY, located 2 miles off the coast of CT in Long Island Sound. Eelgrass meadows (Fig. 6.7) are essential habitat supporting both commercially fished species and species of special concern (pinnipeds, sea turtles) in the North Atlantic region, yet these areas have decreased to less than 10% of their historic acreage in this region. As 24% of the remaining eelgrass in the Long Island Sound (98% of remaining eelgrass in New York governed waters) surrounds Fisher’s Island, the objective was to engage local stakeholders in creating Seagrass Management Areas (SMAs) to protect this ecosystem, and ultimately help support natural recovery of eelgrass meadows in other areas of the Sound.

6.12.1 SeaSketch Users Administrators: This project included SeaSketch team members, project facilitators from The Nature Conservancy and t Henry L. Ferguson Museum, and the Coalition co-chairs as administrators on the project. While the SeaSketch team and project facilitators were heavily engaged in the administrative activities such as data management, forum creation and moderation, and organizing draft SMAs, the coalition members did not use their administrative access at all. Project facilitators believe this is likely due to a combination of being busy and not being comfortable with the software. Project Participants (Primary Users)  Coalition members all used SeaSketch to submit shapes and designs and used SeaSketch during meetings as a visual accompaniment to the discussion (whether on their own device or through screen sharing with an administrator). Some of the Coalition members were identified as ‘super

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Fig. 6.7  The SeaSketch project used by the Fishers Island Seagrass Management Coalition, showing the distribution of eelgrass around the island in 2017

users,’ self-identified members who wanted to be more familiar with the software and potentially train others how to use it. In response, there was a meeting in mid-­ March 2020 between the admins/staff and super users, led by Will, where everyone was given a tutorial. There were also coalition members that did not take as quickly to using SeaSketch. Some never opened the invitation email and relied solely on group meetings to view any data produced by surveys or other data hosted on the SeaSketch interface. There were others that tried to engage with SeaSketch but faced initial challenges they found discouraging. One on one meetings with project facilitators helped some of these user’s become more comfortable with using the tool, however there remained a group that hardly interacted with SeaSketch throughout the project. General Public (Survey Respondents)  The public also had access to SeaSketch through the “Stakeholder Usage Survey,” where anyone that used the coastal waters of Fisher’s Island in any way were invited to identify, from a list, one option that best described their most frequent use of the waters surrounding Fishers Island (FI). They were then able to use the “Add a Feature” function to place points (as many as they wanted) on a map of FI and its surrounding waters to indicate where they engaged in specified activities. There was an optional second question they could respond to in the same way as the first (Optional: Is there a second activity you frequently use the waters surrounding Fishers Island for?) and place points. The survey succeeded in collecting responses from 151 ocean users.

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Fig. 6.8  The SeaSketch survey used on Fishers Island to gather information on the distribution of human activities in and around the coastal ocean

6.12.2 SeaSketch Features Used Survey: As described above, the survey tool was used to gather data on how residents and visitors to fisher’s island used coastal space (see Fig. 6.8). Data from this survey were then added to the project as a visualization tool for coalition members to reference when designing Seagrass Management Areas. Separate layers were developed for each usage category (swimming, boating, fishing, etc.) and could be turned on or off when looking at the map. Together this data showed where hotspots for specific activities were located relative to eelgrass meadows. Forums  Forums were used heavily in the early stages of the project. In August 2020, during a coalition meeting, members in attendance were split into small groups, with each group given a specific area around the island and asked to design draft Seagrass Management Areas for that area. After working together as a group to decide on location, shape and size of potential management areas, each group drew draft SMA’s in SeaSketch and shared them to a forum. The rest of the members were able to comment, through the forum, on each SMA, specifying what they liked or disliked about the design, improvement ideas, or any other thoughts they might have (Fig. 6.9). Sketching and Analytics  The ability to sketch designs for different management areas and view analysis (see Fig. 6.10) was the most heavily used feature for this project.

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Fig. 6.9  A forum used by users to share zoning designs, comment on them, copy and improve upon them over time. Usernames have been blurred to protect their anonymity

Custom analytics were created based on the coalitions overarching goals, which were: • 100% of the island’s seagrass is effectively managed to sustain eelgrass at a level that is greater than or equal to the 2017 extent of 347 acres (no net loss) • Maximize seagrass protection levels within SMAs • Maximize suitable area for eelgrass recovery or restoration with SMAs • Reduce nitrogen loading to SMAs from land-based sources on the island (fertilizer, wastewater) Working closely with the project facilitators, SeaSketch developers created analysis that could be run for each SMA created that reported the following statistics: • • • • • • •

Total acreage of SMA Seagrass acreage within SMA Percent of seagrass within SMA (% of acreage surveyed in 2017 by USFWS) Seagrass Ecosystem Composition Score (0–4) Eelgrass Site Suitability (0–4) Change in seagrass, between 2012 and 2017 (gain, no change, loss) Seagrass Protection: SMAs were scored from 0 (unprotected) to 4 (fully protected) and is based on the allowed fishing gear types and uses within the area(s) using methods defined in Horta e Costa et  al. (2016), a study that evaluated

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Fig. 6.10  SeaSketch reports like this are designed to help users determine whether they are meeting project goals and objectives. In this case, the user is informed as to whether they are protecting enough seagrass and areas suitable for seagrass restoration

impacts to biodiversity and habitats associated with allowed uses across 100 MPAs worldwide. • Watershed Protection: Based on the level of fertilizer use the coalition chose to allow • Survey Results: Data from the Stakeholder Usage Survey: For the area that was drawn, counts would be generated for activities, based on the number of pins in that area

6.12.3 Support Required As the project went on, the coalition members and project facilitators became more and more independent and able to use SeaSketch without much intervention from SeaSketch staff. SeaSketch staff members were always needed to build and update the analytical framework, and to publish data layers to the project. However, project facilitators were able to create and manage forums, designs submitted by user s, and navigate SeaSketch live on calls without any support from the SeaSketch team.

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6.12.4 Additional Notes Given this project was launched right at the beginning of the COVID-19 pandemic, many if not most of the meetings where coalition members were asked to collaborate and provide input were held online. SeaSketch helped enormously with visualization and engagement during these online Zoom meetings. The SeaSketch tool was used in tandem with: Excel spreadsheet to summarize plans and decisions, PowerPoint to lead meetings, PDF packets with photos of SMAs for people to review, and voting/polling features on Zoom and Survey Monkey to elicit feedback and conduct voting sessions with the coalition. Lastly, it is useful to note that this project used version 1.0 SeaSketch. The new version of SeaSketch (2.0) likely would have allowed project facilitators to be less dependent on SeaSketch staff members. First, they might have greater autonomy in data management and visualization as SeaSketch 2.0 allows users to upload their own shapefiles and apply cartographic styling. Second, with the new analytical framework in place, project facilitators with some analytical background may have been able to update the custom analytics and reports produced on the draft SMA’s, responding to the coalition feedback without having to engage the help of a developer.

6.13 Comments and Recommendations As with any tool, the efficacy and utility of SeaSketch will depend heavily on the ways in which it is implemented. The simple tools that SeaSketch provides users to express their values (e.g., what areas are important), explore ideas (e.g., what areas need better management), and collaborate with each other (e.g., to create a network of protected areas) do not require extensive training to be used effectively. Given that SeaSketch is free to use and configuring basic projects (particularly those that do not require analytics) is extremely simple, we encourage those involved in place-­ based planning (such as MSP), to explore using it with non-technical stakeholders.

References Andersen, J.  H., Bendtsen, J., Hammer, K.  J., Harvey, E.  T., Knudsen, S.  W., Murray, C.  J., Carstensen, J., Petersen, I. K., Svegaard, S., Tougaard, J., Edelvang, K., Egekvist, J., Olsen, J., Vinther, M., Al-Hamdani, Z., Jensen, J. B., Leth, J. O., Kaae, B. C., Olafsson, A. S., McClintock, W., Burt, C., & Yocum, D. (2020). ECOMAR: A data-driven framework for ecosystem-based Maritime Spatial Planning in Danish marine waters (NIVA report; no. 7562-2020). Ball, I.  R., Possingham, H.  P., & Watts, M. (2009). Marxan and relatives: Software for spatial conservation prioritisation (chapter 14). In A. Moilanen, K. A. Wilson, & H. P. Possingham (Eds.), Spatial conservation prioritisation: Quantitative methods and computational tools (pp. 185–195). Oxford University Press.

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Ballatore, A., McClintock, W., Goldberg, G., & Kuhn, W. (2019). Towards a usability scale for participatory GIS.  In P.  Kyriakidis, D.  Hadjimitsis, D.  Skarlatos, & A.  Mansourian (Eds.), AGILE conference on geographical information science: Geospatial technologies for local and regional development. Springer. Burnett, C.  M. (2022). Participatory mapping as global governance. Doctoral dissertation, University of Massachusetts, Boston. Chambers, R. (2006). Participatory mapping and geographic information systems: Whose map? Who is empowered and who disempowered? Who gains and who loses? The Electronic Journal of Information Systems in Developing Countries, 25(1), 1–11. https://doi.org/10.1002/j.1681­4835.2006.tb00163.x Currier, K.  E. (2018). Mapping perspectives for environmental planning. Doctoral dissertation, University of California Santa Barbara. Davies, K., Murchie, A. A., Kerr, V., & Lundquist, C. (2018). The evolution of marine protected area planning in Aotearoa New Zealand: Reflections on participation and process. Marine Policy, 93, 113–127. https://doi.org/10.1016/j.marpol.2018.03.025 Ehler, C., & Douvere, F. (2009). Marine spatial planning: A step-by-step approach toward ecosystem-­ based management. In: Intergovernmental Oceanographic Commission and Man and the Biosphere Programme. IOC Manual and Guides No. 53, ICAM Dossier No. 6, UNESCO, Paris. Flower, J., Ramdeen, R., Estep, A., Thomas, L.  R., Francis, S., Goldberg, G., Johnson, A.  E., McClintock, W., Mendes, S.  R., Mengerink, K., O’Garro, M., Rogers, L., Zischka, U., & Lester, S. E. (2020). Marine spatial planning on the Caribbean island of Montserrat: Lessons for data-limited small islands. Conservation Science and Practice. https://doi.org/10.1111/ csp2.158 Goldberg, G., Hastings, S., & McClintock, W. (2018). SeaSketch for Safe Passage: Collaborative mapping helps conflicting marine interests work toward shared goals. Proceedings of the United States Coast Guard, Springer, 77–81. https://bit.ly/2Uz7xt9. Halpern, B. S., Walbridge, S., Selkoe, K. A., Kappel, C. V., Micheli, F., D’Agrosa, C., Bruno, J. F., Casey, K. S., Ebert, C., Fox, H. E., Fujita, R., Heinmann, D., Lenihan, H. S., Madin, E. M. P., Perry, M. T., Selig, E. R., Spalding, M., Steneck, R., & Watson, R. (2008). A global map of human impact on marine ecosystems. Science, 319, 948–952. Halpern, B. S., Frazier, M., Potapenko, J., Casey, K. S., Koenig, K., Longo, C., Lowndes, J. S., Rockwood, R. C., Seic, E. R., Selcko, K. A., & Walbridge, S. (2015). Spatial and temporal changes in cumulative human impacts on the world’s ocean. Nature Communications, 6, 7615. Horta e Costa, B. H., Claudet, J., Franco, G., Erzini, K., Caro, A., & Gonçalves, E. J. (2016). A regulation-based classification system for Marine Protected Areas (MPAs). Marine Policy, 72, 192–198. Jarvis, R. M., Breen, B. B., Krägeloh, C. U., & Billington, R. B. (2015). Citizen science and the power of public participation in marine spatial planning. Marine Policy, 57, 21–26. Johnson, A. E. W. J., McClintock, O., Burton, W., Burton, A., Estep, K., Mengerink, R. P., & Tate, S. (2020). Marine spatial planning in Barbuda: A social, ecological, geographic and legal case study. Marine Policy, 113. https://doi.org/10.1016/j.marpol.2019.103793 Lester, S. E., Stevens, J. M., Gentry, R. R., Kappel, C. V., Bell, T. W., Costello, C. J., Gaines, S. D., Kiefer, D. A., Maue, C. C., Rensel, J. E., Simons, R. D., Washburn, L., & White, C. (2018). Marine spatial planning makes room for offshore aquaculture in crowded coastal waters. Nature Communications, 9, 945. McClintock, W. (2013). GeoDesign: Optimizing stakeholder-driven marine spatial planning. Proceedings of the United States Coast Guard, 70–74. https://go.aws/2Uy5qWm McGee, G., Byington, J., Bones, J., Cargill, S., Dickinson, M., Wozniak, K., & Pawluk, K. A. (2021). Marine plan partnership for the North Pacific coast: Engagement and communication with stakeholders and the public. Marine Policy, 104613. https://doi.org/10.1016/j. marpol.2021.104613

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Merrifield, M., McClintock, W., Burt, C., Fox, E., Gleason, M., Serpa, P., & Steinback, C. (2013). MarineMap: A web-based platform for collaborative marine protected area planning. Ocean & Coastal Management, 74, 67–76. https://go.aws/3bHyroj Pohl, I., & Funnell, G. (2021). Sea Change – Tai Timu Tai Pari Plan marine protected area (MPA) proposals: Agency analysis and advice on selection of MPAs towards development of the Hauraki Gulf Marine Park MPA network. Department of Conservation and Fisheries New Zealand (p. 166). Rambaldi, G., Kwaku Kyem, P.  A., McCall, M., & Weiner, D. (2006). Participatory spatial information management and communication in developing countries. Electronic Journal of Information Systems in Developing Countries, 25(1), 1–9. Seijo, C., Calado, H., McClintock, W. J., Gil, A., & Fonseca, C. (2021). Mapping recreational ecosystem services from stakeholders’ perspective in the Azores. One Ecosystem, 6, 1–17. https:// doi.org/10.3897/oneeco.6.e65751 White, C., Halpern, B. S., & Kappel, C. V. (2012). Ecosystem service tradeoff analysis reveals the value of marine spatial planning for multiple ocean uses. Proceedings of the National Academy of Sciences, 109(12), 4696–4701.

Chapter 7

Sketch Map Tool Carolin Klonner and Jeantyl Norze

Abstract  Participatory methods are a great support to engage residents into disaster risk reduction. Their experience and knowledge about previous disasters, such as floodings, can support the preparation for future events. How can their knowledge be captured in an easy and fast way so that local authorities can use the methods themselves? How can the results be made available in a digital form for the use within disaster risk reduction processes? These questions are answered by the Sketch Map Tool, which combines analogue data collection with digital data processing. A paper map with OpenStreetMap (OSM) data is used for participatory mapping with residents. These sketch maps with the markings of the participants can be uploaded to the Sketch Map Tool website where they are automatically georeferenced. Results can be downloaded and used in a geoinformation system (GIS) for further risk analyzes or to create risk perception maps based on the collected information from all participants. The Sketch Map Tool can also be used in combination with questionnaires in order to gain insights into the background of the participants and further information about the disaster. The quality of the OSM data can be analyzed beforehand to evaluate whether participants can easily orientate on the map during the mapping activity. The automation of the steps allows the use of the tool with little technical knowledge. Further, it is an open-source software so that communities with limited resources can also use it for their own projects. When using the Sketch Map Tool, the users are encouraged to follow appropriate

During the finalizing of the book, the Sketch Map Tool was undergoing some changes. Please check the Sketch Map Tool website for more information (https://www.geog.uni-­heidelberg.de/ gis/sketchmaptool_en.html). We will also provide the link to the new version of the tool there. C. Klonner (*) Institute of Geography, Heidelberg University, Heidelberg, Germany e-mail: [email protected] J. Norze University of Connecticut, Storrs, CT, USA e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 C. M. Burnett (ed.), Evaluating Participatory Mapping Software, https://doi.org/10.1007/978-3-031-19594-5_7

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guidelines and regulations regarding data protection. It is the duty of everyone to ensure good practice. Keywords  Participatory mapping · Local knowledge · Sketch map tool · Disaster risk reduction

7.1 General Information Name of Application: Sketch Map Tool Name of Developer: GIScience Heidelberg (Heidelberg University), Heidelberg Institute for Geoinformation Technology Name of Funder: Various (see website) Type of System Software: Web Application Type of Programming Language: Front-end: JavaScript, (HTML, CSS); Back-­ end: Python API Availability: N/A Features: Analysis of OpenStreetMap (OSM) data quality for use in sketch maps; generation of OSM-based sketch maps to be printed out; automatic georeferencing of sketch maps in uploaded images and automatic marking detection. Cost: Free Type of Data Collected: The quality analysis focuses on: Density of certain landmarks mapped in an area in OSM, shares of different types of landmarks in this area, yearly development of amenity feature mapping, yearly development of highway feature mapping, average time passed since the last edit of amenity and highway features, shares of tagged sources. The sketch maps can collect all kinds of markings such as risk perception. Overview: Sketch Map Tool combines analogue data collection with digital data processing using OpenStreetMap (OSM). Sketch maps with the markings of the participants can be uploaded to the Sketch Map Tool website where they are automatically georeferenced. Results can be downloaded and used in a geoinformation system (GIS) for further risk analyzes or to create risk perception maps based on the collected information from all participants. The Sketch Map Tool can also be used in combination with questionnaires to gain insights into the background of the participants and further information about the disaster. The quality of the OSM data can be analyzed beforehand to evaluate whether participants can easily orientate on the map during the mapping activity. The automation of the steps allows the use of the tool with little technical knowledge. Further, it is an open-source software so that communities with limited resources can also use it for their own projects. When using the Sketch Map Tool, the users are encouraged to follow appropriate guidelines and regulations regarding data protection. It is the duty of everyone to ensure good practice.

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7.2 Ethics Participatory mapping software like the Sketch Map tool has become very popular among geographical information practitioners around the world and their widespread use has been well documented in the literature (McCall, 2006). There has been a great excitement about using geo-referenced data to display visually human physical, biological, and social-cultural features and making the information readily available to the public (Rambaldi et al., 2006). The discovery of local people’s ability to make their own maps has been a revolutionary breakthrough (Chambers, 2006). However, the visualization of place-specific local knowledge and its public consumption can be problematic because failing to be on a map may sometimes mean a lack of proof of existence (Rambaldi et al., 2006, p. 107). For instance, the issues of hard-to-reach populations are often unknown, neglected or misunderstood because of their exclusion from research studies, which subsequently leads to unequal distribution of resources. In addition, the inventory of people’s intangible heritage through geo-referencing can raise legitimate ethical concerns (Rambaldi et al., 2006). As empowering as a participatory mapping software can be, it can lead to potential exploitation of marginalized individuals and communities (Rambaldi et al., 2006). It is important to understand that each culture has its own values and moral code of conduct, and it is to everyone’s (practitioners, researchers, facilitators, etc.) duty to ensure good practice (ibid). It is also critically important that professionals who use the Sketch Map Tool are honest and transparent in their approach throughout the mapping process. They must clearly state the purpose, benefits, and risks of their projects in a format and language that meet the educational level and learning styles of the participants. No claims should be made about the results that are beyond their power to achieve (Rambaldi et al., 2006). In addition, the participants should be made aware of how the information being collected will be used and that no harm will come to them because of their participation in the project or study. The Sketch Map Tool users must have a comprehensive understanding of the intended and unintended consequences of their actions (Fox et al., 2005) and incorporate adequate safeguards in the project or research proposal, according to DHHS and FDA regulations. The users should also understand that people’s participation in their project must be voluntary and therefore opportunities should be given to opt out without fear of losing any entitlements. Further, they should seek the consent and/or assent of the participants before they enroll in the project. In countries that have ethics boards or institutional review boards (IRBs), users of the Sketch Map Tool must seek approval of their project protocol to guarantee the rights of participants or lack of thereof, they must seek approval from leaders (e.g., spiritual) or grassroot village elders to protect the right of the potential participants involved in a selected project. This is critical especially for vulnerable groups. Any amendments in a research or project protocol should be reviewed and approved by the ethics boards.

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Below are some of the major ethical concerns that the users of the Sketch Map Tool should consider when involving local community members in their project. Taking people’s time: The time of vulnerable populations and low-income families is valuable. They often must work multiple jobs to provide for their families. The users of Sketch Map Tool need to be cognizant of the situation of vulnerable populations and be willing to work with them around their schedule. In addition, it is important that they assess the benefits of the projects for the potential participants to determine whether they are worth the participants’ valuable time and efforts. Research projects with vulnerable populations are justified if only reasonable benefits are foreseen, in compliance with the local regulations (ICH GCP, 1996; WMA, 2008). Raising people’s expectations: Vulnerable groups face multiple challenges including natural disasters and social hardship. They often struggle to find help; so participating in research projects, especially in moments of crisis might raise their expectations; which often leads to deceptions (Fagerholm, 2014). Therefore, honesty and transparency during the mapping process are critically important to avoid creating expectations that the users of the Sketch Map Tool cannot meet. Violation of intellectual property rights: The Sketch Map Tool as a participatory mapping software involves participants in the design and development process, which is very important because it empowers the individuals and gives them a sense of ownership, which is also important for the sustainability of the tool. However, using people’s information for other purposes including outsiders’ financial gain that were not clearly communicated to them is a violation of their rights. For instance, the intellectual property (IP) rights of indigenous people have been exploited in many ways. Their resources and knowledge have been collected and patented without due recognition or benefits distributed to them (Davis, 1997). Harm (emotional and physical safety): Vulnerable populations face a lot of problems that often drain them emotionally. They often live in high-risk natural disaster areas and high crime areas. The users of the Sketch Map Tool must guarantee that their information will be secure and protected and therefore their information will not be shared or used against them. In addition, their participation in a project can affect their self-worth or self-esteem if they believe in false feedback from an evaluative task or test (Oczak & Niedźwieńska, 2007). Psychological discomfort can also result from the interaction with a researcher or practitioner (Broder, 1998). The users of the Sketch Map Tool should be thoughtful about the participants’ safety needs.

7.3 Cost The costs of a software or hardware can be a barrier for participatory processes. Haworth et al. (2016) mention several advantages but also disadvantages of participatory mapping based on paper and on a digital form. Resource costs for paper mapping is one of the disadvantages (Haworth et al., 2016). Paper mapping requires

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access to a printer, paper and pens. However, Haworth et al. (2016) do not mention that digital mapping also requires resource costs such as for internet access, software fees and technical devices. The Sketch Map Tool is free of charge and users can decide themselves if they would like to do paper mapping or if they do not have the required equipment and prefer to do the mapping in a digital form. For the analysis of the results, the installation of a geoinformation system (GIS) is required; this could be, for example, QGIS, which is also free. The users will need internet access at some point to use the Sketch Map Tool function for the OSM quality analysis of the base map and to generate this map. Further, the users will need access to a printer to print out the maps that will be used in the field. For markings, the users require some pens. After data collection, a smartphone, digital camera, or scanner is needed to take a picture of the sketch maps. Overall, it is important to consider resources for participants because especially in low-income households in risk areas they need to have some compensation for the time they miss at their work (Rambaldi et al., 2006).

7.4 Technical Level There are various projects based on sketch mapping. The Sea Sketch Project is already in use for several years and Burnett (2020) suggests how the participatory process can be improved. She uses surveys and semi-structured interviews to collect information and concludes in five suggestions. We will focus on the following two: data should be visualized for non-technical experts, and it should be aimed at tools that do not need facilitators, sometimes referred to as “chauffeurs.” We will address these two points in this chapter because the Sketch Map Tool is already covering them to some extent: it can be used with little technical knowledge and local authorities can conduct data collection and mapping events themselves. Currently, we are working together with members of the German Red Cross as facilitators of the data collection in our use cases. As soon as the tools are ready for the release and all features are working, we hope that in some areas local authorities can apply this method without facilitators from other organizations. Sketch Mapping can be conducted on manifold base maps such as OSM. Several tools provide these base maps such as the Field Papers website. The Field Papers approach is already a great support because there is a QR code on each map that allows automatic georeferencing (fieldpapers.org). Therefore, you do not need to conduct a time consuming and error prone manual georeferencing of your map. The purpose of Field Papers is to collect OSM data in your area in an easy-to-use approach. Further, the maps can also be used to collect information about risk perception of flooding events (Klonner et al., 2021b). However, you still need someone who is experienced in OSM in order to decide whether the OSM data of the base map is sufficient for the sketch map application and whether any problems should be expected when using them. Another disadvantage is the size of the Field Papers. Group mapping on larger maps can give valuable insights into local knowledge

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(Klonner & Blessing, 2019, Bustillos Ardaya et al., 2019). The disadvantage of the Field Papers is that the maps are difficult to read due to the low resolution when printed in DIN A0. Here, the Sketch Map Tool offers new solutions (Klonner et al., 2021a). The tool is based on the idea of the Field Papers and advances this format. So it uses the QR code, but it has an additional OSM quality analysis. In this way, you get to know if the OSM data in your study area is sufficient for sketch mapping and whether you should expect any problems for which you might take countermeasures. You also get recommendations such as that you might organize a mapathon to improve sparse OSM data. Further, it offers several sizes for printing, including DIN A0, in a high resolution. In addition, the tool includes an automatic marking detection and therefore you do not need to digitize the marked areas by the participants manually. This data is provided in a digital georeferenced format so that you can directly use it in QGIS. For this final analysis you will need some technical skills but on the Sketch Map Tool website you find a video and PDF tutorial with step-by-step instructions. Overall, a short introduction to the tool is sufficient and then it can be applied for a case study. The participants themselves only need to use a pen to mark the areas at risk. Therefore, they do not need technical skills, they only need to be familiar with a map. That is why it is so important to do the OSM quality check at the beginning in order to find out if sufficient landmarks such as churches, bus stops and supermarkets are available so that the participants can orient themselves on the map. With respect to the results, the Sketch Map Tool also has a low technical barrier. The marked areas of the participants are used for an analysis of overlapping areas in order to present them in a form of heat map. This analysis can be done automatically based on a QGIS script. The user only needs to color the maps in QGIS according to his/her needs. In a future step, this visualization of the result maps could also be included in the Sketch Map Tool so that the users only need to upload the marked Sketch Maps and will get a map, which visualizes the results in the required form.

7.5 Inclusiveness Using paper and pen mapping approaches allows users to bridge the digital divide and include people without internet access or required technical devices. Especially in the case of group mapping, the paper format plays an important role because the participants can stand around the map and discuss together what to mark on the map. However, it is difficult to transfer the results of these mapping activities into a digital format, which is important for computerized analyses as well as comparisons and combinations with other geographic data. On the other hand, there are many participatory mapping approaches which collect geographical information via tablets and smartphones and therefore their results are already digital. The disadvantage here is that you might exclude people who do not have the required equipment. The Sketch Map Tool combines the advantages of both approaches: While paper

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and pen during the sketch mapping activity allow an easy-to-use method to visualize local knowledge, the website of the Sketch Map Tool enables to transfer this analogue information into a digital form in a fast way. Overall, the following devices are required: First, users need a computer with internet access to access the Sketch Map Tool website for the OSM quality analysis, the map generation as well as the map upload. If the users have sufficient knowledge, they can also host their own local instance of the Sketch Map Tool based on the code in the GitHub repository. In this case they can download the OSM data for their areas of interest beforehand, so an internet connection is only required for the quality analyses, but neither the sketch map generation nor the upload processing. If an analogue mapping is planned, users need a printer, for the base map for the participatory mapping as well as for printing the result map in the end if they want to give the information back to the community. Colored pens and a scanner or camera (mobile phone) for taking a picture of the sketch maps for the upload to the website of the Sketch Map Tool. There are two different levels of participation and thus, there are two different levels of difficulty. The first level is the role of the facilitator who accesses the Sketch Map Tool, prepares the base maps, conducts the mapping activity with citizens, uploads the sketch maps again to the website, and prepares the analyzed results. At this level, some technical knowledge is required. On the website there are some technical terms, but the main functions are described in clear terms: generation, analysis, and upload. The use of the Sketch Map Tool can be also learned during a short workshop. Furthermore, the required equipment needs to be provided. The second level is the role of the participants during the participatory mapping event. They do not need to have technical knowledge or any devices available. It would be important that participants have some map literacy, so that they can mark their experiences on the map themselves. It might be possible to offer a workshop about map literacy before the sketch mapping takes place. Map literacy is an essential part for effective participatory mapping, and it can be a limitation. According to Brown and Kyttä (2018) this limitation might be overcome by digital technology which can support map reading and understanding. However, this might also lead to an exclusion of people who might not be able to use such technical devices as mentioned above. The Sketch Map Tool offers with the group mapping on paper-based maps the opportunity to participate not only to people who lack the required digital devices and technical knowledge but also to people who are illiterate. In group mapping events they can tell their story and other group members can mark the areas in the map. Currently, the Sketch Map Tool is offering two languages: English and Portuguese. In future, many more languages will be included so that there will not be a language barrier. User friendliness is continuously evaluated by GIS experts, students, practitioners, and local citizens (for example, during the application in use cases by the German Red Cross) via questionnaires (partly based on the approach by Ballatore et al. (2019)), interviews, think aloud tests and real use case scenarios.

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We are still in the prototype phase of the Sketch Map Tool and data was already collected in some projects. A future step will include the discussion of the results with the participants themselves to clarify whether their contributions are displayed in a way to which they agree.

7.6 Data Accuracy When it comes to data collected by citizens, it is essential to have some quality checks included. Brown et al. (2018) refers to Spielman (2014) and point out the validity-asaccuracy and validity-as-credibility. The first one can also be rephrased as external quality assessment because the data is compared to authoritative data. The latter looks closer at the data itself and the contributors, thus it is an intrinsic quality analysis. The work with sketch maps covers both aspects. The external quality assessment of sketch maps is covered in a study by Klonner et al. (2021b) about capturing flood risk perception via sketch maps. They visually compared the results of the participatory mapping of flood risk perception to official flood maps and concluded that the risk perception maps can be used as an additional complementing data set to enrich official data or to update such maps based on historical data. In areas where no other data is available, the risk perception maps have an essential role. The intrinsic quality is considered in several levels within the Sketch Map Tool because there are various factors that ensure and increase accuracy. First, the Sketch Map Tool uses OSM as a base map. Therefore, the markings of the participants, for example their experiences of flood extents, are already geographic data because they are based on the buildings and streets from OSM. Second, the accuracy of the markings depends on the quality of the OSM data of the study area. The OSM quality analyses within the Sketch Map Tool help to ensure that a sufficient quality is given. If there are not enough landmarks for participants to orient on the map and to correctly mark the areas, the analysis gives you a recommendation to improve the base map first. The OSM quality analysis is based on the Application Programming Interface (API) provided by the Heidelberg Institute for Geoinformation Technology (HeiGIT). The advantage of the Sketch Map Tool in comparison to other participatory approaches based on white paper or authoritative map data is that OSM can be edited and thus, the base maps can directly be improved. This mapping of missing features can be done with the residents or with the help of the OSM community. The advantage of mapping with local people, for example together with schools, is the capture of local knowledge. Thus, the base map will include the important landmarks, which participants of the future sketch mapping will need to correctly mark their experiences. A third point is the automatic georeferencing of the sketch maps, which makes error- prone manual georeferencing obsolete. The same applies for the automatic color detection of the markings, which overcomes potential errors during manual digitization of the markings. Finally, the collected markings can be analyzed, and the results can be presented as overlap maps; this means that the more participants have marked a specific area as flood areas, the darker the color. This allows another intrinsic check because outliers can be detected.

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Of course, one needs to keep in mind that there might be some bias towards main streets which are more present in the perception of the participants; however, the results still give a hint towards affected areas. Local authorities can install monitoring devices, for example, in order to verify the areas which were perceived as flood risk areas. Another bias mentioned by Brown et al. (2018) might occur based on the digital devices. The Sketch Map Tool offers a solution to overcome this digital and educational divide by offering a paper-based approach for mapping. After collecting and analyzing the data, it is essential to discuss the results with the participants again. There are two reasons for this step. First, the citizens can comment on the results and point out problems with aggregations or with sensitive data. Second, they see that their contribution matters and their awareness and feeling of responsibility might increase. This is essential for their own measures of risk reduction.

7.7 Data Privacy As previously stated, the Sketch Map Tool is an open-source participatory mapping tool that builds a sense of ownership of the local people in the data collection and mapping process. We recognize that there are some legal and ethical challenges associated with open-source data. We encourage users of the Sketch Map Tool to avoid uploading sensitive data on the Sketch Map Tool because of the risk of having data stolen, hacked, or seized for malicious purposes. In addition, disclosing sensitive information may undermine the sovereignty of certain communities or groups, especially minority groups such as indigenous people. We also encourage the users to scrutinize existing legislations of local governments about data privacy and security and adhere to them. The tool indicates to the users not to upload sensitive data (including examples of what that is). In general, data is stored on the server of the Heidelberg Institute for Geoinformation Technology (HeiGIT). It is an open-source tool and therefore you can also install it locally and have your own server. In this way, data is just stored locally, and the privacy depends on your own settings. Transparency is provided by the additional information about the OSM quality analysis and the tutorial. In this way, the users know what is happening “behind the scenes”. Moreover, the contact address is provided, and so further information can be acquired.

7.8 Analytical Capacity The Sketch Map Tool website has a section for each part of the tool: the analysis function, the generation of the base map for your sketch mapping activity, and the upload section. They are outlined in an easy, accessible way (see Fig. 7.1).

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Fig. 7.1  Sketch Map Tool website with the three different functions: Selection and Analysis, Generation, and Upload

Brown and Kyttä (2018) identified several issues for improving the effectiveness of participatory mapping. One of them is the need of statistical, visual, and spatial analysis techniques, which are person- and place-based (ibid). The Sketch Map Tool offers an analysis technique covering the statistical and spatial analysis of OSM data. This analysis of the OSM base data of the required study area gives the user feedback whether the data is sufficient for adequate sketch mapping. This intrinsic OSM data analysis is based on the OpenStreetMap History Database (OSHDB) and the Ohsome API, both developed by the HeiGIT. This allows aggregation and filtering of OSM data for a specific study area. The aim of the Sketch Map Tool is to provide a sustainable tool which can be used by local communities themselves. Therefore, possible interpretations of the results are explained to the user (see Fig. 7.2). A traffic light represents the results in an easy way: A green traffic light means that the results indicate that the base data is likely sufficient for the sketch mapping. Orange or even red indicates that the current OSM data might not be appropriate for sketch mapping. Recommendations are given to the user, for example, to conduct an OSM mapping event to improve the base map data. In case the user wants to know more about the results, the website offers an in-depth report of the results as a PDF document for download (see Fig. 7.2). Diagrams and further literature references are included. For further details see Klonner et al. (2021a).

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Fig. 7.2  Traffic light result in the PDF report, which presents the results of the OSM analysis of the study area

In line with Brown and Kyttä’s (2018) suggestion, one can count another part of the Sketch Map Tool as a person- and spatial-based analysis technique. The marking of the participants can be automatically analyzed with respect to overlapping areas and the user will get a dataset for usage in QGIS with which it is possible to visualize heat maps. Furthermore, it is also possible to easily add questionnaires with information about the participants via free tools such as KoBo Toolbox. Such a place-based questionnaire allows to directly link the data to the sketch map of the respective participant (the interviewer just needs to add an ID to the map). This combination of sketch maps and questionnaires was also used by Klonner et  al. (2021b). To increase the user friendliness of the tool, there are also step-by-step tutorials in the form of a video and a PDF document, which are available on the tool website. These tutorials are made for users with little technical knowledge and can also be used for mapping with students. Moreover, the website provides an FAQ section with the main questions that may arise when using the tool. In this way, the technical barrier of usage for mapping and for the analysis afterwards is kept low.

7.9 Visualization Capacity Visual research methods can support participatory processes but require critical awareness and reflection of the facilitator (Simpson Reeves, 2015). The author points out that local ownership and horizontal dialogue are essential for such

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processes. The concept of the Sketch Map Tool addresses several aspects of this horizontal dialogue. The group paper mapping offers access to dialogue for people from different backgrounds and educational as well as technical levels of knowledge. “Although these factors may never be completely neutralized, they should be recognized as potential barriers to successful dialogue” (Simpson Reeves, 2015, p. 3329). So, it is important to keep these potential barriers in mind during the work with the Sketch Map Tool. Furthermore, local ownership of the data is given. The results of the data collection are visualized in a way that the community can use the data for their own purposes and for decision making. In detail, the Sketch Map Tool offers different aspects of visualization. First, the results of the OSM fitness for use analysis are visualized in a traffic light. Moreover, detailed information is outlined in a report, which also includes several diagrams. Second, the local knowledge of the participants is visualized as markings on paper maps, which are provided by the Sketch Map Tool for printing. These sketch maps are uploaded, which results in a downloadable GeoTIFF file. These files can be used in QGIS for analysis. If the user wants to have the markings digitized automatically, the tool also provides a function for this. The markings can be downloaded as shapefiles and used for further calculations in a GIS, e.g., QGIS. Klonner et al. (2021b) present the option of overlapping the marked areas so that the darker the color, the more participants named the area as risk area. In this way, the results can be visually compared to flood maps based on authoritative data. The authors used Field Papers for their study and not only had to manually digitize the markings but also to do the overlap count themselves (Klonner et al., 2021b). The Sketch Map Tool offers these steps as automatic functions, and the user only needs to classify and color the overlapping areas. A step-by-step instruction for this final visualization is provided in the PDF tutorial.

7.10 Openness The Sketch Map Tool is open source with an Affero General Public License (AGPL-3.0) and you can host the application on your own server or PC. As previously described, you will have different options for downloading the result files: the georeferenced sketch maps with markings as GeoTIFF files, the automatically detected markings as shapefiles even as a QGIS project including the shapefiles of the markings. Moreover, the results of the OSM base data analysis can be downloaded as a PDF file. The sketch maps for printing are provided in the same format. It is important to offer such a tool for free to allow local authorities to apply sketch mapping even if they do not have enough monetary resources for proprietary tools. However, apart from being open source, there is another important point to consider: The usability for lay people. Wubishet et al. (2013) point out that open-source projects are often tools from developers for developers and thus, they stay in a closed space due to technical barriers. Therefore, they conclude that “a truly participative process is not one that allows anyone to contribute freely, but the one that

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provides the infrastructure that users need to acquire the skills to participate in the development process” (p. 192). In this line the Sketch Map Tool is constantly evaluated to make the final version for release a joint project. In addition, evaluations will continue thereafter to always keep the tool user friendly. The availability of the code in the GitHub repository makes it possible for users to add issues with error descriptions or feature requests, for example, hence, they can interact with the developers and give feedback. A step-by-step tutorial provides information needed during the different steps when conducting your own study. Furthermore, training is offered to gain both knowledge about the application of the tool and about the concept of participatory mapping and the analysis functions. Depending on the project or use case, the training is offered for free or at low cost. Within only a few hours people are ready to work with the Sketch Map Tool.

7.11 Accessibility The Sketch Map Tool provides the option to do the participatory mapping with paper and pen. However, for the analysis parts and the generation of the maps, internet access is needed. This restriction is overcome by hosting an own instance and downloading OSM data beforehand; in some remote regions with poor connections this can be a great advantage. Thus, the analyses and the OSM downloads can be done at a place with stable internet connection and then the tool is taken to the field where the work is done completely offline. The application is easy to use and after a short introduction a facilitator can do the mapping together with the participants. The results of the OSM analyses are made accessible with detailed information about the background of the calculations. Other aspects of access to the tool such as language, technical barriers, inclusiveness, and costs are already discussed in the previous sections.

7.12 Brief Use Case The first prototype of the Sketch Map Tool was developed within the Waterproofing Data Project based on experiences in the field during flood risk perception mapping in Brazil. Now it is applied in use cases with the German Red Cross (GRC) and developed further based on the feedback from the use cases. The first cooperation was with the GRC from Madagascar to collect local information for flood risk reduction in Antananarivo. Funding by the GRC allowed the development of additional functions of the Sketch Map Tool. The applicability of the Sketch Map Tool was evaluated via interviews with the local GRC group and an international GRC team member. The second use case was in the cities of Maputo and Matola in Mozambique. The Sketch Map Tool was used to support the mapping activities

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within the Urban Disaster Risk Reduction Project, namely for collecting local knowledge about flooding in Maputo. In the following, this second use case is depicted in more detail and the use of the Sketch Map Tool is evaluated based on the experience of Michela Sotomane, mapping intern at the Mozambican Red Cross (CVM). In a project financed by GRC, Michela Sotomane from the CVM worked with the Sketch Map Tool and the first step was the analysis of the selection of the study area and the OSM quality analysis for the selected study area. The latter resulted in a green traffic light, which means that the base data (such as landmarks) is likely sufficient for participants to orientate on the map during the participatory mapping. Furthermore, it is indicated that some of the OSM data was acquired during mapping projects such as the Mobility and Gender Mapping Project (see Fig. 7.3). In a next step, the map for the sketch mapping is generated (see Fig. 7.4). The base map was used in DIN A1 for a participatory mapping event with the local community of Maputo, which took place in February 2022 (see Fig. 7.5). Some areas were not sufficiently represented by the OSM data and therefore, the community relied on satellite images to identify specific areas on the map. This was very useful feedback and therefore, a future step will be the inclusion of satellite imagery as a base layer to the Sketch Map Tool. The work together with the participants resulted in a Sketch Map with information about flood risk areas (see Fig. 7.6). Afterwards, the map was uploaded to the website of the Sketch Map Tool. The map was automatically georeferenced resulting in a GeoTIFF of the map including the markings. Furthermore, the markings are detected automatically and provided as shapefiles for further use in a GIS such as the open-source tool QGIS. A flood risk perception map can be designed on this base data from the sketch mapping.

Fig. 7.3  Analysis of the study area. (Screenshot: Michela Sotomane, February 2022)

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Fig. 7.4  Generated base map for the sketch mapping in Maputo City. The QR Code is used for the automatic georeferencing. (Screenshot: Michela Sotomane, February 2022)

Fig. 7.5  Mapping with the community. (Picture: Alexandra György, Maputo City, February 2022)

The Sketch Map Tool is still under development and therefore, there were some issues with the color detection. All the markings were detected as areas. The evaluation resulted in the suggestion of adding another option so that markings are just detected as areas when the marking has a certain thickness. Below this threshold of thickness, a line will be detected. Furthermore, the color detection is limited to blue and red and more colors would be useful for additional features collected during the mapping. This is also an additional step for future development.

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Fig. 7.6  Picture of the Sketch Map with information about flood risk areas provided by the local community. (Picture: Michela Sotomane, Maputo City, February 2022)

The overall conclusion was that the mapping process with the Sketch Map Tool was much faster than the previous way of mapping. It was a great support to be able to extract a map in a very short time, to have a graphic scale and a standardized size of the map as well as an automatic georeferencing of the result map. There were some obstacles, but the digitizing took only a few minutes because only some minor errors of the automatic detection needed to be corrected. The tool not only saved time but also provided analyses to get insights into the map quality of the selected areas and to improve the local OSM data. It can be considered as a support for both mappers and communities.

7.13 Comments and Recommendations The Sketch Map Tool was developed within the Waterproofing Data Project and is now a tool of the HeiGIT. It is still under development and there is a long list of planned future improvements. The tool is continuously released in the GitHub repository. Some improvements are still in work before all functions described in this chapter are completely available. We are very happy to see that the tool is

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already used within real-life projects and can support humanitarian organizations in their important work. The Sketch Map Tool provides an easy-to-use tool for the collection of local knowledge, perception of risk, fear, heat and/or memories about historic events. Currently, the focus of use cases is on flooding, but it would be great to apply the tool also to other use cases to cover more disaster types and other topics of interest such as the support of city planning with respect to areas of noise or fear in a city. In addition, the Sketch Map Tool can be used in combination with questionnaire tools such as Open Data Kit or KoBoToolbox. The interviewer can add the ID of a specific sketch map to the questionnaire and in this way, information about the participants as well as additional information about the risk perception can be collected and combined with the sketch map data. Klonner et al. (2021b) used such a combination to find out the differences in risk perception depending on characteristics of the participants. In conclusion, it is important to make the collected data also available for the citizens who participated and to engage them actively in the process of risk reduction. We as researchers need, on the one hand, to listen carefully to the real problems of the communities and adapt our tools and methods to the needs of the citizens (Rambaldi et al., 2006). On the other hand, it is important to communicate findings and research in an understandable way to the local communities (Fagerholm, 2014). Visualizations such as maps of risk perception can be of great support for such science communication. As the Sketch Map Tool provides users with opportunities to involve local communities in the mapping process, it is also recommended that they incorporate adequate safeguards in the projects.

References Ballatore, A., McClintock, W., Goldberg, G., & Kuhn, W. (2019, June). Towards a usability scale for participatory GIS.  In The international conference on geographic information science (pp. 327–348). Springer. Broder, A. (1998). Deception can be acceptable. American Psychologist, 53(7), 805–806. Brown, G., & Kyttä, M. (2018). Key issues and priorities in participatory mapping: Toward integration or increased specialization? Applied Geography, 95, 1–8. Brown, G., McAlpine, C., Rhodes, J., Lunney, D., Goldingay, R., Fielding, K., et  al. (2018). Assessing the validity of crowdsourced wildlife observations for conservation using public participatory mapping methods. Biological Conservation, 227, 141–151. Bustillos Ardaya, A., Evers, M. & Ribbe, L. (2019). Integrated participatory methodologies for disaster risk reduction: Tools to analyze complex systems through participatory processes in Brazil. In Strategies and tools for a sustainable rural, Rio de Janeiro, ed. U. Nehren, S. Schlüter, C. Raedig, D. Sattler, and H. Hissa, 361–376. Berlin: Springer. Burnett, C. M. (2020). Incorporating the participatory process in the design of geospatial support tools: Lessons learned from SeaSketch. Environmental Modelling & Software, 127, 104678. Chambers, R. (2006). Participatory mapping and geographic information systems: Whose map? Who is empowered and who disempowered? Who gains and who loses? The Electronic Journal of Information Systems in Developing Countries, 25(1), 1–11.

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Davis, M. (1997). Indigeneous people and intellectual property rights. Parliament of Australia. Retrieved from: Indigenous Peoples and Intellectual Property Rights – Parliament of Australia (aph.gov.au). Fagerholm, N. (2014). 14 Whose knowledge, whose benefit? Ethical challenges of participatory mapping. In J.  Lunn (Ed.), Fieldwork in the global south: ethical challenges and dilemmas (pp. 158–169). Routledge. Fox, J., et al. (2005). Mapping power: Ironic effects of spatial information technology in mapping communities, ethics values, practice. East-West Center. See: www.eastwestcenter.org/res-­rp-­ publicationdetails.asp?pub_ID=1719 Haworth, B., Whittaker, J., & Bruce, E. (2016). Assessing the application and value of participatory mapping for community bushfire preparation. Applied Geography, 76, 115–127. ICH GCP – International Conference on Harmonisation of Technical Requirements for Registration of Pharmaceuticals for Human Use ICH Harmonised Tripartite Guideline, Guideline for Good Clinical Practice E6(R1) Current Step 4 version dated 10 June 1996. Klonner, C. & Blessing, L. (2019). Gathering local knowledge for disaster risk reduction: The use of sketch maps in group discussions. In Proceedings of the ISCRAM 2019 conference, Valencia, Spain (pp. 1397–1398). Klonner, C., Hartmann, M., Dischl, R., Djami, L., Anderson, L., Raifer, M., Lima-Silva, F., Degrossi, L. C., Zipf, A., & de Albuquerque, J. P. (2021a). The sketch map tool facilitates the assessment of OpenStreetMap data for participatory mapping. ISPRS International Journal of Geo-Information., 10, 130. https://doi.org/10.3390/ijgi10030130 Klonner, C., Usón, T. J., Aeschbach, N., & Höfle, B. (2021b). Participatory mapping and visualization of local knowledge: An example from Eberbach, Germany. International Journal of Disaster Risk Science., 12(1), 56–71. https://doi.org/10.1007/s13753-­020-­00312-­8 McCall, MK. (2006). PGIS–PSP–IK–(CB)NRM: Applying Participatory-GIS and Participatory Mapping to participatory spatial planning and to local–level land & land resources management utilizing indigenous & local spatial knowledge: a bibliography. Oczak, M., & Niedźwieńska, A. (2007). Debriefing in deceptive research: A proposed new procedure. Journal of Empirical Research on Human Research Ethics, 2(3), 49–59. [PubMed: 19385851]. Rambaldi, G., Chambers, R., McCall, R., & Fox, J. (2006). Practical ethics for PGIS practitioners, facilitators, technology intermediaries and researchers. Participatory Learning and Action, 54(1), 106–113. Spielman, S. E. (2014). Spatial collective intelligence? Credibility, accuracy, and volunteered geographic information. Cartographic Geography Information Science, 41(2), 115–124. Simpson Reeves, Laura. (2015). Visualizing Participatory Development Communication in Social Change Processes: Challenging the Notion that Visual Research Methods are Inherently Participatory. International Journal of Communication. 9, 3327–3346. WMA declaration of Helsinki-ethical principles for medical research involving human subjects-­59th WMA general assembly, Seoul, Korea, October 2008. Wubishet, Z. S., Bygstad, B., & Tsiavos, P. (2013). A participation paradox: Seeking the missing link between free/open source software and participatory design. Journal of Advances in Information Technology, 4(4), 181–193.

Chapter 8

Survey123 for ArcGIS Online Sabine Hennig, Robert Vogler, and Jiří Pánek

Abstract Survey123 for ArcGIS Online is a web application within the Environmental Systems Research Institute (Esri) ecosystem; thus, it is not free of charge. Its use relies on the purchase of one of the available ESRI’s pricing and licensing levels. Survey123 is used to generate smart forms that contain map-based questions, among other things. Depending on the tool used, Survey123 Web Designer or Survey123 Connect for ArcGIS, simple and complex smart forms can be created, including different features such as multimedia elements, calculations, and device/user properties. To fill out smart forms, which can occur both online and offline, the survey can be opened in a browser or in the Survey123 field app. However, for many aspects, such as ethical issues, analytical and visualization capacities, inclusiveness, and openness, the use of other Esri ecosystem products, such as ArcGIS Online web maps, ArcGIS online web apps, ArcGIS Dashboards, ArcGIS Online StoryMaps, ArcGIS Experience Builder, and ArcGIS Hub, play an important role. Keywords  ArcGIS · ESRI · GIS · StoryMaps

8.1 General Information Name of Application: ArcGIS Survey123 Name of Developer: Esri Name of Funder: Esri Type of System Software: Online, Software as a Service (SaaS) S. Hennig · R. Vogler Paris Lodron University Salzburg, Salzburg, Austria e-mail: [email protected]; [email protected] J. Pánek (*) Palacky University Olomouc, Olomouc, Czech Republic e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 C. M. Burnett (ed.), Evaluating Participatory Mapping Software, https://doi.org/10.1007/978-3-031-19594-5_8

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Type of Programming Language: Python API Availability: JavaScript API for the survey, ArcGIS API for Python for further actions Features: • • • • • • • • • •

Non-spatial questions with multiple answer options, such as: Singleline text Multiline text Single choice Single choice grid Multiple choice Dropdown Rating Likert Scale Spatial questions – possibility to locate answer in the map (points or lines or polygons) • Ability to add images/audio files Cost: $500–$3800 per year Type of Data Collected: Geographic and descriptive, as well as attachments Overview: Survey123 is an online survey administration software application developed and offered by Esri and part of the ArcGIS Online ecosystem. It allows users to create, publish and share online surveys. As with other survey tools, the collected information can be visualized and initially analyzed online and additionally exported for further and advanced analysis. Compared to other survey tools, the unique feature of Survey123 is that  – despite conventional question types and attachment upload possibilities – a location can be surveyed and be added as points, lines, or polygons by the survey respondents. This can be done manually (e.g., via setting a pin on a map) or based on the device location if the data is gathered with GPS-enabled mobile devices in the field. The collected data can then be exported to different file types (such as shapefile or KML) or can be embedded and visualized as a feature layer within the ArcGIS Online ecosystem (in e.g., web maps, story maps or interactive dashboards). This can be done also in real-time, because once the survey is published, a feature layer is generated and its data model corresponds with the survey, which allows for setting up the visualization specifications even before the data is gathered. This makes Survey123 a powerful tool for participatory mapping initiatives.

8.2 Ethics Participatory mapping initiatives require consideration of various ethical concerns (Chambers, 2006; Rambaldi et al., 2006; URISA, 2013). Apart from ethical concerns that rely on the attitude of the responsible party of an initiative (e.g., being aware of consequences and risks, admitting mistakes), other ethical issues require

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appropriate solutions in connection with the participatory mapping tool. For instance, the provision of information, giving feedback, obtaining participants’ consent of use, and developing and implementing a suitable, particularly user-centered participation and survey design. These points can be addressed using Survey123 for ArcGIS Online and other Esri ecosystem products.

8.2.1 Provision of Information Providing information to the participants is a key issue in participatory initiatives. This relates to meeting participants’ needs for openness, realistic expectations, and supporting and guiding the participatory mapping process. This requires different types of information: the background and purpose of a project, the benefits that can be achieved from participation, the participatory work to be done and related efforts, the data collection and reporting process (including building spatial literacy skills), data protection and security, and project findings and progress (Hennig, 2020; Rambaldi et al., 2006). Survey123 for ArcGIS Online provides various possibilities for meeting the information needs of the participants. To provide different levels of information and include multi-media, different features are available, such as survey title and description, question label and hint, note question, group question, and Thank-You-Screen. Some of these possibilities allow the integration of external links and multimedia elements (see Table 8.1).

Table 8.1  Information provision in the context of Survey123 smart forms Feature Survey title Survey description

Question label Question hint Note question

Group question (including e.g. note questions) Thank-You-Screen (currently online available in the web app but not supported in the field app) Multimedia elements (related to all question types; requires the use of Survey123 Connect for ArcGIS)

Description (including links) Text or image (https://doc.arcgis.com/en/survey123/ browser/create-­surveys/styleyourform.htm) Text, images, and external links (https://doc.arcgis. com/en/survey123/browser/create-­surveys/ styleyourform.htm) Text Text and external links Text, images, and external links (https://community. esri.com/t5/arcgis-­survey123-­blog/understanding-­ notes-­in-­survey123/ba-­p/894937) Possibility to collapse/extend it depending on user interaction Text, images, and external links (https://doc.arcgis. com/en/survey123/browser/create-­surveys/ styleyourform.htm) Images and audio files (https://doc.arcgis.com/en/ survey123/desktop/create-­surveys/xlsformmedia.htm) Video (via an external link)

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In addition, Esri products, such as ArcGIS Experience Builder, make it possible to embed a Survey123 smart form in a web app that provides extensive information about the related project (Table 8.2). This is consistent with Hennig et al. (2020), who recommended providing only brief and necessary information together with a smart form, but to complement this information with more comprehensive details available on a project-related website that can be accessed by participants if they need or wish more information.

8.2.2 Consent of Use A key issue in contributory initiatives and participatory mapping is obtaining participants’ consent of use. Information related to participants’ consent of use must include, among other things, project objectives, methods of participation, contact data of those responsible for the initiative, options to edit and withdraw (personal) data at any time. All information and explanations must be clear and easy to understand (EC, 2010). Using Survey123 for ArcGIS Online, consent of use can be provided via single-choice questions that must be mandatory. Information related to the consent of use can be made available to the participants in the simplest way through the question hint. Another possibility is to add a group question and, in this context, add a note question (to add more comprehensive information), as well as a single-­ choice question. Depending on confirming consent of use or denying it, the respondents can be branched to the following questions (i.e., use of branch logic: set rule, https://support.esri.com/en/technical-­article/000022942).

8.2.3 Participation and Survey Design Regarding the participation process, it is important to provide spatial information technologies that are manageable for lay people, consider people’s time (e.g., avoiding repeating and/or unnecessary activities), and meet participants’ usability and accessibility requirements to ease participation and make it fun (Chambers, 2006; Hennig et al., 2020; Rambaldi et al., 2006). This requires careful participation and survey design. This includes requesting only the data that is necessary and

Table 8.2  Information provision using ArcGIS Experience Builder Features General Survey widget

Link https://doc.arcgis.com/en/experience-­builder/configure-­widgets/widgets-­ overview.htm https://doc.arcgis.com/en/experience-­builder/configure-­widgets/survey-­widget. htm

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proportionate to the defined and communicated project goals. Survey123 supports this by different, question-related features, such as the possibility of setting rules (i.e., use branch logic), providing default values and calculations, and prepopulating answers in the context of device and user properties (see Table 8.3). To provide a user-centered smart form, various possibilities exist in Survey123. This also enables us to consider different web usability and accessibility criteria that partially overlap (Nielsen, 2020; W3C, 2021). Examples include the careful use of language (different languages: no technical terms), appropriate font style and size, optimized contrast between text and background, multimedia elements (images, video, audio files), and customized base maps (Hennig & Vogler, 2016). The links to recommendations on how to handle these aspects in Survey123 are listed in Table 8.4.

Table 8.3  Question-related features to support appropriate participation and survey design Feature Link Set rule (branch logic) https://doc.arcgis.com/en/survey123/desktop/create-­surveys/ xlsformformulas. htm#ESRI_SECTION1_A3C2F3566F974734B55ECECD31C6CA91 Default answers https://doc.arcgis.com/en/survey123/desktop/create-­surveys/ prepopulateanswers.htm Calculations Device/user properties

Table 8.4  Links to selected recommendations to meet usability and accessibility criteria in Survey123 smart forms Topic Design issues/ general usability

Web accessibility

Link Style your survey https://doc.arcgis.com/en/survey123/browser/create-­surveys/ styleyourform.htm https://doc.arcgis.com/en/survey123/desktop/create-­surveys/ styleyourform.htm Advanced Smart Form Design https://storymaps.arcgis.com/stories/22d6e29c532248c2b975a818b4ad 00f6 Survey123 Custom Basemaps https://www.youtube.com/watch?v=rGYT4sk6M0I Esri Accessibility Conformance Report_ArcGIS Survey123_3.11 https://www.esri.com/en-­us/legal/accessibility/conformance-­reports Web accessibility best practices for Survey123 authors https://www.esri.com/arcgis-­blog/products/survey123/national-­ government/web-­accessibility-­best-­practices-­for-­survey123-­authors/ Survey123 Tricks of the Trade: Introducing Multilingual Surveys https://community.esri.com/t5/arcgis-­survey123-­blog/survey123-­tricks-­ of-­the-­trade-­introducing/ba-­p/894919

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8.2.4 Feedback People who put time and effort into supporting a project appreciate the acknowledgment and feedback on their work (Hennig, 2020; Rambaldi et al., 2006). Survey123 and related other Esri ecosystem tools offer various ways to provide feedback to participants. This is in connection with the visualization and analysis of the data reported by the participants using ArcGIS Online web maps and ArcGIS Online web apps. Since ArcGIS Online web maps focus on providing users the full array of ArcGIS Online tools, data should be published through a map. If specific tools and functions are also to be made available to users, then maps should be integrated and shared in the context of web apps. These applications can either be built in ArcGIS Online using one of the web app templates provided or they can be configured individually using the Web AppBuilder (Kerski, 2014). In addition, ArcGIS Operations Dashboards, and ArcGIS Online StoryMaps can be used (see Table 8.5). In addition to the possibilities listed in Table 8.5, also Survey123 reports provide feedback. This is an effective way to quickly visualize, interpret, and share survey responses as either a Microsoft Word or PDF document. For this purpose, a template exists that can be personalized to create reports. Several methods are available to generate reports from contributed data. The most common method is through the survey’s Report panel on the Data tab on the Survey123 platform. Here, report templates can be managed, and reports can be generated (in a PDF and DOCX format). Furthermore, a webhook can be used to trigger a process to create and share reports on survey results. For instance, each time a survey is submitted, a webhook can trigger the Create Report module in a third-party tool such as Integromat (https://www. integromat.com). Thus, whenever data is submitted, a report is generated and sent to particularly indicated persons, including the participant. Another approach involves running automated reporting processes at regular intervals. For example, a report for all surveys submitted in the past week, month, or quarter can be produced. Here, the ArcGIS Survey123 module in the ArcGIS API for Python can be useful. A script can be set up and run periodically as a scheduled task. Information regarding the use of reports and related aspects can be found in Table 8.6.

Table 8.5  Feedback possibilities in connection with analytical and visualization capacities of Esri ecosystem tools Tool ArcGIS Online web maps

Link https://doc.arcgis.com/en/arcgis-­online/reference/what-­is-­web-­map. htm ArcGIS Online web apps https://doc.arcgis.com/en/arcgis-­online/create-­maps/create-­map-­ apps.htm ArcGIS Operations https://www.esri.com/en-­us/arcgis/products/arcgis-­dashboards/ Dashboards overview ArcGIS Online StoryMaps https://doc.arcgis.com/en/arcgis-­storymaps/get-­started/what-­is-­ arcgis-­storymaps.htm

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Table 8.6  Dealing with Survey123 reports Topics Creating Reports Reports and webhooks (using Integromat) Reports using ArcGIS API for Python

Links https://www.esri.com/arcgis-­blog/products/survey123/ announcements/introducing-­survey123-­feature-­reports/ https://doc.arcgis.com/en/survey123/browser/create-­surveys/ webhooks.htm https://github.com/Esri/Survey123-­tools

8.3 Cost As mentioned in the beginning and furtherly explained in Sect. 8.8, Survey123 is part of the ArcGIS Online ecosystem provided by Esri. Therefore, there are no direct costs for a Survey123 license, but an ArcGIS Online subscription is needed to use Survey123 (as an author), i.e. to create and publish a survey and to visualize and publish the results in a web map. Here, on the one hand, Esri provides so-called public accounts, which are free of charge but do not include access to premium content or additional tools like Survey123. On the other hand, there are different subscription models for single use (starting from $100, − per year) or for organizations (i.e., an individual ArcGIS Online organization including an own account management for a certain number of users with an individual pricing scheme depending on the size of the organization). In this context it is worth mentioning that there are special prices for non-profit organizations and for the education domain. Schools in the United States and in most European countries are e.g., eligible to subscribe for a free of charge ArcGIS Online organization. Despite these account models, there is also a developer program, which enables users to set up a single-use organizational account for free including the full suite of tools and resources. These developer accounts have limited capacities on e.g., data storage and do not include advanced geospatial analysis functions (with the option to pay for additional services) but provide access to almost all the tools within the ArcGIS Online platform including Survey123. Table  8.7 provides an overview of further information about the different account options.

8.4 Technical Level The technical level needed to use Survey123 for a participatory mapping initiative must be evaluated from two perspectives. From a frontend point of view, the technical level for all stakeholders participating in the mapping initiative (i.e., contributing data to the survey) is quite low. The survey can be populated browser-based, so the only technological requirement is the need for a device (mobile or desktop) with an active internet connection. Filling the survey itself does not require technological

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Table 8.7  ArcGIS Online account options Account type or program Account overview Subscription overview Developer program Nonprofit program Education program K-12 school program (US) European school program

Further information https://www.esri.com/en-­us/arcgis/products/create-­account https://www.esri.com/en-­us/arcgis/products/arcgis-­online/ buy https://developers.arcgis.com/ https://www.esri.com/en-­us/industries/nonprofit/overview https://www.esri.com/en-­us/industries/education/overview https://www.esri.com/en-­us/industries/k-­12-­education/ overview https://www.esri.com/en-­us/school-­program-­europe/ overview

Fig. 8.1  The web designer of Survey123. (Source of the tool: Esri)

knowledge or even GIS skills. Answering the questions (i.e., providing the feature attributes) is self-explanatory and providing the feature location is in fact just putting, e.g., a pin on the respective location in a web map. Thus, the frontend technical level is so low that Survey123 also can be used in the classroom with high school students (see Sect. 8.12) or even in primary school (see e.g., Pokraka et al., 2021). From a backend point of view, the technical level to create, design and publish a survey and then to visualize its results in an interactive web map is a bit more advanced and requires at least basic skills in information and communication technologies ICT and/or geodata handling and management. To set up a survey, there are two options: a web designer and respective desktop application. The web designer provides a simple online drag & drop editor comparable with other basic survey tools like e.g., Google Forms or MS Forms (see Fig. 8.1 for an illustration). The desktop application (called Survey123 Connect) enables users to edit an XLSForm spreadsheet to set up and design a survey and provides full smart form capabilities. Therefore, the desktop application is way more advanced and,

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Table 8.8  Tutorials provided by Esri Issue Survey123 resources Web designer tutorial Application tutorial Map design with attributes

Further information https://www.esri.com/en-­us/arcgis/products/arcgis-­survey123/ resources https://doc.arcgis.com/en/survey123/browser/create-­surveys/ createsurveys.htm https://doc.arcgis.com/en/survey123/desktop/create-­surveys/ createsurveys.htm https://doc.arcgis.com/en/arcgis-­online/create-­maps/create-­maps-­and-­ apps.htm

accordingly, requires a higher level of technical skills. It also has to be said that the ArcGIS Online ecosystem is undergoing a permanent development including new functionalities, like e.g., the smart camera feature for Survey123 using machine learning to classify images gathered in the field with a survey (Esri, 2021a), which partially require expert knowledge. Nevertheless, there are very well documented tutorials provided by Esri for both the simple web designer and the Survey123 Connect application (see Fig. 8.1). To use Survey123 and the ArcGIS Online ecosystem for a participatory mapping initiative, it is necessary to not just set up and publish a survey but also to visualize its results in a web map or web map application. Therefore, the survey results are stored in a feature layer (hosted in ArcGIS Online by the survey author) containing all survey responses as single features with attached attributes based on single question responses. This feature layer then can be added to a web map and visualized (symbols and popup content) based on the attribute values of each feature. To set up and publish such a web map, basic knowledge on geodata handling and attribute-­ based map design in ArcGIS Online is required, even if there are also very well documented tutorials available (see Table 8.8). Due to the embedding in and intertwinement with the whole ArcGIS Online ecosystem, the range of technical skills required for Survey123 is very wide starting from low level to very advanced. But it can be said that especially the low-threshold tools needed to use Survey123 for participatory mapping initiatives (i.e., the web designer for the survey and the map viewer for the visualization) are easy to learn with the support of the very well documented tutorials and materials.

8.5 Inclusiveness Survey123 as such does not include any specific tools and measures to include the underrepresented minorities into the decision-making process, nevertheless, the intuitiveness and drag & drop building mechanism allows a quick and easy way to build one’s own survey. To build a questionnaire in the Survey123 the editor needs to have the institutional account, which itself does not support the inclusiveness a

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lot, but general users (respondents) do not need to have any account to fill in the questionnaire. The respondent can use either a web link (not depending on the device operating system) or can use Esri mobile app (available for iOS as well as Android). The advantage of the mobile app is that it saves data offline, while the respondent is not within the data signal or Wi-Fi reach and allows the respondent to submit the data later. On the other hand, it raises further obstacles regarding the technical expertise of the users/respondents.

8.6 Data Accuracy The data accuracy depends on the question asked within the survey (qualitative, or quantitative questions – rankings, free text areas, etc.). From the geographical point of view the most related data accuracy is information regarding the spatial data collected via the survey. In 2022 version of Survey123, users can collect: • Point • Line (vertex, or sketch) • Area (vertex, or sketch) The coordinates saved with each of the locations will be as accurate as the GPS chip in your device allows. For example, the latest iPhone 13 Pro (as well as some older models) have a built-in chip, that can read signal not only from US system GPS, but also from GLONASS (Russia), Galileo (EU), QZSS (Japan), and BeiDou (China). The quality of the GPS chips in the mobile device is increasing, in 2009 Zandbergen (2009) tested GPS and A-GPS on iPhone 3G (Assisted GPS (A-GPS) is also using Wi-Fi and cellular network to improve the positioning accuracy) and reported that “3G iPhone are much less accurate than those from regular autonomous GPS units (average median error of 8m for ten 20-minute field tests)”. Nevertheless, in 2011 Menard et  al. (2011) stated that “iPhone 4 determined approximately 98% of its GPS points within 10m of true positions and approximately 59% within 5m”. Some studies claim (Karki & Won, 2020) that modern dual-frequency smartphones can reach submeter accuracy, but this comes with large power loss. Users can also mark the point to a location that they are not currently positioned – just marking the location on the map. In such cases the (in)accuracy may be much higher than just the GPS error. The correct selection of the geometry type depends strongly on the feature we are mapping. Brown and Pullar (2011) evaluated Public Participation GIS (PPGIS) projects and analyzed in which cases points or polygons should be used in participatory mapping. The selection of optimal mapping geometry seems to attract a larger audience in recent years, as Ramirez Aranda et al. (2021) analyzed using point, marker, or polygon form PPGIS cultural ecosystem services mapping.

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8.7 Data Privacy To create a Survey123 questionnaire, one has to have an institutional account, so the question about the data privacy depends on the owner (country of residence) of the data server. Once the data is sent from the mobile device to the server, the survey data is stored on the mobile device as a .sqlite database. This database can be copied and edited to aid data recovery. By copying the .sqlite database to a desktop, it is possible to fix the database or manually modify the paths stored in the .sqlite database from the ArcGIS Survey123 field app (Esri, 2022a). Location-based apps usually require the user to allow location data to be collected as a part of privacy settings/permissions. The default behavior is to only capture the location as needed by a survey, meaning that no location is captured when the app is in the background. The data collected are owned by the owner of the license, used for creating the survey (usually the institution running the mapping). As was stated above, the collected data (if the mobile device is used) are stored in the mobile device itself. Regarding the web-based environment, the generic ArcGIS online privacy and data storage rules apply. The survey is composed of multiple items in your ArcGIS account. The survey is created from a Form item, a Feature Layer item and a Web Map item are created in a new folder. If you create a survey in Survey123 Connect based on an existing feature layer, only the Form item and Web Map item will be created in the new folder; the existing feature layer will be referenced from its source location. When a survey is created from the Survey123 website, a Form item, a Feature Layer item, and a Web Map item are created in a new folder. A stakeholder view and fieldwork view of the feature layer will also be created (Esri, 2022b).

8.8 Analytical Capacity While a continuously growing number of analytical methods for spatial data exist (e.g., Redecker et al., 2020), Fagerholm et al. (2021) discuss methods used for the analysis of participatory mapping data. They differentiate between the methods used in the different data analysis phases (see Table 8.9): (i) explore, (ii) explain, and (iii) predict/model. We use these categories in the following and further distinguish between methods available to the survey participants and/or the survey authors.

8.8.1 Survey123 Platform: Survey Participants Analytical methods regarding explanation and predicting/modeling that can be used by the participants are not available on the Survey123 platform. Only exploratory methods (visual output: view and filter results) can be made available to anyone

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Table 8.9  Phase-related spatial data analysis methods (Fagerholm et al., 2021) Phase Explore Explain

Predict/Model

Methods Data description: descriptive/univariate analysis Data visualization (Visual outputs, in form of thematic maps and charts) Visual and overlay analysis Spatial pattern analysis: intensity and density; clustering Proximity-related analysis Analysis across spatial scales Calculation of indices across spatial units (e.g., conflict potential) Analysis of spatial associations Cluster and multivariate association analysis Predictive analysis (e.g., extrapolation, assessment of land use consistency) Modeling (statistical, spatial, and mathematical modeling)

other than the survey author. For this, the survey author must assign the participants the necessary rights (Survey123 platform: Collaborate tab, Share Results panel) and share the respective link with the participants. The link opens information available to the survey author under the Survey123 platform, Analyze tab.

8.8.2 Survey123 Platform: Survey Authors In direct connection with the Survey123 platform, only limited analytical capacity is available to the survey author. This refers to the exploratory methods. Survey123 offers the possibility of viewing and filtering the data contributed: regarding spatial data visualization (Survey123 platform: Data tab) and non-spatial visualization (Survey123 platform: Analyze tab). This includes the possibility of data filtering.

8.8.3 Map Viewer: Survey Participants In Map Viewer (Survey123 platform; Data tab, Open Map Viewer tab), a web map can be created and shared (Map Viewer: Save tab; Map Viewer: Share tab). The web map gives participants the opportunity to explore the data. This includes functionalities generally available in web maps such as navigation tools (zoom, pan, home, find my location), basemap gallery/switcher, layer switcher, search, measure, share, and print. The web map can also be integrated into a web app. Depending on the option selected (Configure Apps, Web AppBuilder, or ArcGIS Dashboard), additional analysis methods can be implemented within the web app and thus made available to the participants. Regarding the Configure Apps option, depending on the web app template used, different functionalities are available. This includes functionalities such as finding and filtering, highlighting features within a buffered distance of a user-selected

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Table 8.10  Implementation of ArcGIS Online web maps, ArcGIS Online web apps, and ArcGIS dashboards Implementation ArcGIS Online web map ArcGIS Online web app (Configure App) ArcGIS Online web app (Web AppBuilder) ArcGIS Dashboards/Operations Dashboard

Further information https://doc.arcgis.com/en/arcgis-­online/reference/view-­ maps.htm https://doc.arcgis.com/en/arcgis-­online/create-­maps/ choose-­configurable-­app.htm https://doc.arcgis.com/en/web-­appbuilder/ https://www.esri.com/en-­us/arcgis/products/arcgis-­ dashboards/resources

location, and highlighting an area and showing a summary of quantitative data related to its location. Concerning the Web AppBuilder, basic and advanced analytical capacities (i.e., related to exploration, explanation, and prediction/modeling) are provided. These are based on widgets (distinguished in OffPanel-Widgets and InPanel-Widgets; https://doc.arcgis.com/en/web-­appbuilder/create-­apps/widget-­ overview.htm), which are added to the web app. The last option refers to the implementation of an ArcGIS Dashboard (alternatively, Operations Dashboard). It is a configurable web app that allows the integration of interactive (visual) elements such as charts, gauges, maps, and lists to reflect the status and performance of assets, personnel, services, and events in real time. These dashboards enable the monitoring of activities and performance indicators related, for instance, not only to an organization’s business objectives and workflows, but also to Survey123 smart form results within a single display. This is an excellent way to provide participants with an interactive dynamic display of the data contributed (Law, 2019). Information on the creation process of ArcGIS Online web maps, ArcGIS Online web apps, and ArcGIS Dashboards is accessible through the links provided in Table 8.10. Depending on the product and features implemented, there are different possibilities for exploring the data provided by participants. For instance, if the participant’s name/username has been requested and added when filling out the Survey123 smart form, it is possible to use this information to search for this person, indicate the corresponding feature in the map, and show the contributor’s name/username in the feature pop-up window.

8.8.4 Map Viewer: Survey Authors In the Map Viewer tab (Survey123 platform: Data tab, Open Map Viewer tab), the survey author can create and share a web map showing the survey results. Moreover, Map Viewer also supports a range of analysis functionalities (explore, explain, predict/model the survey data) that the survey author can use (see Table 8.11).

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Table 8.11  Analytical capability generally available in ArcGIS Online Map Viewer Category Summarize data

Find locations

Data enrichment Analyze pattern

Use proximity

Manage data

Analytical capability (https://doc.arcgis.com/en/arcgis-­online/analyze/perform-­analysis.htm) Aggregate Points Summarize Within Join Features Summarize Center and Dispersion Summarize Nearby Find Existing Locations Choose Best Facilities Derive New Locations Create Viewshed Find Centroids Create Watersheds Find Similar Locations Trace Downstream Enrich layer Calculate Density Find Point Clusters Find Hot Spots Interpolate Points Find Outliers Create Buffers Plan Routes Create Drive-Time Areas Connect Origins to Destinations Find Nearest Dissolve Boundaries Merge Layers Extract Data Overlay Layers Generate Tessellations

8.8.5 Other Analytical Capacity: Survey Author With the export of the contributed data (CSV, excel, kml, shapefile, file geodatabase) from the Survey123 platform (Survey123 platform: Data tab), the data can be used in other expert tools for spatial data analysis and Geographic Information Systems (GIS). For instance, this refers to ArcGIS Pro/ArcGIS Map and QGIS (including the use of Python) and data science tools such as R. However, the possibility of using certain functions in ArcGIS Online Map Viewer and ArcGIS Map/ ArcGIS Pro (i.e., their availability) depends on the pricing and license level chosen by the user (Sect. 8.3).

8.9 Visualization Capacity Regarding visualization capacity, concerning the data submitted via Survey123 smart forms, we distinguish between possibilities available, on the one hand, to the survey author and, on the other hand, to the participants. These possibilities refer to the functionalities available on the Survey123 platform and different Esri ecosystem tools. Because these possibilities are also relevant in the context of feedback to the participants and are part of analytical methods (i.e., exploration), they have already been presented in Sects. 8.2 and 8.8 (e.g., Survey123 platform: Analyze tab; Survey123 platform: Reports, Map Viewer). This includes the creation and sharing of web maps, web apps, ArcGIS Dashboards, and ArcGIS StoryMaps.

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Table 8.12  Background and recommendations regarding different visualization possibilities in the ArcGIS Online Topic Tool decision Web map design

Links https://www.esri.com/about/newsroom/arcnews/ how-­to-­choose-­the-­right-­web-­app-­in-­arcgis-­online/ https://www.esri.com/news/arcuser/0612/designing-­great-­web-­maps.html https://www.gislounge.com/dos-­and-­donts-­of-­web-­map-­design/

Table 8.13  Tools and recommendations regarding their use Topic ArcGIS Online Web App ArcGIS Online Story Map ArcGIS Online Operations Dashboard ArcGIS Insights ArcGIS Business Analyst

Links Using templates: https://doc.arcgis.com/en/arcgis-­online/create-­maps/ choose-­configurable-­app.htm Using Web MapBuilder: https://doc.arcgis.com/en/web-­appbuilder/ https://www.esri.com/arcgis-­blog/products/story-­maps/mapping/ ten-­essential-­steps-­for-­story-­map-­success/ https://doc.arcgis.com/en/dashboards/reference/author-­effective-­ dashboards.htm https://www.esri.com/en-­us/arcgis/products/arcgis-­insights/overview https://community.esri.com/t5/arcgis-­survey123-­blog/how-­to-­perform-­ spatial-­analysis-­on-­survey123/ba-­p/898762

Visualizing the data collected by Survey123 using these tools is based on considering aspects such as the audience, the purpose, the design look and function. This also allows us to decide for the most suitable tool in the respective context (see Table 8.10). Since web maps are integrated in web apps, ArcGIS Dashboards, and ArcGIS StoryMaps recommendations regarding the design and implementation of web maps including cartographic recommendations (e.g., scale, color, symbols, fonts) are generally of importance. Information on this is presented in Table 8.12. Moreover, for web apps, ArcGIS Dashboards, and ArcGIS StoryMaps  – apart from recommendations regarding the development and implementation of web maps – individual aspects regarding these features must be considered (Table 8.13). However, using ArcGIS Insights or ArGIS Business Analyst additional visualization options exist. They, among other things, provide possibilities to use various visuals to present the collected data, including not only maps but also different types of charts.

8.10 Openness The term openness is an umbrella term that includes different components: (i) open-­ source software, (ii) open data, (iii) open hardware, (v) open standards, (v) open education, and (vi) open science (see Table  8.14; Coetzee et  al., 2020). Of these

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Table 8.14  Components of openness (Coetzee et al., 2020; OKFN, n.d.; UniMelb, 2021; UTA Libraries, 2021) Component Open-Source Software Open Data Open Hardware Open Standards Open Education

Open Science

Definition Free and open collaborative software development Freely available and accessible, shareable, and (re-)usable data Physical products, machines, and systems designed and offered by means of publicly shared information Technology-neutral specifications for hardware, software, or data developed through an open process Learning and teaching without barriers which is based on practices such as open data and open-source software, open access publishing, open admissions/ registration (flexible admission policies to institutions or courses), open teaching/ pedagogy (i.e., experiential learning with assignments that promote student publishing/participating on the open web), open scholarship, and open educational resources (sharing and reuse of teaching and learning materials) Making scientific research and its dissemination accessible to all levels of the society

components, open-source software, open data, and open education, which are particularly relevant to Esri ecosystem products, are discussed here.

8.10.1 Open-Source Software Survey123 is an application of the Esri ecosystem. Therefore, it is not an open-­ source system. There is no possibility of participating in its development, which is a condition for free and open-source software (Thomas, 2010; Wubishet et  al., 2013). However, Esri is interested in feedback on its tools including Survey123. A website is operated to build up and maintain a community around Survey123 (https://community.esri.com/t5/arcgis-­survey123-­questions/bd-­p/arcgis-­survey123-­ questions). The Survey123 community can report problems and errors as well as contribute ideas and recommendations for improvement. Although users cannot participate in the development of the Survey123 platform, they can collaborate in the design and implementation of Survey123 smart forms (currently only Survey123 website/web designer). This requires an ArcGIS online account for those who shall take part in a Survey123 smart form development process. Furthermore, a shared update group must be established by the administrator of the respective ArcGIS online organization (Survey123 platform: Collaborate tab, Update Survey panel; Survey123 platform: Collaborate tab, Group Settings panel; https://doc.arcgis.com/en/survey123/browser/create-­surveys/sharesurvey.htm). Because of the user-friendliness of the Survey123 platform, users – being also lay people – can easily be involved in the design and implementation of a Survey123 smart form. This makes it possible to understand their needs, skills, and preferences in greater detail (Hennig et al., 2020).

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8.10.2 Open Data Open data refer to data that is freely available and accessible (i.e., technically open), shareable, and (re-)usable (i.e., legally open), and characterized by universal participation (e.g., Coetzee et  al., 2020; OKFN, n.d.). Considering this, data collected through Survey123 smart forms is not automatically open data. This depends on the survey author. There are several possibilities for providing open access to the data contributed through a Survey123 smart form. This refers to the possibilities available within the Survey123 platform (Survey123 platform: Collaborate tab, Share Results panel). Here, the survey author decides on who (e.g., everyone) is allowed to access the survey results, that is, the contributed data, and the level of access (e.g., view and export data). There are additional methods to share the data to be used by others using ArcGIS Online, ArcGIS Hub, and ArcGIS Open Data. Information on these possibilities is presented in Table 8.15.

8.10.3 Open Education Open education includes the activities listed in Table 8.14. Of these practices, open data and open source software have already been presented in the previous paragraphs, and opportunities for open admission/registration (free trial regarding Survey123 and Esri ecosystem products) have been highlighted in Sect. 8.8.2. In the following, open teaching/pedagogy and open educational resources will be briefly discussed, in contrast to open access publishing and open scholarship, which are of less importance here. With the possibility that users can share their material (e.g., data, web maps, web apps) with others and the fact that Survey123 examples from the community are published by Esri on a particular platform (e.g., https://doc.arcgis.com/en/survey123/gallery/), Esri supports open teaching and open pedagogy practices to a certain extent. In this context, products that are openly licensed will live outside the initiative and can thus have an impact on the greater community (UTA Libraries, 2021). There are numerous paid and free educational resources that help users familiarize themselves with Esri products, including Survey123 (e.g., implementation of smart forms and handling of the data submitted). Apart from the paid and free offers Table 8.15  Possibilities to share Survey123 smart form data for use by others Tool ArcGIS Online ArcGIS Hub/Open Data Other tools/ platforms

Further Information https://doc.arcgis.com/en/arcgis-­online/reference/best-­practices-­share.htm https://www.esri.com/en-­us/arcgis/products/arcgis-­open-­data https://www.esri.com/about/newsroom/arcwatch/ create-­an-­open-­data-­site-­in-­three-­steps/ https://gis.stackexchange.com/questions/100273/ comparison-­of-­open-­data-­portal-­solutions https://www.screencast.com/t/WbvcUztb

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in Esri’s MOOC (https://www.esri.com/training/mooc/) and training course program (https://www.esri.com/training/catalog/search/), this refers to tutorials, webinars, videos, and online courses. Examples therefore are presented throughout this chapter (e.g., Table 8.3, 8.4, and 8.6). In addition, support is provided by an open FAQ website and an open Survey123 community website that allows exchanges with Esri staff and other community members and serves as a get-away to other material regarding Survey123.

8.11 Accessibility ArcGIS Survey123 can serve both as an online web service as well as a mobile app (offline during the data collection, but you need to be online to submit the data). As all the data is collected and stored in the ArcGIS Online cloud service, the connection to the Internet is paramount for the application to be operational. The editor needs to be online to create the survey and distribute it to the devices – while collecting (and if using the Survey123 app) the respondents do not need to be online, but the connection to the internet is required for submitting the collected data. Once the data is collected, it can be downloaded from the server and used/edited/analyzed/visualized both offline as well as online. The World Wide Web Consortium (W3C), an international community that develops open standards for the Web, introduced in 2008 the Web Content Accessibility Guidelines (WCAG) 2.0 (WCAG, 2022). WCAG 2.0 offers guidelines in four major areas of the web content accessibility: The web (including web-based surveys such as Survey123) must be: Perceivable • Provide text alternatives for any non-text content so that it can be changed into other forms people need, such as large print, braille, speech, symbols, or simpler language. • Provide alternatives for time-based media. • Create content that can be presented in different ways (for example simpler layout) without losing information or structure. • Make it easier for users to see and hear content including separating foreground from background. Operable • Make all functionality available from a keyboard. • Provide users enough time to read and use content. • Do not design content in a way that is known to cause seizures. • Provide ways to help users navigate, find content, and determine where they are. Understandable • Make text content readable and understandable. • Make Web pages appear and operate in predictable ways. • Help users avoid and correct mistakes.

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Robust • Maximize compatibility with current and future user agents, including assistive technologies. Esri evaluates its software (including Survey123) for conformance with web accessibility standards. The results of the evaluations are available in the Accessibility Conformance Reports (ACR) – for both mobile (Esri, 2021b) as well as web (Esri, 2021c) versions of Survey123. The Survey123 ACRs explain the extent to which the software adheres to standard web accessibility guidelines.

8.12 Brief Use Case Even if this might not be a typical domain for participatory mapping initiatives, the following use case was designed and conducted for classroom use in secondary education. The respective lesson was dedicated as an introduction to globalization based on a student-centered learning approach (Jones, 2007), i.e., focusing the student’s lifeworld instead of abstract concepts or examples. Therefore, the students had the introductory task to reflect on their own media consumption: Which media do they use on which devices? Following this, they were asked to do a little online research and collect information on this: Where is the media company located? Where is the device company located? Where was the device manufactured? Where do the resources for the device come from? Where are these devices disposed of after usage? Instead of using a paper-pencil-approach, all this information was collected with a survey designed in Survey123 (see Fig. 8.2). Since Survey123 is fully embedded in the ArcGIS Online ecosystem, the respective feature layer collecting all the replies was added to a web map before the lesson. This map was designed based on the data model defined in question 1 of the survey: the values of the respective attribute are equivalent to the available survey question answers. It is possible to design and implement the map even before any data is submitted: layer filter based on attribute values (categories from question 1), symbols based on attribute values (categories from question 1), popup content based on attribute values (description from question 2). It was possible to design the classroom setting in a way that the designed map was projected while students submitted their replies to the survey and accordingly the map could “grow” in real-time. The result was an individual interactive map showing an aspect of media globalization, which was insofar as it was based on the students’ lifeworlds and then served as a basis for further discussion. In this case, geospatial technology helped to spatially contextualize authentic learning contents and therefore to foster learning itself following the approach of spatially enabled learning (Vogler et al., 2012, 2018) (Fig. 8.3). Beyond using Survey123 in the classroom for data collection by school students, the tool is also easy to use by school students as survey authors as e.g. conducted in the Sparkling Science 2.0 project u3Green (www.sparklingscience.at/en/u3Green-en.html. funded by the Austrian BMBWF).

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Fig. 8.2  The frontend of the survey used in the classroom. Question 1: type of location (media company, device company, resource location, device manufacturing, device disposal). Question 2: name and/or short description. Question 3: location. (Source of the tool: Esri; survey design: R. Vogler)

Fig. 8.3  The map application visualizing the survey results in real-time. (Source of the tool: Esri; map design and content: R. Vogler)

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8.13 Comments and Recommendations ESRI’s Survey123 for ArcGIS Online can be a simple as well as powerful tool for participatory mapping and field exploration. Its strong ties to the Esri ecosystem including ArcGIS Online and other visualization apps (StoryMaps, etc.) are one of the strengths (due to the integration options to other Esri applications and platforms and especially the manyfold visualization opportunities) and make it easy to learn and operate with the help of many well documented tutorials provided by Esri. The fact, it is not an open-source application, and one needs to have an institutional account to set up a survey and publish the results in an interactive web map may prevent some users from using the application. But there are many special offers for the education domain and non-profit organizations to keep the costs comparably low or even at zero (e.g. in the developer program) and one strength is that all stakeholders can submit data browser-based in a very simple and open way. This makes Survey123 (in combination with the ArcGIS Online ecosystem) a very powerful tool for participatory mapping initiatives.

References Brown, G., & Pullar, D. (2011). An evaluation of the use of points versus polygons in public participation geographic information systems using quasi-experimental design and Monte Carlo simulation. International Journal of Geographical Information Science, 26(2), 231–246. https://doi.org/10.1080/13658816.2011.585139 Chambers, R. (2006). Participatory mapping and geographic information systems: Whose map? Who is empowered and who disempowered? Who gains and who loses? The Electronic Journal of Information Systems in Developing Countries, 25(1), 1–11. Coetzee, S., Ivánová, I., Mitasova, H., & Brovelli, M. A. (2020). Open geospatial software and data: A review of the current state and a perspective into the future. International Journal of Geo-Information, 9(90), 1–30. https://doi.org/10.3390/ijgi9020090 EC European Commission. (2010). European textbook on ethics in research. EUR 24452EN. Esri. (2021a). ArcGIS Survey123 smart camera: Machine learning meets field data collection. https://www.esri.com/arcgis-­blog/products/survey123/announcements/ arcgis-­survey123-­smart-­camera-­machine-­learning-­meets-­field-­data-­collection/ Esri. (2021b). Esri Accessibility Conformance Report ArcGIS Survey 123: Product Version  – Mobile application. https://www.esri.com/content/dam/esrisites/en-­us/media/legal/vpats/ arcgis-­survey123-­mobile-­313-­vpat.pdf Esri. (2021c). Esri Accessibility Conformance Report ArcGIS Survey 123: Product Version – Web App Version 3.13. https://www.esri.com/content/dam/esrisites/en-­us/media/legal/vpats/arcgis-­ survey123-­313-­vpat.pdf Esri. (2022a). FAQ: What are the ways to recover ArcGIS Survey123 data? https://support.esri. com/en/technical-­article/000024617 Esri. (2022b). ArcGIS Survey123 General FAQ. https://doc.arcgis.com/en/survey123/faq/faqgeneral.htm#anchor6 Fagerholm, N., Raymond, C.  M., & Olafsson, A.  S. (2021). A methodological framework for analysis of participatory mapping data in research, planning and management. International Journal of Geographic Information Science, 35, 1848. Hennig, S. (2020). Motivation and its consideration in participatory spatial data contribution. The Professional Geographer, 72(2), 238–252. https://doi.org/10.1080/00330124.2019.1676799

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Hennig, S., & Vogler, R. (2016). User-centered map applications through participatory design: Experiences gained during the “YothMap 5020” project. The Cartographic Journal, 53(3), 213–229. Hennig, S., Abad, L., Hölbling, D., & Tiede, D. (2020). Implementing geo citizen science solutions: Experiences from the citizenMorph project. GI_Forum, 8(1), 3–14. https://doi.org/10.1553/ giscience2020_01_s3 Jones, L. (2007). The student-centered classroom. Cambridge University Press. Karki, B., & Won, M. (2020). Characterizing power consumption of dual-frequency GNSS of smartphone. In GLOBECOM 2020-2020 IEEE global communications conference (pp. 1–6). IEEE. Kerski, J. (2014). Web maps, web apps, story maps. https://community.esri.com/t5/education-­blog/ web-­maps-­web-­apps-­story-­maps/ba-­p/892608 Law, D. (2019). Dashboards in ArcGIS. https://www.esri.com/arcgis-­blog/products/ops-­dashboard/ decision-­support/dashboards-­in-­arcgis/ Menard, T., Miller, J., Mowak, M., & Norris D. (2011). Comparing the GPS capabilities of the Samsung Galaxy S, Motorola Droid X, and the Apple iPhone for vehicle tracking using FreeSim_Mobile. In 14th International IEEE conference of intelligent transportation systems, 2011, October, Washington, DC. Nielsen, J. (2020). 10 usability heuristics for user Interface design. https://www.nngroup.com/ articles/ten-­usability-­heuristics/ OKFN Open Knowledge Foundation. (n.d.). What is open? https://okfn.org/opendata/ Pokraka, J., Kralemann-Popell, T., Gryl, I., & Schmidt, P. (2021). ‘This is a great place for children. Here, they can play, do what they want, have fun and other things.’ Mapping primary school children’s everyday spaces. GI_Forum, 9(2), 18–33. Rambaldi, G., Chambers, R., McCall, M., & Fox, J. (2006). Practical ethics for PGIS practitioners, facilitators, technology intermediaries and researchers. Participatory Learning and Action, 54(1), 106–113. Ramirez Aranda, N., De Waegemaeker, J., Venhorst, V., Leendertse, W., Kerselaers, E., & Van de Weghe, N. (2021). Point, polygon, or marker? In search of the best geographic entity for mapping cultural ecosystem services using the online public participation geographic information systems tool, “My Green Place”. Cartography and Geographic Information Science, 48(6), 491–511. Redecker, A., Burian, J., Moos, N., & Macků, K. (2020). Spatial analysis in geomatics. In V.  Pászto, C.  Jürgens, P.  Tominc, & J.  Burian (Eds.), Spationomy. Springer. https://doi. org/10.1007/978-­3-­030-­26626-­4_3 Thomas, B.  K. (2010). Participation in the Knowledge Society: The Free and Open-Source Software (FOSS) movement compared with participatory development. Development in Practice, 20(2), 270–276. UniMelb. (2021). Open scholarship. https://library.unimelb.edu.au/open-­scholarship#home URISA Urban and Regional Information Systems Association. (2013). GIS Code of ethics. https:// www.urisa.org/about-­us/gis-­code-­of-­ethics/ UTA Libraries. (2021). Introduction to open pedagogy. https://libguides.uta.edu/openped Vogler, R., Hennig, S., Jekel, T., & Donert, K. (2012). Towards a concept of ‘spatially enabled learning’. In T. Jekel, A. Car, J. Strobl, & G. Griesebner (Eds.), GI_Forum 2012: Geovisualization, society and learning (pp. 204–211). Herbert Wichmann. Vogler, R., Jekel, T., & Killingseder, E. (2018). Using the geographies of learning. An exploratory categorization for spatially enabled learning. GI_Forum 2018 – Journal for Geographic Information Science, 2018(2), 181–192. W3C Web Accessibility initiative. (2021). Introduction to web accessibility. Available at: http:// www.w3.org/WAI/intro/accessibility.php Web Content Accessibility Guidelines (WCAG) 2.0. (2022). W3C recommendation 11 December 2008. Available at: https://www.w3.org/TR/WCAG20/ Wubishet, Z. S., Bygstad, B., & Tsiavos, P. (2013). A participation paradox: Seeking the missing link between free/open-source software and participatory design. Journal of Advances in Information Technology, 4(4), 181–193. Zandbergen, P. A. (2009). Accuracy of iPhone locations: A comparison of assisted GPS, WiFi and cellular positioning. Transactions in GIS, 13, 5–25. https://doi.org/10.1111/j.1467-­9671.2009. 01152.x

Chapter 9

Terrastories Christopher Martin, Rudo Kemper, Colin M. Gibson, Natalie Thornhill, Rohini Patel, and Dawn Martin-Hill

Abstract  Terrastories is a free and open-source participatory mapping software enabling communities to build a database of place-based stories and visualize these on a digital map. Co-designed with Indigenous communities, Terrastories leverages a simple interface to serve the focused needs of its targeted users: to map information that is culturally relevant and important to communities. Terrastories allows for uploading information in different multimedia formats and protects the information by granting users different levels of access. Terrastories is easy-to-use, requiring a low level of technical expertise. Knowledge on Indigenous issues, data sovereignty, and ethics are important to guide information gathering methodologies to build a Terrastories map. These concepts solicit novel interpretations of conventional terms such as ‘data accuracy’. A case study is presented in this chapter that outlines how Terrastories is being used by an Indigenous water research program from Six Nations of the Grand River in Canada called Ohneganos Ohnegahdę:gyo. Keywords  Counter-mapping · Free and open-source software · Indigenous data sovereignty · Indigenous knowledge · Indigenous mapping · Oral histories · Place-based storytelling

C. Martin (*) Ohneganos Community Mapping Facilitator, Six Nations of the Grand River Reserve, Canada R. Kemper Digital Democracy, Springfield, VA, USA C. M. Gibson (*) · N. Thornhill · D. Martin-Hill McMaster University, Hamilton, L8S 4L8, ON, Canada e-mail: [email protected]; [email protected]; [email protected] R. Patel Department of History, University of Toronto, Toronto, Canada e-mail: [email protected]; [email protected] © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 C. M. Burnett (ed.), Evaluating Participatory Mapping Software, https://doi.org/10.1007/978-3-031-19594-5_9

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9.1 General Information Name of Application: Terrastories Name of Developer: Terrastories (open-source steward team) Name of Funder: N/A Type of System Software: Desktop and Mobile Type of Programming Language: Ruby on Rails, JavaScript, React, Mapbox GL JS, Docker API Availability: None Features: Interactive map, sidebar with stories and other media content, Indigenous taxonomy filters to sort through content, administrative backend to edit stories and set them as restricted, granulated permissions for viewing and editing stories per username, multiple communities per Terrastories server Cost: Free software plus cost of hosting and hardware Type of Data Collected (Geographic and Descriptive): Custom background map (provisioned via Mapbox GL JS), stories, speakers, places, and multimedia content. Overview: Terrastories is a free and open-source participatory mapping and storytelling application for Indigenous and other communities to map, protect, and share stories about their land. It can be used by individuals or communities who want to connect audio or video content to places on a map. It is designed to be user-friendly and interactive, letting community members freely explore and engage with information contained in the map without needing any technical background. Terrastories began when a team of geographers from the Amazon Conservation Team, along with software developers, identified that there was a need to digitally map a community’s place-based oral histories. Located in South America, the Matawai Maroons of Suriname, a community of formerly enslaved Africans who fled into the forests over three centuries ago and reside there today, wanted to map oral histories about when their ancestors first arrived in these lands. The community leaders were interested in having a tool that helps the young people get to know these places, their history, their culture, and who they are as a people. Terrastories was built to accommodate that need, which the team also heard about from other communities across the globe. While Terrastories was built with Indigenous communities and values in mind, it can however be used by any community  – or any person  – who wishes to map their own place-based oral histories. At its core, Terrastories consists of an interactive map and a sidebar with stories (see Fig. 9.1). On the map, there are Place markers that are associated with one or more Stories, shown in the sidebar. Users can either activate Place markers to see a popup with more information about that - Place, and to filter the sidebar to only show Stories associated with that Place - or users can activate Story cards to filter the map to only show Places associated with that Story, and zoom to their location. Stories also have Speakers, and it is possible to filter Stories by Speaker, by

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Fig. 9.1  Screenshot from Terrastories used during a technical training session at the 2021 Indigenous Mapping Workshop (November 2, 2021)

topic, taxonomy term (which can be Indigenous taxonomies), using a dropdown menu at the top of the sidebar. The entire user interface of Terrastories works in desktop as well as mobile. The interface can also be translated to any language, including commonly spoken ones and translations for minority languages provided by the user. Users with the right editing permissions can access the Terrastories dashboard to add Stories, Places, and Speakers to the map, customize the interactive map content, and set thematic properties for their community’s Terrastories instance. They can also set Stories as restricted, meaning that one needs to have the right level of access in their credentials to be able to view those Stories. Without that level of access, neither Stories nor Places associated with those Stories will show for that user. To summarize, Terrastories gives Indigenous communities the ability to focus on the following three key elements of storytelling and knowledge exchange: Speakers, Places, and Stories. • The Speaker category refers to the contributor of the story, knowledge, or resource. Each specific point on the map will include one or more speaker from which the data and information has originated from. Speakers can be both Indigenous and non-Indigenous; any information can be contributed so long as it is tied to the geographical area of interest and is relevant to the mapping priorities of the community leading the development (see Sect. 9.6: Data Accuracy, pg. 200). • The Place category refers to site-specific locations shown on the background map of Terrastories in which Stories are attached to. Assigning a Place to a Story

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involves attaching the latitude and longitude of the specific location in addition to adding pictures and a description. • The Stories category refers to the content and knowledge being shared by a Speaker that is tied to a particular Place. This is where a more detailed description of the area can be uploaded as data into Terrastories, alongside multimedia formats such as pictures, audio, and video. Terrastories can be hosted entirely offline or online, depending on the community’s needs and resources. Terrastories is built to be multi-instance, meaning that more than one community can access a singular Terrastories server, but each with their own dedicated space, stories, and map that is only accessible by them. In this way, as a digital tool Terrastories empowers Indigenous and other local communities to map and share Indigenous sites of geographical, traditional, ecological, and cultural significance from anywhere in the world (Kemper, 2018). As a decolonial research tool, Terrastories supports Indigenous Peoples and Indigenous communities to develop their own Indigenous-led and protected repository of community-based Traditional Ecological Knowledge (US TEK Task Team, 2021). A key design component of Terrastories is accessibility because some Indigenous communities may be unfamiliar with digital technologies and have limited technical capabilities. To promote accessibility, the Terrastories software employs a simple, user-friendly interface that works on computers and personal digital devices like tablets, laptops, and cellular phones – on or offline. This also helps Indigenous communities engaging with the Terrastories platform choose what knowledge or data they want to share publicly and what stories or knowledge they would like to keep private (see Sect. 9.7: Data Privacy, pg. 202). The development of Terrastories as a program has focused on the needs of the targeted end-users. Core to the Terrastories philosophy is the recognition that the end-users are also the architects of the map they decide to build. Terrastories is community-led in all aspects; designed by community, for community, and community members are the users and stewards of the map they envision and create. Data and information entered the platform acts as a living, community-guided, story-based archive of the land, water, resources, and cultural knowledge integral to Indigenous communities engaging the platform (Kemper, 2018). Ultimately the application acts as a tool to help protect and document tangible and intangible cultural knowledge, while ensuring access to that knowledge from anywhere and at any time.

9.1.1 Ohneganos Ohnegahdę:gyo Ohneganos Ohnegahdę:gyo (Ohneganos) is a community-led university research program directed by Mohawk scholar Dr. Dawn Martin-Hill in partnership with Six Nations of the Grand River (Six Nations). The Ohneganos team is using the

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Terrastories mapping application to develop an Indigenous map of Haudenosaunee1 Knowledge. Terrastories is paramount to helping Six Nations create a decolonial Indigenous map that compiles and visualizes community data and knowledge on top of a background map of traditional Haudenosaunee territory. Importantly, Terrastories facilitates the sharing of knowledge that is culturally relevant to Six Nations in accordance with Indigenous pedagogies. This is achieved by geolocating and embedding stories, oral histories, and observations that are documented in digital multimedia formats (e.g., pictures, videos, audio recordings, and text) in accordance with specific locations or points on a map. References to Ohneganos will be made throughout this chapter to help contextualize Terrastories and provide specific examples of its features being used. See Sect. 9.12: Brief Use Case (p. 206) for more information about Ohneganos and details of how the research program is using Terrastories in practice.

9.2 Ethics As a participatory mapping software, Terrastories regularly encounters several general areas of ethical concern and consideration. Six have been described below: • • • • • •

Community Input Local Community Ethics Protocols Free, Prior, and Informed Consent (…it is a continual process) Validating Individual Permissions Settings Legal Ethics (specific to a country or region) Ethics Connected to Research within Academic Settings

9.2.1 Community Input Community input is a crucial element of ethical consideration for Terrastories. The platform is designed to be community-led, as such, community input throughout the planning, documenting, and building of land-based maps is a vital component of the Terrastories process. In working with Terrastories, communities may decide upon their own input strategies to put in place that reflect their needs. This means the timelines for completing Terrastories projects can also vary depending on how the community approaches its role and the data input process.

 As per King (2007), “…Haudenosaunee is the Seneca word to denote the ‘People of the Longhouse’ and is sanctioned by the Confederacy of Six Nations to be the word used when referring to the Confederacy. The Mohawk word is Rotinohnsonni”. 1

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9.2.2 Local Community Ethics Protocols Local community ethics protocols refer to the cultural and social ethics established by communities. These ethical considerations are unique in each user case and can manifest in varying ways throughout the life of a Terrastories project. Formalized community ethics protocols are particularly common in Indigenous communities that have been heavily researched in the past or have frequent partnerships with non-community individual or organizational stakeholders. For Terrastories, community ethics are set and guided by the community utilizing the digital platform.

9.2.3 Free, Prior, and Informed Consent Consent is also a key ethical consideration at all levels of research, documentation, and land mapping related to Terrastories. The methodology for working with Terrastories recommends treating consent as an ongoing and continual process process, and continually seeking consent from the community through the community’s channels identified as best practice for their collective and individual needs. This also involves considering broader policy and ethics connected to research and development in each country or region in partnership with the community.

9.2.4 Validating Individual Permissions Settings As an extension of the consent and community input processes, it is possible to ensure that the permissions settings tied to a community’s Terrastories map reflect the request of both users and the community guidelines established by the broader community. This means permissions may exist in layers, where the single user has control to establish permissions settings that reflect their individual needs first. This is then followed by the broader settings guided through community consultation and agreement.

9.2.5 Legal Ethics (Specific to a Country or Region) Legal ethics refer to a country’s or government’s ethical considerations connected to data, human research participants, and copyright within a given country or region in which Terrastories is operating. Legal ethics can vary widely from place to place. Terrastories stewards work with partner communities to identify if there are legal ethics that must be considered in each region the platform is being used to collect data within. A basic example of this is adhering to a countries or provinces

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copyright guidelines for materials or stories (images, documents, oral stories) that are loaded into the Terrastories platform.

9.2.6 Ethics Connected to Research within Academic Settings In some instances, Terrastories use cases have involved partnerships with academic institutions. In such cases, Terrastories projects must also consider the partnering university’s ethical requirements for research or data collection with human participants. This is typically assessed through institutional Research Ethics Boards (REBs). Ethical considerations and associated applications are led by project leads who act on behalf of the university (or other academic institution). Notably, in Canada,  most government-sponsored research grants require adherence to the Government of Canada’s Tri-Council Policy Statement (TCPS2), specifically Chap. 8: Research Involving the First Nations, Inuit, and Metis Peoples of Canada. Review of these guidelines and best practices should be done prior to submitting ethics applications (community or institutional).

9.3 Costs The Terrastories application is free and open source. However, depending on where you use or host Terrastories, there may be hardware or server costs associated with Terrastories.

9.3.1 Online Hosting If you set up your own Terrastories server online, you will be responsible for cloud storage and data service costs. The total cost of this will largely be determined by the size of the media content uploaded to Terrastories, and your data service package. However, this may not need to be very expensive. For storage, the costs are very low. At the time of writing, AWS S3 Standard costs $0.023 per gigabyte per month. If the video files uploaded to Terrastories are compressed for web viewing, this is likely to be a very small amount even when considering hours of video footage, only several cents per month. For data services, the costs vary depending on your needs. At the time of writing, for serving the application using Heroku, there is a free tier that can support several users running the application concurrently and goes into sleep mode after 30 min of inactivity. There is also a hobby tier that costs $7 per month and can serve numerous users concurrently, never goes to sleep, can support an SSL certificate, and can be hosted on your own domain.

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For the online background map, Terrastories uses Mapbox.com, and usage is therefore subject to their pay-as-you-go pricing scheme. At the time of writing, Mapbox has a generous free tier that permits 50,000 monthly loads; afterward, the costs start to accrue at $5.00 per 1000 loads (see Chap. 2: Mapbox, Sect. 2.3: Costs, pg. 23). It is recommended to consider the long-term hosting costs for online hosting and set aside funding accordingly. How long (i.e., how many years) do you anticipate for your Terrastories server to be available online? How much might your Terrastories server grow with file content in that time? Terrastories as a volunteer organization also has their own server available for Indigenous and other local communities to utilize freely. However, if a community wishes to host their own server (i.e., for reasons of data sovereignty), the Terrastories team has guides available that detail how to go about doing so on the website https:// terrastories.app.

9.3.2 Offline Hosting If you set up Terrastories offline, there will be costs associated with hardware. You can install Terrastories on a local computer, which means that the costs will be the unit price of that computer. You can also install Terrastories as a “Field Kit”, or a mini-computer that automatically generates a Wi-Fi hotspot through which other devices can load Terrastories. At the time of writing, the following equipment is recommended for a “Field Kit” setup: • Intel NUC i7 Performance-G Kit (NUC8i7HVK): $819 (see Fig. 9.2) • RAM for Intel NUC i7: $73 • Internal SSD Hard Drive for Intel NUC i7: $88 You may also want to supply a beamer, speakers, keyboard, and mouse if you want to project Terrastories from the minicomputer during a collective workshop setting. For more information, the Terrastories team has guides available that detail how to go about doing so on the website https://terrastories.app.

Fig. 9.2  An Intel NUC i7 minicomputer used for hosting Terrastories offline

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9.3.3 Other Costs Most communities using Terrastories do not already have their maps and recordings of oral histories ready to be uploaded and published. You may therefore want to consider other costs relating to an oral histories mapping project, such as: • Equipment for mapping and recording • Compensation (i.e., incentives or honorariums) or stipends for community members or the project team • Logistical costs for travel and workshops • Software for cartography and media editing/production On the Earth Defenders Toolkit platform, there is a case study of a community in Suriname called the Matawai that built an oral histories mapping project around the use of Terrastories with support from the Amazon Conservation Team. In this case study, some of these other costs are named. The following guide can therefore also be useful as an insightful cost reference. Matawai: Place-based Storytelling in Suriname  – https://www.earthdefenderstoolkit.com/community/place-­based-­storytelling-­with-­the-­matawai-­in-­suriname/

9.4 Technical Level Terrastories has been directly co-created with Indigenous communities with limited experience working with digital technologies; therefore, it has been intentionally developed to require a very low level of technological literacy to use. By design, there are not a lot of options or tools built into Terrastories. This enables the tool to be easy-to-use and prioritizes its functionality to be effective at one primary task – namely, the visualization of how stories or other multimedia content relate to places on a map. The primary task is complemented by several simple secondary tasks or features, including the maintenance of a database of stories, places, and speakers, and deciding who has access to the data.

9.4.1 Front-End: Using and Administering a Terrastories Community Interacting with the Terrastories map and sidebar of stories does not require any technical skills and can be demonstrated to non-technical users with ease on both mobile and desktop platforms. Building, editing, and maintaining the Terrastories database, along with setting up user and story permissions, can both be done using the Administrative Menu (see Sect. 9.7: Data Privacy, pg. 202) and does not require any technical capacity. However, this latter task may require users to consider and

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implement several best practices around ensuring that the database does not become unwieldy, or accidentally granting permissions to restricted stories for users who should not have that heightened level of access. There is one slightly technical aspect to working with the administrative back-­ end – namely, that places are put on the map using latitude and longitude coordinates in a decimal degree’s format. Currently, a user must enter those manually into a field, rather than being provided with a user interface to “pin” the stories directly on the map. This has caused some issues for users who either (a) do not have a way to access location coordinates, or (b) have them in a different format such as degrees, minutes, and seconds (DMS), or a projected Universal Transverse Mercator (UTM) format.

9.4.2 Back-End: Setting Up Terrastories Setting up Terrastories for a community may require some expertise and external support. There are several components to consider here. • Cartography. A major feature of Terrastories is the interactive map on which the storied places are populated. This interactive map can be customized according to community needs and can be served via Mapbox Studio or any other tileserver that works with Mapbox GL (such as TileServer GL). If you need to customize your map, or use a map offline, somebody with cartography and geographic information system (GIS) skills needs to help create and style the map and ensure that it is accessible wherever Terrastories is being hosted. • Hosting. Some technical computer skills may be required, which will vary depending on whether Terrastories is hosted online or offline. There are step-by-­ step directions for both online and offline setup, but they involve interacting with interfaces that may feel unfamiliar or complex to a non-technical user (e.g., Amazon Web Services, Heroku, Docker, and command line). However, anyone with a background in server administration, software development, or mesh network/offline software will be able to work with these processes, and even more advanced computer users (e.g., someone experienced in GIS) will likely be able to follow the instructions without any issue. • Language. It is possible to translate Terrastories to any language, whether they are commonly spoken languages, minority languages, or Indigenous languages. A community or user can provide their own translations for all the Terrastories content, starting with an existing translation (such as English, Spanish, Portuguese, or Japanese) as a basis. You can then add that language using Terrastories’ localization tools, and it will be available as an option at the login screen (see Fig. 9.3).

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Fig. 9.3  Terrastories translated in the language of the Matawai Maroons of Suriname

9.4.3 Training and Capacity-Building Using Six Nations as an example, while the Ohneganos mapping project is still in its infancy, strategies for familiarizing community members with Terrastories have been successful through virtual workshops (e.g.,Haldimand Tract Workshop and Indigenous Mapping Workshop 2021) and from being featured on the research program’s vodcast (i.e., Ohneganos: Let’s Talk Water). Additionally, time and resources have been dedicated to giving Ohneganos team members the technical skills needed to give community members positive experiences with the mapping application and provide further front- and back-end training. See Sect. 9.12: Brief Use Case, pg. 206 for more details.

9.5 Inclusiveness By nature of its design, Terrastories functions to enable communities to map their own oral storytelling traditions, which places decisions for inclusion, distribution, and access to information on the community itself. This form of empowerment is linked to decolonizing geography and counter-mapping (Hunt & Stevenson, 2017) because Indigenous and other communities are structurally underrepresented decision-­ makers in dominant representations of global maps. In the case of Terrastories, these communities are instead centered as both architects and users of the maps they design and create. For inclusion of decision-makers, and participation in decision-making processes, is determined by the interplay of the Terrastories technology and the community engaging with the software. In terms of primarily technological concerns, Terrastories will require certain technical support during processes like initial

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set-up and map customization (see Sect. 9.4: Technical Level, pg. 197). However, these do not inhibit decision-makers and community leadership from participating in initiating or customizing their maps. Terrastories has been designed to be accessible on both desktop and mobile applications, as well as offline and online, which enables users to participate, adapt, and inform the map-building process without limitations based on internet access or device preference. This is a significant technological feature that addresses issues of digital divisions with respect to access to modern information and communications technologies between rich and poor regions globally, as well as rural and urban regions locally. As a participatory mapping platform, Terrastories has been designed to encourage all community members to provide input during the map-building process and it does so in an inclusive and culturally relevant manner. The interface is user-­ friendly and interactive, with both auditory and visual features, and allows people without technical backgrounds to engage with the development and use of Terrastories maps. Furthermore, Terrastories can be translated into any language, including minority and Indigenous languages, ensuring that the user base in a community is not restricted by language. Accounting for language variation can also address factors like generational differences in commonly spoken languages in a community. The language feature can also serve to enhance maps for users when it is relevant to tie place-based traditional knowledge to specific linguistic names. Lastly, decisions regarding which members of a community can directly input data and access data (when information is not entirely open access) will be autonomous decisions made by the community developing the map. For Ohneganos, Six Nations chose to have Ratikararò:roks (Story Gatherers) work with Haudenosaunee Knowledge Keepers, leaders, Elders, and other knowledge holders to record and document oral stories, sacred sites, and traditional knowledge. The level of access to the information gathered will depend on the nature of the information, which is governed by the local decision-makers leading the project.

9.6 Data Accuracy Terrastories was not designed with conventional notions of ‘data accuracy’ in mind. For instance, one core function of Terrastories is to be a platform that maps the oral histories that are shared through storytelling. Stories are not often characterized as being ‘right’ or ‘wrong’, which has implications in relation to data validation, verification, and accuracy. Stories and oral histories are complex, often symbolic, and metaphorical sources of information, that may contain subjective or qualitative data reflective of the beliefs, viewpoints, and lived experiences of the individual sharing the story (Cunsolo Willox et al., 2012). Oral stories, histories, and interactions with the environment are all examples of traditional knowledge. In the context of Indigenous communities and cultures, traditional knowledge, empirical knowledge, and spiritual knowledge make up three

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core components of Indigenous Knowledge (Dei et  al., 2000). Described by Daes (1994), …the heritage of an indigenous people…[is] a complete knowledge system with its own concepts of epistemology, philosophy, and scientific and logical validity. The diverse elements of an indigenous people’s heritage can only be fully learned or understood by means of the pedagogy traditionally employed by [the] peoples themselves. (pp. 2–3)

Definitions and understandings of data accuracy must therefore be reinterpreted within the context of a mapping platform that services Indigenous Knowledge about the natural world as opposed to Western Scientific environmental knowledge; the latter referring to the dominant and colonial knowledge system which typically prioritizes empirical knowledge, objective truths, and quantitative data over and above all else. For Terrastories, ‘data accuracy’ is better understood as the systems in place that consider if the stories and oral histories being shared are representative or in agreement with a community’s general understanding of the land and culture. As noted in the excerpt by Daes (1994), systems of validity and stewardship of Indigenous Knowledge can only be understood by Indigenous Knowledge Keepers and thus are the communities’ to dictate. One example of a mechanism commonly adopted by Indigenous communities to validate knowledge transferred orally is called “relational accountability” (Wilson, 2008). Central to relational accountability is attribution – describing details about the source of the story or knowledge being shared (i.e., where, who, when etc.). As a platform, Terrastories thus cannot (and should not) have the power to dictate the accuracy or validity of the knowledge or ‘data’ being shared, nor should the small group of often non-community support administrators. However, with a solid understanding of data accuracy within the context of Indigenous Knowledge, Terrastories does have systems, functions, and recommended processes in place to facilitate information screening to promote data accuracy. For instance, principally – and by design – as a decentralized knowledge platform Terrastories relies on the community to upload knowledge and information, which upholds the principle of ensuring the community (and its members) have the power to manage the information being contributed to the map. In practice, that means that, if community members have concerns with data or information that has been uploaded to the platform, they can raise their concern with the administrators and mapping support team and arrange for a dialogue to discuss the concern with the initial contributor. This way, members of the Terrastories community simultaneously act as sources of data (knowledge holders), users (learners), as well as stewards (knowledge keepers) on the platform. The Terrastories mapping community that is formulated creates an ongoing, dynamic, and recursive verification process for all information existing on the Indigenous map, which helps to materialize Terrastories core philosophy of being community-led. Another interpretation of ‘data accuracy’ within the context of Terrastories is related to relevance. This interpretation does not invalidate the stories or oral histories being shared but helps to ensure the data and information contained within the stories are relevant to the goals and scope of the map, as prescribed and outlined by

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the community. Depending on the nature or purpose of the Terrastories map being created, some data and information may fall outside of the map’s scope. Hence, the community may decide to (perhaps temporarily) exclude some stories shared or data collected. This community-informed screening procedure is achieved through the process of manually uploading all data and information to Terrastories. Input access is restricted to the number of users delegated as Admins and Editors (see Sect. 9.7: Data Privacy, pg. 202) who, upon reviewing the content, are tasked with uploading the data and information collected based purely on relevance (i.e., the nature of content, not the content itself). Restricting input access to a small number of mapping coordinators, as well as requiring all data that is input to be screened manually, is a rigorous (though labour intensive) process that ensures quality control and quality assurance with respect to data accuracy. To summarize, the community ownership and vetting process described earlier is a secondary validation process that takes place after the primary screening of information that occurs as a first step before information is uploaded to Terrastories. These are the systems, functions, and recommended processes in place to help ensure ‘data accuracy’, as reinterpreted within the context of Indigenous Knowledge.

9.7 Data Privacy Indigenous communities that use Terrastories to build maps own and control the data and information that is uploaded. Terrastories was designed with Indigenous data sovereignty; free, prior, and informed consent (FPIC); and the principles of ownership, control, access, and possession (OCAP) in mind (see Sects 9.2: Ethics, pg. 193 and 9.12: Brief Use Case, pg. 206). However, many Indigenous communities do not have the digital infrastructure or technical capacity to manage the required databases and servers on their own. Due to this limitation, the administrative back-end of Terrastories has been designed to be flexible to accommodate the specific needs of the communities that Terrastories is serving. Communities decide who can access a community space by assigning credentials to permitted individuals. In practice, these decisions are made by a body, such as a community mapping steering committee, who create user profiles (i.e., usernames and passwords) for each community member granted access to the Terrastories map (for Ohneganos, this is the Ohneganos mapping team, under the direction of the community leads). However, different levels of access and permissions are granted to users at the profile creation stage. Table 9.1 below describes the different ‘roles’ that can be assigned to each user and the associated permissions/restrictions (at the time of writing). In the future, it will be possible to define user permissions at a more granular level (i.e., per individual profile). Permissions are necessary because some information uploaded to Terrastories may be privy to a small number of community members (e.g., Knowledge Keepers). Restrictions may allow (or inhibit) some users from viewing and/or editing data and information. In some circumstances, the community may decide that some

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Table 9.1  Terrastories user roles and associated permissions Role Admin

Description No restrictions. Can access the Administrative Menu to create new user profiles and change Theme settings (background images, logos, custom map settings). Can add, edit, and manage all information uploaded. Editor Cannot access the Administrative Menu to create new user profiles or modify Theme settings (see ‘Admin’). Can add, edit, and manage all information uploaded. Member Cannot access the Administrative Menu (see ‘Admin’) or add, edit, and manage all information uploaded. Can only view data and information granted access to ‘Members’. Viewer Cannot access the Administrative Menu (see ‘Admin’) or add, edit, and manage any information uploaded. Can only view data and information granted access to ‘Viewers’. This is the most basic level of access, typically reserved for non-­ community members, providing access to publicly available information or data the community decides as being privy to the public.

knowledge and information is open to the public. In that case, they may either make available a general ‘Viewer’ login for the public or use a new feature in development at the time of writing, which will provide public access to the community’s space on a Terrastories server without needing to login, while still providing an option for community members to login to access information that has been hidden under various levels of restrictions.

9.8 Analytical Capacity As a visualization tool for mapping oral histories or other stories about places on an interactive map, Terrastories does not have any analytical capacities, strictly speaking. Terrastories may be used in an analytical way for a participatory decision-­ making process; for example, by overlaying Indigenous knowledge as expressed through stories over maps that show environmental impacts to show how Indigenous landscapes are being affected by extractivism. This kind of analysis would be extrapolated by users by looking at the map, and there are no inherent analytical capabilities built into the tool. However, this speaks to the ways in which Terrastories can be used in tandem with other applications as covered in this volume – the data and maps collected and compiled as a Terrastories background map may have been produced using sophisticated analytical methodologies, in applications such as Mapeo (see Chap. 3, pg. 41), Mapbox (see Chap. 2, pg. 21), QGIS, or ArcGIS and Survey 123 (see Chap. 8, pg. 169). There are several user tutorials, videos, and practical guides compiled on the Terrastories website on the How It Works page: https://terrastories.app/how-­it-­ works/. These tutorials do not require any technical expertise, and there is a live online demo to experiment with.

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9.9 Visualization Capacity Once places, speakers, and stories have been added to Terrastories, they can be interacted with and sorted in several ways: Through the Map View  One way to access the stories is by navigating the map and clicking/pressing on storied place markers. These appear as markers on top of the interactive map. Doing so will open a popup of that place with optional items like a photo, a description, the type of place that it is, and the region where it is located. It will also filter the stories on the sidebar to only those that are associated with the place. This can be useful for users who want to start exploring the map and learning about the history associated with different areas. Through the Sidebar  The other main feature of the Terrastories front end, alongside the interactive map, is the sidebar where the stories are located. A user can also click/press on a story card (before or after viewing any media content), which will trigger the map to travel to the place(s) associated with the story. This can be useful for users who are interested in stories but have not yet learned where they took place. Using the Filters  On the sidebar, there are also filters that allow the user to sort/ filter through both storied place markers on the map, and story cards in the sidebar. There are filters for speaker, region, topic, community, and type of place. These all function similarly – for example, you may use the speaker filter if you only want to view the stories shared by one speaker, and any places associated with those stories. Or you may choose to filter stories/places by type of place. All these filters will utilize the metadata provided by the community, and can therefore reflect community knowledge, categories, and taxonomies for how they think about stories and places. An Indigenous community may choose to have their own worldview and cosmology reflected in how they categorize types of places, opting for both natural categories (such as river, rapid, mountain) and cultural categories (such as specific categories of sacred or spiritual sites). For Terrastories users with permissions to access a community’s administrative back-end (see Fig. 9.4), they may also filter through the community data by Speaker, Story, and Place and there are search options available to help them find particular data.

9.10 Openness Terrastories utilizes the MIT Open Source License (https://opensource.org/ licenses/MIT). Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the “Software”), to deal in the

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Fig. 9.4  Screenshot from the administrative menu of Terrastories used by a technical session at the 2021 Indigenous Mapping Workshop (November 2, 2021)

Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions: As an entirely open-source application, Terrastories can be hosted on your own server, or hosted offline. Terrastories is built in alignment with principles of Indigenous data sovereignty, which in terms of hosting means that the data can be stored in a location of your choice. Exporting or backing up data will depend on the hosting environment. Some environments (like AWS/Heroku) allow for easy and regularly scheduled backing up of data. It is also possible to do an export of the whole Terrastories database via Rails, but this is a more technical task. Terrastories developers are planning on having an export option made available from within the Terrastories user interface sometime in the future. It is, however, already possible to batch import data into Terrastories from within the user interface. For more information on the technology stack architecture of Terrastories, see Fig. 9.5.

9.11 Accessibility Terrastories is an offline-first application, which means that it can be hosted online or offline entirely without any limitations of core functionality. As a web application, Terrastories can be loaded onto any platform (Mobile, Microsoft Windows,

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Fig. 9.5  Terrastories technology stack architecture (as of June 2020)

Mac, Linux), and the application is designed to be responsive, meaning it will render well on any platform including mobile phone (see Fig. 9.6). The application can be translated into any language, and text content is relatively minimal to allow the maps and media recordings to serve as most of the interface. At the time of writing, a near-term roadmap objective is to provide a place name pronunciation option where users can upload a recording of somebody pronouncing a place name out loud.

9.12 Brief Use Case In Winter 2020, Ohneganos Ohnegahdę:gyo approached the Terrastories Stewards Team  – a volunteer team composed of open-source developers and community engagement facilitators – seeking to use the Terrastories platform as a decolonial research tool that could support the broader goals of Ohneganos (see https://www. ohneganos.com/). Ohneganos is a research program comprising two subprojects, Co-Creation of Indigenous Water Quality Tools and Ohneganos  – Indigenous Ecological Knowledge, Training, and Co-Creation of Mixed-Method Tools. With the support of

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Fig. 9.6  Screenshot from mobile view of Terrastories used during a technical session at the 2021 Indigenous Mapping Workshop (November 2, 2021)

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Six Nations Elders and Indigenous and non-Indigenous academics, both project teams connect scientific water testing and measurements to Traditional Ecological Knowledge (TEK) and Indigenous oral traditions about the lands and waters at Six Nations. Collectively, the community-led projects conduct research from the perspective of acknowledging and embracing the culturally relevant spiritual, social, and ecological significance of the lands that support the community of Six Nations (Kemper, 2018). Within this context, the Terrastories platform (and other complementary tools, such as Mapeo), support Ohneganos and the community of Six Nations in the decolonization and Indigenization of their geospatial water data. Terrastories facilitates the community’s ability to layer this data with oral stories and sites of significance that are vital to the community’s well-being (Kemper, 2018).

9.12.1 Living Archive of Haudenosaunee Knowledge Digitizing Indigenous maps help to make them more engaging, interactive, and allows for them to reach a wider audience. The Terrastories digital map being developed by Six Nations will become a key component of the Ohneganos data platform and learning portal. Information that will be included in the map may include historic, sacred, or cultural sites of significance; changes in habitat and animal movement patterns; current locations (and historical changes) of culturally and/or ecologically significant plant and animal species (including extinctions such as pawpaw trees, Indigenous bees, fungi, etc.); and various other environmental data and ecological indicators. Importantly, all data will be tied to Indigenous place-­ names for land areas and water features. The data may be quantitative or qualitative geospatial data and, as a result, has been (and will continue to be) collected in a variety of ways, including through oral storytelling (i.e., open-ended interviews), by searching through secondary data and existing public and community resources, and through primary research being conducted by Ohneganos. The Indigenous place-names that will be researched place emphasis on the semantic conceptualizations of the local landscape and waters, which demonstrate deep cultural ties to geographic location by connecting language, history, and spirituality. A descriptive placename and its meaning, together with its spatial conception, can become the context for ‘knowing and learning’ and ensures the Indigenous language is meaningfully connecting people to ecological ways of being. All of the data tied to Indigenous placenames helps to preserve Indigenous Knowledge for future generations. Therefore, in addition to producing an Indigenous map, the practice of Indigenous mapping has been an excellent learning opportunity for our project partners and the Indigenous youth that are participating. This supports the project’s overall objectives of providing Indigenous Knowledge training, developing interactive educational resources, and promoting capacity building by fostering youth engagement and developing academic accreditation pathways.

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9.12.2 Ohneganos Mapping Team Structure The Ohneganos mapping team is overseen by the research program’s Principal Investigator, Dr. Dawn Martin Hill, and led by the Ohneganos Community Mapping Facilitator, Christopher Martin. Rudo Kemper, a Lead of Mapping and Earth Defenders Toolkit at Digital Democracy, is a Terrastories expert who has been hired to serve as a Project Advisor to support the implementation of Terrastories for Ohneganos and Six Nations.

9.12.3 Ethical Considerations Ohneganos addresses ethical concerns associated with the use of Terrastories through implementation of best practices and innovative solutions. Five strategies used by Ohneganos are listed and described below: • • • • •

Community-led Research Indigenous Data Sovereignty Ratiká:raton’s (Storytellers) & Ratikararò:roks (Story Gatherers) Ownership, Control, Access, and Possession (OCAP) Credits and Attribution Licenses

Community-Led Research The Ohneganos Terrastories project at Six Nations was initiated by the endorsement and support of the Haudenosaunee Confederacy Chiefs Council (HCCC). The HCCC has provided direction for the project, including identifying what local and historical knowledge exists about local landscapes, and what local and Indigenous Knowledge should be mapped to contribute towards Indigenous sovereignty, cultural revitalization, and climate resiliency. As the Terrastories project continues to develop at Six Nations, the formation of an Indigenous community-led Advisory Group composed of Haudenosaunee Elders, Knowledge Keepers, and Leaders could further guide the direction of the mapping at a more granular level. This group would help provide feedback on an ongoing basis and direct the focus of the Terrastories data collection at Six Nations. For instance, by identifying what types of knowledge is integral to incorporate into the platform (helping to define the scope), and how the data will be managed and curated throughout the project and after the project ends (and by whom). Future community input will range from Haudnosaunee Elders, Knowledge Keepers, and Leaders, to Six Nations youth and other community members in Six Nations. For example, while Elders, Knowledge Keepers, and Leaders can provide central guiding considerations, oral histories, and other knowledge, Indigenous youth  – such as students at the local language immersion school, Kawenní:io/ Gawęní:yo – can provide input into Terrastories mapping by engaging in technical

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training, embedding stories, and inputting ecological data. Community input must be undertaken in systematic conjunction with practices of continual consent. Indigenous Data Sovereignty The Terrastories community at Six Nations is protected using server/domain credentials. Administrators uploading knowledge into the platform can make data publicly available or restrict its availability by assigning restrictions/permissions, rendering the information only accessible by user credentials with a heightened level of access. To protect data entered and shared within the Terrastories platform, the Ohneganos mapping team will support the project’s leadership (e.g., the Advisory Group) in establishing their own series of user restrictions. This system ensures the data remains protected while also enabling all community members of Six Nations to access their cultural knowledge via the Terrastories application from anywhere in the world, at any time. For the Ohneganos project, all data entered directly into the Terrastories platform is hosted on a Terrastories AWS S3 Cloud bucket, physically located in Columbus, Ohio. In addition, data is stored with McMaster University in Hamilton and with the Ohneganos Team’s Google Drive. Eventually, through community consultation, the data connected to the Terrastories project at Six Nations will be fully hosted by the Six Nations of the Grand River community within a community-selected and governed digital repository. As the project evolves, the data will be centralized to ensure the community of Six Nations retains complete control over their intellectual property. Ratiká:raton’s (Storytellers) & Ratikararò:roks (Story Gatherers) For Ohneganos, the Speaker function (or input category) in Terrastories (as described in Sect. 9.1: General Information, pg. 190) is very important because it credits the Knowledge that is being given to us from the Ratiká:raton’s (Storyteller). This helps ensure ‘data accuracy’ through relational accountability (see Sect. 9.6. Data Accuracy, pg. 200). Those engaging with the Ratiká:raton’s, the Ratikararò:roks, are also an essential and integral part of the Ohneganos Terrastories project at Six Nations. Ratikararò:roks are involved in listening, recording, documenting, collecting, and mapping a wide array of stories and information about Traditional Ecological Knowledge tied to the people, lands, and waters at Six Nations. Importantly, Indigenous community members participating in the project as Ratikararò:roks consider a series of culturally-based ethics and research protocols as a component of their role in the project. To ensure both Ratikararò:roks and Ratiká:raton’s feel safe, respected, informed, and protected while participating in knowledge sharing, the Ohneganos mapping team put together a document titled: A Ratikararò:roks Training Guide for the Stewardship of Haudenosaunee Ecological Knowledge. The training guide introduces the project and a series of culturally relevant ethical, cultural, and spiritual guidelines unique to the Haudenosaunee and Six Nations Ratikararò:roks.

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The guide identifies the following nine principles, which all act as vital ethical considerations for Ratikararò:roks, as well as any community member engaging with Terrastories at Six Nations: • • • • • • • • •

Cosmology and Traditional Law Language Integrity & Honesty Respect Reciprocity Quality of life Protection of Indigenous Knowledge Acknowledgement of Traditional Protocols Intent

Ratikararò:roks (Story Gatherers) and all community members who use Terrastories at Six Nations are asked to engage these principals when documenting knowledge about the community of Six Nations through the application. The training guide, which outlines the principals in greater detail, is available for free through the Ohneganos project website (see  https://www.ohneganos.com/ indigenous-­mapping). Ownership, Control, Access, and Possession (OCAP) All stories and data gathered at Six Nations from Ratiká:raton’s (Storytellers), community members, and project participants for use in the Terrastories map are protected under the principles and guidelines of The First Nations Principles of Ownership, Control, Access, and Possession (OCAP) (Schnarch, 2004). OCAP refers to rules for how First Nations2 data and information can be collected, used, shared, or stored. OCAP acts as a resource to help Indigenous communities navigate sovereignty over their data and govern the information they provide or collect for research or projects about their communities, Nations, or Peoples (FNIGC, 2021). OCAP asserts that Indigenous communities own all data and control any data collection processes in their communities, especially those concerning their cultural knowledge (FNIGC, 2021). They alone have the right to decide how this information is disseminated, shared, and who has access. Lastly, possession refers to the data being physically stored on servers within communities. Currently, the Ohneganos Terrastories mapping team is in the planning stages of navigating project needs in relation to OCAP  (see Indigenous Data Sovereignty, pg. 204). Credits and Attribution Licenses In the context of Ohneganos, Terrastories will also provide opportunity for Ratiká:raton’s (Storytellers) to apply creative commons licensing to their posts or  In Section 35 of the consolidated Constitution Act of 1982, Canada legally groups Indigenous people into three broad categories. As per Section 35.(2), “In this Act ‘aboriginal peoples of Canada’ includes Indian, Inuit, and Metis Peoples of Canada” (Government of Canada, 2013). The “Indian” category is now commonly referred to as “First Nations”. 2

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traditional knowledge (TK) licensing as a component of credit attribution. TK contributed to the project will follow the TK Licenses concept, where appropriate. TK Licenses are based upon Creative Commons licensing (see https://localcontexts.org/ licenses/traditional-­knowledge-­licenses/). Where TK licensing is not appropriate, Creative Commons attribution will be applied (see https://creativecommons.org/ licenses/). This form of licensing allows Ratiká:raton’s (Storytellers) to indicate how their data and stories can be used and by whom. TK licensing provides a mechanism for granting culturally relevant attribution to contributed data and stories. This process within the Ohneganos Terrastories project is still unfolding and will be guided by the individuals who are contributing data to the project in partnership with project stewards, project advisors, and the community of Six Nations.

9.12.4 Training and Capacity Building Terrastories does not require a high degree of technical literacy to use (see Sect. 9.4: Technical Level, pg. 198). However, as a participatory mapping software, it does require collaboration and community buy-in, direction, and engagement. Additionally, to make best use of Terrastories, it is important to have a solid understanding of the social and environmental issues that drive the Terrastories guiding philosophy. Thus, education and capacity building is required to help familiarize communities with Terrastories. Some of the preparation work that has been performed by Ohneganos to-date has been offered in the form of the following four workshops: • • • •

Kawenní:io/Gawęní:yo Workshop and Youth Training Haldimand Tract Workshop ‘Train the Trainers’ Workshop Indigenous Mapping Workshop (IMW2021)

For more information about these workshops, visit https://www.ohneganos.com/.

9.12.5 Mapping and Data Collection Methodologies Introduced earlier, one of the ways in which community members have been engaged in the project is through Ratikararò:roks (Story Gatherers) talking and exchanging knowledge and resources with Ratiká:raton’s (Storytellers). To address ethics considerations, all participants are asked to provide written or oral consent before sharing their knowledge (see Sect. 9.2: Ethics, pg. 193). In terms of how this knowledge may be shared, several effective methods have been applied to gathering community knowledge, stories and resources.

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One of these methods is through simple one-on-one conversations. The Ratiká:raton’s (Storytellers) share their perspectives during a recorded interview which is then assessed for relevance by the Community Mapping Facilitator (i.e., the Ohneganos lead Administrator) and suitable components are then embedded into the Terrastories map (see Sect. 9.6: Data Accuracy, pg. 200). Aspects of the interview may be transcribed to text or kept as audio or video files. In either case, the knowledge is referenced to locations using Terrastories. As noted, the Ratiká:raton’s (Storyteller) is credited through the Speaker feature on Terrastories. Another method of accessing knowledge is through receiving resources (e.g., physical or digital data or files) from Ratiká:raton’s (Storytellers) to embed into Terrastories (see Fig. 9.7). These resources may contain stories, historical knowledge, and or any other type of relevant data. A final method proven to be effective at gathering data for Terrastories is the Firelight Group’s Direct-to-Digital method. Using this data collection methodology, Ratikararò:roks (Story Gatherers) and Ratiká:raton’s (Storytellers) use a digital map to place information on a map together and in real-time. Readily accessible mapping programs such as Mapeo or Google Earth can be used as a visual aid to help prompt the memories of Ratiká:raton’s (Storytellers) and can be pinned and described at the time of discussion for review and input into Terrastories at a later time. For a detailed description of the Firelight Group’s Direct-to-Digital method, see https://firelight.ca/wp-­content/uploads/2016/04/Guide_FirelightGroup_Direct ToDigital_20JAN2016.pdf.

Fig. 9.7  Screenshot from Terrastories used by Ohneganos to map Haudenosaunee traditional knowledge and information around the Six Nations of the Grand River reserve

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9.13 Comments and Recommendations The following six recommendations offer advice, suggestions, and insights for anyone considering using Terrastories for the purposes of Indigenous map-building. These important reflections, derived from implementing Terrastories in practice, are lessons learned from the Ohneganos mapping team.

9.13.1 Focus on Learning About Implementing Terrastories, How to Use the Tool Is Easy Terrastories is a relatively uncomplicated software that has been carefully designed to incorporate important nuances that address unique ideas surrounding Indigenous ethics, Indigenous Knowledge, and Indigenous sovereignty. It is not a highly technical or esoteric software to use (by design), but it does require a solid understanding of social and environmental issues within the context of Indigenous communities in order for users who may be supporting partner communities to take the right approach following inclusive and participatory methodologies. As such, it is recommended for users of Terrastories to become familiar with issues related to social and environmental justice within the context of Indigenous issues. A solid knowledge base in these areas is necessary to understand the various goals of Terrastories, what it is trying to achieve, and, therefore, how to use it properly and as intended.

9.13.2 Terrastories Is Primarily a Data Visualization Tool, Not a Data Collection Tool The primary purpose of Terrastories is to visualize stories about places on an interactive map. Depending on your use case, you may first need to start by putting together the background map that is used by Terrastories. For some use cases, a publicly available basemap such as OpenStreetMap or Mapbox Satellite is sufficient, but for many communities (especially Indigenous communities), it is important to show a custom map that shows the territory from their point of view, with landmarks and place names not found on publicly available maps. The creation of a custom map involves tools and processes outside of Terrastories. If data needs to be collected or mapped, a tool such as Mapeo or QGIS could be suitable. If you already have data and need to design a custom map, Mapbox Studio will allow you to do that. Similarly, for gathering and preparing information such as recordings of oral histories, this will need to take place outside of Terrastories, and it may be beneficial to have a process for storing, editing, and organizing multimedia content using other tools as well.

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9.13.3 Carefully Plan How to Gather, Add, and Manage Data To accommodate a wide range of approaches in how stories are shared by communities across the world, Terrastories is designed to be very flexible in structuring the Speakers, Places, and Stories data. A Place can have numerous Stories, so that more than one community member can add their own story, which may be unique or a different version of an existing story. Similarly, a Story can be related to multiple Places, and can have multiple Speakers. Depending on the community and use case, it may make sense to utilize a particular structure; for example, limiting stories to only have one speaker. It is up to you to implement this, and so it is good practice to consider how you want your Terrastories data to be structured in advance of starting a project, so you know what kind of data to collect and how to facilitate information gathering with the community.

9.13.4 Ethics Are Central, and Ongoing Plan out how you are going to engage and address ethical considerations from the onset; the underlying concepts behind the ethics are complicated and can be difficult to implement in practice. We recommend taking time to do this in advance of moving forward on a community-led mapping project to avoid ethics concerns or complications while the project is in operation. Much of this work relies on the participation, interest, and enthusiasm of the community leading the project and obstacles or roadblocks (such as ones arising from unresolved ethical issues) can significantly derail momentum that accumulates during the map-building process.

9.13.5 Plan for Safekeeping Your Data for the Long Term, in a Responsible Way When working with Terrastories, you will likely be gathering invaluable community stories and data, so we recommend having a solid plan for safekeeping that information on a very long-term basis and taking into consideration protocols for protection and data sovereignty (e.g., OCAP). While Terrastories is an excellent medium for visualizing recordings of place-based oral histories, it is not recommended to consider Terrastories as the primary repository where those recordings are kept. Instead, we recommend working with an archival entity that is well-equipped for setting up an archive where these recordings are stored indefinitely, who then work in accordance with your protocols for data protection, sovereignty, and permissions. For Indigenous data, a member institute of the Digital Endangered Languages and Musics Archives Network (DELAMAN) may be an appropriate entity to collaborate with, or there could be a local archive that is familiar with specific community

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protocols. Regardless of where you host Terrastories (e.g., online or offline), you should always have a backup of the data somewhere where it is not likely to be compromised or lost.

9.13.6 Information Gathering Is the Greatest Challenge: Be Innovative Collecting data and information for Terrastories takes time and involves human interaction. Developing relationships is key that often requires interacting with community members, especially when Terrastories has a central map-building team. Working during the COVID-19 pandemic was a major obstacle the Ohneganos mapping team had to overcome. Employing data collection methodologies in a virtual space, such as over video conferencing software, was one way the team was able to collect data for Terrastories while abiding by public health restrictions. Such strategies may also be useful for map-builders working with remote communities. Social media is also an effective way to communicate and recruit community members to the project. As a participatory mapping software heavily reliant on community engagement  - the more outreach, the better. Ultimately,  there are lots of opportunities for new ideas; work with communities to identify methods and approaches.

References Cunsolo Willox, A., Harper, S. L., & Edge, V. L. (2012). Storytelling in a digital age: Digital storytelling as an emerging narrative method for preserving and promoting indigenous oral wisdom. Qualitative Research, 13(2), 127–147. https://doi.org/10.1177/1468794112446105 Daes, E.-I. (1994). Special Rapporteur: Protection of the heritage of Indigenous people. United Nations Economic and Social Council. Dei, G. J. S., Hall, B. L., & Rosenberg, D. G. (2000). Indigenous knowledges in global contexts: Multiple readings of our world. University of Toronto Press. First Nations Information Governance Center (FNIGC). (2021). The First Nations Principles of OCAP®. https://fnigc.ca/ocap-­training/ Government of Canada. (2013). A consolidation of the Constitution Acts 1867 to 1982 (Vol. 94, Issue 4). The American Association of Teachers of Spanish and Portuguese, Inc. Hunt, D., & Stevenson, S.  A. (2017). Decolonizing geographies of power: Indigenous digital counter-­mapping practices on turtle Island. Settler Colonial Studies, 7(3), 372–392. https://doi. org/10.1080/2201473X.2016.1186311 Kemper, R. (2018). From the Amazon to the Great Lakes: Sharing knowledge with First Nations communities in Canada. Terrastories. https://terrastories.io/from-­the-­amazon-­to-­the-­great-­ lakes-­s haring-­k nowledge-­a nd-­m apping-­o ral-­h istories-­w ith-­first-­n ations-­c ommunities-­ in-­Canada/ King, J. T. (2007). The value of water and the meaning of water law for the native Americans known as the Haudenosaunee. Cornell Journal of Law and Public Policy, 16(3), 448–472. http://scholarship.law.cornell.edu/cjlpp%0A http://scholarship.law.cornell.edu/cjlpp/vol16/iss3/1

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Schnarch, B. (2004, January). Ownership, control, access, and possession (OCAP) or self-­ determination applied to research. Journal of Aboriginal Health, 80–95. https://jps.library.utoronto.ca/index.php/ijih/article/view/28934 United States Caucus of the Traditional Ecological Knowledge Task Team (US TEK Task Team). (2021). Guidance document on traditional ecological knowledge pursuant to the Great Lakes water quality agreement. https://www.bia.gov/sites/bia.gov/files/assets/bia/wstreg/Guidance_ Document_on_TEK_Pursuant_to_the_Great_Lakes_Water_Quality_Agreement.pdf Wilson, S. (2008). Research is ceremony: Indigenous research methods. Fernwood Publishing. https://search.library.wisc.edu/catalog/9910125360602121

Recommended Readings Brown, G., & Kyttä, M. (2018). Key issues and priorities in participatory mapping: Toward integration or increased specialization? Applied Geography, 95, 1–8. https://doi.org/10.1016/j. apgeog.2018.04.002 Castellano, M. B. (2004). Ethics of aboriginal research. Journal of Aboriginal Health, 1, 98–114. Digital Democracy. (2021). Terrastories: A tool for place-based storytelling. Earth Defenders Toolkit. https://www.earthdefenderstoolkit.com/toolkit/terrastories-­a-­tool-­for-­place-basedstorytelling Fernández-Llamazares, Á., & Cabeza, M. (2018). Rediscovering the potential of Indigenous storytelling for conservation practice. Conservation Letters, 11(3), e12398. https://doi.org/10.1111/ conl.12398 Kemper, R. (2019). Mapping and recording place-based oral histories: A methodology. https:// www.amazonteam.org/wp-­c ontent/uploads/2019/12/ACT_OralHistories_Guide_2019_ ENGLISH.pdf Kovach, M. (2009). Indigenous methodologies: Characteristics, conversations, and contexts. University of Toronto Press. Martin-Hill, D., & Soucy, D. (2005). Ganono’se’n e yo’gwilode’: Ethical guidelines for aboriginal research elders and healers roundtable. http://www.ihrdp.ca/media/docs/lega4e54fe5d0c807-­ ethical%20guidelines%20for%20aboriginal%20research.pdf McGurk, T. J., & Caquard, S. (2020). To what extent can online mapping be decolonial? A journey throughout Indigenous cartography in Canada. The Canadian Geographer/Le Géographe Canadien, 64(1), 49–64. https://doi.org/10.1111/cag.12602 Ollivierre, A. D., Burnett, C. M., & Hetoevėhotohke’e Lucchesi, A. (2021). Participatory mapping. In International encyclopedia of geography (pp. 1–9). https://doi.org/10.1002/9781118786352. wbieg1155.pub2 Thornhill, N. (2020). A Ratikararò:roks (story gatherers) training guide for the stewardship of Haudenosaunee ecological knowledge. https://static1.squarespace.com/ static/5a0cddae51a584d71fb23968/t/6244f2fb4532687d792d58e8/1648685820728/ Terrastories+at+Six+Nations_A+Story+Gatherers+Training+Guide.edited.pdf

Chapter 10

Ushahidi

Janet Marsden and Angela Oduor Lungati

Abstract  Ushahidi is a crowdsourced information sharing platform developed following the December 2007 general election in Kenya. Election protests and rioting broke out when the government claimed victory in the disputed election and shut down the national media to prevent information sharing and free speech. Because of the government ban on media, in early January 2008 Ory Okolloh, a freelance journalist in Nairobi asked people to report incidents of violence they were experiencing on her personal blog (weblog). She was quickly overwhelmed by the numbers of emails and messages she received. Focusing on the urgent need to share the information she was receiving, in early January she posted another request on her blog asking for help to develop a website where people could post anonymously online or via mobile phone text messages. Several technically astute, mainly Kenyan volunteers responded and within a day, the Ushahidi (Swahili for ‘testimony’) domain was registered, and the website went live in less than a week. More than 250 people began using the site immediately to share information and within a few weeks Ushahidi became one of the main sources of news about the unrest. Participants eventually grew to 45,000 users, including radio stations. The ability to post directly to the site using mobile phone text messaging meant it was available via the most widely accessible type of communications technology at that time in Kenya. The project was funded with donations, with many volunteer developers. Later the platform was adapted for crisis mapping during disease outbreaks in other countries in Africa and natural disasters such as the Haiti earthquake in 2010. Keywords  Emergency response · Emergency communication · Crisis mapping

J. Marsden (*) Syracuse University, Syracuse, NY, USA e-mail: [email protected] A. Oduor Lungati Ushahidi Platform, Nairobi, Kenya e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 C. M. Burnett (ed.), Evaluating Participatory Mapping Software, https://doi.org/10.1007/978-3-031-19594-5_10

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10.1 General Information Name of Application: Ushahidi Name of Developer: Ushahidi Name of Funder: Ushahidi receives funding from many corporate and private sources: MacKenzie Scott, Stefan Thomas (CEO of COIL), the Rockefeller Foundation, the MacArthur Foundation, USAID, CISCO, Digital Impact Alliance (DIAL), Google.org, the Ford Foundation, Humanity United, the Knight Foundation, UKAID, and many others. Type of System Software: Open Source GNU/Linux (HVM), Google Maps, Google Earth Type of Programming Language: SiLCC, Open-Source HTML, Frontline SMS API Availability: None Features: A broadly available platform for collecting and visualizing information directly from people experiencing or responding to crises. Ushahidi is a non-­ profit tech company specializing in developing free and open-source software for information collection, visualization, and interactive mapping. Cost: Free for grassroots and not-for-profit groups aligned with Ushahidi’s mission with income below US $250k annually. Mission-aligned groups with higher income levels are charged on a sliding scale according to their ability to pay. Pricing has since been waived since the outbreak of COVID-19. Type of Data Collected: Ushahidi collects citizen generated data via SMS, Email, Twitter, Web and smartphone apps, and uses a map-based user interface to display this data, allowing marginalized groups to share information for crisis response, human rights protection and good governance. Overview: Ushahidi was originally developed in 2007 as a website using modular, adaptable, and self-managing end-user components combined in mashups. Its software development team was largely composed of spontaneous volunteers. By combining existing software using rapid application development, the team was able to build the original platform in a very short time in response to a crisis in Kenya. The Ushahidi system is framed as a dynamic, non-profit virtual organization developed in the context of emergency response. In 2008, development of its alpha version was funded by a grant from the nonprofit group Humanity United. It was released and tested in late 2008 in the Democratic Republic of Congo, among other places. The beta version was released in 2009, utilizing Frontline SMS, free software that turns a laptop and a mobile phone or modem into a central communications hub. The Frontline SMS software, originally released in 2005, is a cross-platform simple messaging service which can be used on a single laptop computer without the need for the internet, allowing users to send and receive text messages with large groups of people through mobile phones. Since its original release in 2005, Frontline SMS has been widely adopted in the grassroots non-profit community and nominated for several awards. The combination of Frontline SMS’s messaging capabilities with

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Ushahidi’s map-based interface made it possible to locate respondent’s locations (Banks & Hersman, 2009). Ushahidi’s commitment is to raise the voices of marginalized and underrepresented communities by enabling them to rapidly and purposely gather, analyze, respond and act on data and information about their communities. Ushahidi is named with the Swahili word for testimony. The platform was originally developed to give ordinary people in crisis a voice, access to information and the ability to communicate. In Kenya, following the December 2007 general election, election protests, rioting and violence broke out. The national media had limited capacity to report everything happening on the ground. Because of this, in early January 2008 US educated Kenyan journalist Ory Okolloh solicited information about incidents of violence from ordinary people in the form of comments posted on her personal weblog (blog). Okolloh was quickly overwhelmed by the numbers of emails and messages that she received. To focus on the “immediate need to get the information out,” (Okolloh, 2009) in early January, she posted a request on her blog for help to develop a website where people could post anonymously online or via mobile phone text messages. Built by 15–20 mainly Kenyan volunteers using open-source software based on Google Maps and Frontline SMS, the project was funded entirely by donations, with many volunteer developers. Within a day the Ushahidi domain was registered, and the website went live within less than a week. More than 250 people began using the site immediately to share information. Participants eventually grew to 45,000 users, and even included radio stations. Within a few weeks Ushahidi became one of the main sources of information about the unrest. The ability to post directly to the site using mobile phone text messaging meant it was available via the most widely accessible type of communications technology in Kenya. Later it was used for crisis mapping during disease outbreaks and natural disasters including the 2010 earthquake in Port-au-Prince, Haiti (Munro, 2010). The platform is designed to be deployed in areas with limited technology infrastructure, by people with little technical experience, and used by anyone with access to a mobile phone. Following the events in Kenya, Humanity United, a non-profit organization dedicated to ending modern slavery and mass atrocities, offered to fund redevelopment of Ushahidi as a broadly available platform for collecting and visualizing information. Ushahidi was transformed from its early origins as a personal blog by journalist Ory Okolloh, into a non-profit tech company specializing in developing free and open-source software for information collection, visualization, and interactive mapping. The goals of Ushahidi the company are to “build tools for democratizing information, increasing transparency, and lowering the barriers for individuals to share their stories”. Ushahidi defines itself as “a disruptive organization that is willing to fail in the pursuit of changing the traditional way that information flows” (Ushahidi, 2022).

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10.2 Ethics The Ushahidi name comes from the Swahili word for “testimony,” chosen upon its founding to reflect how technology gave voice to the people of Kenya during a time of social and political unrest. Ushahidi carries its commitment to amplifying voices, empowering communities, and fostering change to this day, seeking to foster a world in which communities are thriving and just. Ushahidi is a global not-for-profit technology company that develops integrated tools and services to enable people to generate solutions and mobilize communities for good. Ushahidi builds open-source software with the intent of strengthening communities and improving lives, empowering users to gather, analyze, respond, and act on data and information rapidly and purposefully. Since its founding in 2008 as a tool to monitor and map post-election violence in Kenya, Ushahidi’s crowdsourcing tools have been used by thousands of groups and millions of people to raise voices, inform decisions, stop suffering, and influence change (Ushahidi, 2022).

10.2.1 Code of Conduct Ushahidi is a not-for-profit company with a mission to serve and empower marginalized communities for good, improve lives, and end suffering. Special emphasis is placed on helping to develop Latin American and African countries by using technology to improve the lives of ordinary people by enabling communication and access to information. Ushahidi is a humanitarian platform intended to empower communities and those in crisis by increasing agency, participation, and communication capabilities of ordinary people. Ushahidi is particularly aimed at serving marginalized people and communities. Ethical concerns include protecting privacy and ensuring users’ safety and security while allowing access to data, determining how to afford access to data while maintaining protections, ensuring data quality and meeting provenance concerns related to crowdsourcing (Ushahidi, 2022).

10.3 Cost Small nonprofits and grassroots organizations that are aligned with Ushahidi’s mission and can demonstrate a yearly operating budget of less than $250k USD per year are invited to apply for a free Basic plan. Organizations with a revenue over $250k are charged according to their ability to pay. All those interested are welcome to try the free Ushahidi Demo version before purchasing. Ushahidi is committed to serving the underprivileged and ensuring that cost is not a barrier to using Ushahidi. For example, Ushahidi waived fees for COVID-19

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response to ensure there would be no barriers due to cost to its use during the pandemic (Ushahidi, 2022).

10.4 Technical Level Ushahidi is server-based (i.e., it must be installed on a server) and can be configured for different locations and situations. Ushahidi offers two options. The first is to host Ushahidi from your own server, the second is to deploy Ushahidi hosted by Ushahidi’s corporate servers. The first is more demanding as it requires the capacity to provide, setup, and maintain the server hardware and software environment. The use of Ushahidi either through engagement with stakeholders using guides or chauffeurs, is a choice to be made by those that are deploying the platform. The Ushahidi platform is designed for versatility and has been adapted for many different purposes. The main objective is to ensure as few barriers as possible for effective use of the platform. Its development and use have been geared towards areas and people with limited infrastructure and technical experience. Ory Okolloh characterized the Ushahidi development strategy as: “embrace the rapid prototype model and focus on pushing the boundaries of the various areas that the platform focuses on – crowdsourcing, visualization, mapping, and mobile phone platforms.” The Ushahidi software has continued to evolve. There are several open-source products available in addition to Ushahidi. The Ushahidi platform is a downloadable software product that enables the collection and sharing of map based crowdsourced information using mobile phones, email, or the internet. Crowdsourcing refers to using the public for problem solving and work. Ushahidi uses OpenStreetMaps or Google Maps to create geocoded and timestamped event archives from users’ information posted via an SMS interface. Geocoding, the use of locational data to position information on a map, is used to capture geospatial data. Locational data can be based on GPS (global positioning system) points, street addresses, zip codes, compass points, etc. Temporal data is captured using timestamping. Ushahidi can be used along with the following software: • Crowdmap application was a cloud-based version of the Ushahidi platform launched in 2010 that could be very quickly deployed without the need for a server installation. CrowdMap had a feature like Foursquare to allow users to add their own tags to its sites. It was discontinued in 2021 following enhancements to the Ushahidi platform incorporating its functionality. • The SwiftRiver platform, built in 2009, was a downloadable software product built from real-time information processing APIs (application programming interfaces) designed to rapidly handle the overwhelming quantities of data reported in the early hours of a disaster. SwiftRiver was shut down in 2015, but its code is still available as open source via Ushahidi’s website hosted Wiki. • BRCK is a rugged, cloud managed, full-featured modem/router with built-in failovers and programmable GPIO expansion. BRCK makes accessing the inter-

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net simple and reliable wherever you are. Since the creation of the original BRCK v1 in 2013, more products have been developed: the Kio Kit for education, and the SupaBRCK for enterprise connectivity, computation, and storage, and the PicoBRCK for rugged IoT needs. The solutions fit local infrastructure needs in both urban and rural areas where electricity and internet connections are problematic and is on the cutting edge of meeting frontier market technology needs for connectivity. In 2019, BRCK acquired Surf, another internet provider, becoming the largest public Wi-Fi network in sub-Saharan Africa. • SMSsync (2010) is a free and open-source SMS gateway for Android – a simple, yet powerful SMS to HTTP sync utility that turns any Android phone into a local SMS gateway by sending incoming messages (SMS) to a configured URL (web service). SMSsync, as of now, has been completely translated into five languages. Ushahidi is seeking participants to assist in building the gateway in many forms from writing documentation for the project to translating the app into other languages (Ushahidi, 2022).

10.5 Inclusiveness The Ushahidi development strategy is characterized as: “embrace the rapid prototype model and focus on pushing the boundaries of the various areas that the platform focuses on  – crowdsourcing, visualization, mapping, and mobile phone platforms” (Ushahidi, 2022). In other words, the focus is on the end user, and the aim of the platform is maximizing accessibility, communication, and the free flow of information. Essentially, inclusiveness is more about the process rather than the software. Like statistical surveying, systematic error introduced into sampling or testing by selecting or encouraging one outcome or answer over others is always an issue (Ushahidi, 2022).

10.6 Data Accuracy Ushahidi relies on crowdsourcing for its incident reporting data. The crisis map interface provides a geographic reference for each data point. Crisis maps are built from Google Maps or OpenStreetMaps. This ensures geographic accuracy and locational reliability. Data points are created by any individual that posts to the map. Multiple reports of the same events from the same area can provide a certain level of reliability. Contradictory reports can be identified and potentially resolved through crowdsourcing as well as through secondary sources of information. Originally, Ushahidi initiated a simple manual report verification process. If a reporter could be identified, they were contacted for verification; if anonymous, a certain volume of similar reports was considered verification. Because of the tense

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political situation and the mainstream media blackout, many people were reluctant to identify themselves. Unverified reports were posted in any case and were tagged as unverified. Within weeks hundreds of incidents of violence had been documented in detail that otherwise would have gone unreported. The website received hundreds of thousands of visits from around the world, sparking global media attention (Okolloh, 2009). The SwiftRiver open-source toolkit, developed in 2009, was designed to accomplish three tasks: structure unstructured data, conditionally filter and prioritize real time content, and provide context, especially location. These are tasks which are critical for rapid response in an emergency or natural disaster. SwiftRiver accomplished these tasks through applications for natural language/artificial intelligence processing, SMS and Twitter data mining, and information source verification. The SwiftRiver project is no longer actively maintained and was sunset by Ushahidi. You can access resources about it from the Ushahidi Wiki (https://wiki.ushahidi. com/wiki.ushahidi.com/display/WIKI/SwiftRiver.html) (Ushahidi, 2022).

10.7 Data Privacy Ushahidi operates on the belief that the data collected via the software is owned by the users of the platform. The users are responsible for access, privacy, verification, and protections. In any case, end users own their own data, and as such are responsible for privacy in terms of not disclosing what they do not wish to disclose. Ushahidi has always allowed users to post anonymously. Today, there are still many users that wish to remain anonymous for various reasons. The future direction of Ushahidi includes plans to continue leveraging artificial intelligence (AI) and machine learning to improve verification while protecting privacy. Ushahidi uses a variety of industry-standard technologies and services to secure all transmitted and collected data from unauthorized access, disclosure, use, and loss. This includes but is not limited to encrypting all data in transit using SSL standardized server configurations including sensible security defaults, such as hardened SSL configuration and restricting open ports where possible. This includes limiting internal communication between services to internal private networks. Ushahidi takes reasonable administrative, physical, and electronic measures designed to protect any information that is collected from or about users (including PII) from unauthorized access, use or disclosure. However, no method of transmitting information over the Internet or storing information is completely secure. Accordingly, Ushahidi cannot guarantee the absolute security of any information. Ushahidi is also committed to protecting users’ personal information once obtained. Ushahidi has implemented physical, business, and technical security measures and continues to update these. Despite these efforts, if Ushahidi learns of a security breach, users will be notified in order to take appropriate protective steps (Ushahidi, 2022).

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10.8 Analytical Capacity Although Ushahidi was originally built to put dots on a map, the v3 platform removes the assumption of building a geospatial analysis. Data can be visualized as charts, graphs, and/or maps, or even viewed as textual narrative. This freedom also gives the user more responsibility to plan what data will be needed for analytics and visualization. Ushahidi is designed to allow many sources to contribute facts to a central dataset, from which additional facts might be inferred. For example, many sensors reporting rising water in one village may cause analysts to infer that water is going to rise downstream. Many people reporting fraud at a particular polling may allow analysts to infer that something is amiss; they may then choose to correlate voting patterns with the allegations of fraud (Ushahidi, 2022).

10.8.1 Data Management The Ushahidi platform provides you with modes to not only visualize your data in different ways, but to also manage it. Modes are designed for the discrete and specific actions users need to take within the platform, to make the platform more intuitive and action-oriented for different user types on a deployment. Ordinary viewers of a deployment can access three different modes as shown below: Map view, Data view or Activity view (Ushahidi, 2022).

10.8.2 Map View The Map View mode displays all published posts on a map, including: • Each post appears as an icon on the map. There is an option to combine nearby posts on the Map that will cause posts adjacent to each other on the map to cluster together, displaying a number denoting number of posts combined. • Clicking on each individual post displays a small popup box with the post title and description. • You should also be able to zoom in and out of the map as desired (Ushahidi, 2022).

10.8.3 Data View The Data View allows viewing, triaging, and managing posts coming into a deployment as a chronological list of events over time. Data View provides a split pane that lists summaries of posts received on the left pane, and details of posts and editing features on the right pane (Ushahidi, 2022).

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10.8.4 Activity View The Activity View mode gives a summary of how users are interacting with a deployment over time. Activity can be seen in chart or graph form. Activity view allows comparison of activity over time. Post counts can be filtered in a line chart over time showing: • • • •

All posts Categories that the posts belong to Surveys that the posts were submitted to Status (i.e., whether the posts are published or not)

Post counts can be viewed on the graph as cumulative totals of Activity by Volume. Post counts can be filtered in a bar chart by volume by: • Categories that the posts belong to • Surveys that the posts were submitted to • Status i.e., whether they’re published or not (Ushahidi, 2022).

10.8.5 Saved Searches Saved searches are dynamic groupings of posts that match parameters chosen in filters. They are dynamic because as new posts are added that fit the search criteria, they will show in the saved search automatically, and without manual intervention. Saved searches are particularly useful for managing workflows and teams on your deployment. They allow you to set filters for information that’s relevant to each working group/team. For example: • It is useful for a team tasked with structuring to only see posts that are unstructured. Creating a saved search with these parameters can be useful. • A team tasked with publishing needs to only see posts that are yet to be published, so creating a saved search with these parameters can be useful. • Please note that only registered users can create Saved searches. Nonregistered users can only view public searches (Ushahidi, 2022).

10.8.6 Collections A “Collection” is a manually curated grouping of posts. It is not dynamic, meaning the posts within it do not change unless they are manually updated. Collections are useful in grouping posts that you would like to share with external partners. For example, it may be useful to add all posts that require escalation to a collection and

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then export the data in that collection in a .CSV file that can be shared with partners. Please note that only registered users can create Collections. Nonregistered users can only view featured public collections (Ushahidi, 2022).

10.9 Visualization Capacity The Harvard University Berkman Center for Internet & Society case study of Ushahidi stated, “Far and away the most prominent and successful digital civic campaign was Ushahidi” (Goldstein & Rotich, 2008). Ory Okolloh initiated the project with the following post to her blog: “Google Earth supposedly shows in detail where the damage is being done on the ground. It occurs to me that it will be useful to keep a record of this, if one is thinking long-term. For the reconciliation process to occur at the local level the truth of what happened will first have to come out. Guys looking to do something – any techies out there willing to do a mashup of where the violence and destruction is occurring using Google Maps?” (Goldstein & Rotich, 2008). David Kobia and Erik Hersman, two technologists with roots in Kenya, answered Okolloh’s request. Leading a small group of volunteers, they designed Ushahidi in 1 week and launched the initial Ushahidi platform. Ushahidi was originally a mashup or blending of two Internet applications, Google Maps and Frontline SMS. In its earliest form, Ushahidi used Google Maps mapping services to display manually added text messages and emails to map locations. Ushahidi developers then added FrontlineSMS to the Google Maps interface to allow users to zoom in and view orthorectified satellite photography images of Kenya and created tools for users to report incidents of violence on the map via mobile phone or Internet browser and to create visualizations of the data. The FrontlineSMS messaging tool is an open-source API released in 2005 that enables users to utilize any computer as a communications hub for simple text messaging via internet or cell phone. FrontlineSMS can operate without an internet connection. It was originally developed to monitor wildlife in nature preserves and parks and was adapted for use to provide healthcare in Africa via the FrontlineSMS: Medic version of the API (Banks & Hersman, 2009; Freifeld et al., 2010; Fellett, 2011). “FrontlineSMS is free software that turns a laptop and a mobile phone or modem into a central communications hub, allowing users to send and receive text messages with large groups of people through mobile phones. The software – originally developed in 2005 and updated in 2007 – is being used around the world for a wide range of non-profit activities including the sending of market prices and other agricultural data to smallholder rural farmers in Aceh, Cambodia and El Salvador, the dissemination of news in Iraq, the sending of security alerts to fieldworkers in Afghanistan, for human rights work in places such as Zimbabwe, Pakistan and the Philippines, and the running of a rural healthcare network for 250,000 people in Malawi. Because the software can be used on a single laptop computer without the need for the internet, it has been widely adopted among the grassroots non-profit

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community and nominated for several awards. Real time situation awareness, visualization, verification” (Banks & Hersman, 2009). Figure 10.1 shows the original Ushahidi deployment in Kenya using Google Maps and Frontline SMS. The map-based interface visually represents data geolocated using Google Maps. Each red dot represents a user post. Data can be exported as .csv files. The Ushahidi platform was strenuously tested in the aftermath of the earthquake centered in Port-au-Prince, Haiti. One of the biggest challenges was the need to translate messages in many languages spoken by emergency workers, including Haitian Kreyol, French, English, and other languages. Very quickly, Ushahidi was deployed by the United Nations and used effectively to crowdsource thousands of volunteer translators. The deployment was called Mission 4636 for the 4-digit mobile telephone exchange used to receive text messages. The UN reported that the average turn-around from a message arriving to the application in Kreyol to it being translated, categorized, geolocated and streamed back to the responders was 10 min. In the first week alone more than 1000 people came online to help translate messages as they arrived. Figure  10.2 shows an image from a later deployment of Ushahidi in the aftermath of the Port-au-Prince, Haiti earthquake in 2010 (Munro, 2010).

Fig. 10.1  Screen shot of the original 2007 Ushahidi deployment in Kenya

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According to the United Nations, Ushahidi was the only emergency reporting and response service available to people within Haiti following the earthquake. Ushahidi assisted in directing aid through coordinating crowdsourced volunteers participating all over the world. The translators and the Ushahidi mappers were both aided by a parallel crowdsourcing effort. The devastation from the earthquake changed the area drastically making directions and maps obsolete in minutes. Volunteers combined satellite imagery, offline maps, and reports from people in Haiti using GPS devices, to add thousands of data points to OpenStreetMap, taking the number of labeled roads and landmarks from dozens to thousands in just a few days. Hundreds of lives were saved, and first aid was able to be directed to tens of thousands (Marsden, 2013; Munro, 2010).

10.10 Openness Ushahidi is built on open-source software. It can be hosted on your own server or Ushahidi can host. Data can be exported via .csv and maps can be linked with data overlays. Ushahidi originally used Google Earth because in the immediate term, it shows in detail where damage or change is occurring on the ground. For the long-term, this means that a record can be made and preserved, allowing the truth of what happened to come out and to be preserved. Ushahidi was originally a mashup of two Internet applications: Google Maps and Frontline SMS. In its earliest form, Ushahidi used Google Maps mapping services to display manually added text messages and emails

Fig. 10.2  Locations of interactions between people collaborating to translate messages in the first week of Mission 4636. Each dot represents a person contributing to the online chatroom used for collaboration between translators

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to map locations. Ushahidi developers then added FrontlineSMS to the Google Maps interface to allow users to zoom in and view orthorectified satellite photography images of Kenya and created tools for users to report incidents of violence on the map via mobile phone or Internet browser and to create visualizations of the data. Currently, Ushahidi uses OpenStreetMap as it’s default map base layer, encouraging it’s community to contribute to improving these maps directly from within the platform. The Ushahidi development strategy has been characterized as embracing the rapid prototype model and focused on pushing the boundaries of the various areas that the platform focuses on crowdsourcing, visualization, mapping, and mobile phone platforms (Ushahidi, 2022; Marsden, 2013).

10.11 Accessibility The Ushahidi software is available for download from Github or sign up from the website. The software uses a mobile text messaging version with its user interface. The software is hosted on a server and accessible via text message for input. The platform allows for data collection not only via text message, but via smartphone applications, web, USSD, and most recently, whatsapp. It’s also made available in over 45 different languages, in line with making it accessible to as many audiences as possible. The software has been widely adopted among the grassroots non-profit community and nominated for several awards, offering real time situation awareness, visualization, and verification. The accessibility of the technology is exemplified by its use in over 160 countries, over 200,000 times since inception in 2008.

10.12 Brief Use Case The Ushahidi and CrowdMap application have been cited for effectiveness, robustness, and ease of use in multiple contexts, from crisis response and management on a staggering scale such as the 2010 Port-au-Price, Haiti and the 2011 Fukushima nuclear disaster, to assistance at the local level with disease tracking and incident response, including most recently, COVID 19 tracking and reporting. For more information and examples, please check the 2018 impact report and case studies, available from the Ushahidi website. Table 10.1 shows some of the early deployments of Ushahidi and the technical development that drove the widespread use of the platform in a myriad of crisis situations, from political unrest, disease outbreaks, public health outreach, earthquakes, floods, hurricanes, and wildfires. The Ushahidi Platform helps communities turn information into action with an intuitive and accessible crowdsourcing and mapping tool. By enabling the rapid

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Table 10.1  Partial chronology of early Ushahidi Development deployments (Marsden, 2013) Phase Inception (2007–2008) Expansion (2008)

Deployment (2008–2009) Enhancement I (2010)

Applications Initial Ushahidi platform based on Google Maps, FrontlineSMS & email Redevelopment of Ushahidi platform for use anywhere Issues: language translation, cyberinfrastructure, local support, trust and security, information siloing Global access via free downloads Crowdmap – cloud-hosted service offering checkin (e.g., FourSquare) with a purpose and instant mapping

Enhancement II Swift River – crowdsourced (2011) information validation, translation

Event Used in Kenya during political unrest following presidential elections Used in: South Africa: anti-immigrant violence; Kenya, Congo, Uganda, Malawi, Zambia: epidemiology and pharmacy stockouts Used in: Gaza, Liberia: Political violence Used in: Haiti, Chile: Earthquake. Kyrgystan: Ethnic violence. Washington, DC: Snowstorm. Russia: Wildfires Used in: New Zealand, Japan: Earthquake; Tunisia, Egypt, Libya: Political unrest; Australia: Floods; US: Occupy movement

c­ollection, management, and analysis of crowdsourced information, Ushahidi empowers everyone – individuals, community groups, governments, activists, organizations – to create meaningful change (Marsden, 2013; Ushahidi, 2022).

10.13 Comments and Recommendations Following its initial development during the post-election violence during government imposed news blackouts in Kenya in 2007, Ushahidi has been used to support the rescue mission following the Port-au-Prince earthquake in Haiti in 2010, the 2011 Fukushima tsunami and resulting nuclear disaster, the BP oil spill in the Gulf of Mexico, public health disease tracking for epidemic aid and support in various African countries, emergency reporting and response for hurricanes and other storms including Superstorm Sandy. Very recently, Ushahidi has been used for tracking the spread of COVID19 in more than 130 countries, as well as many local communities. Ushahidi is currently available for deployment in approximately 40 languages and is working to expand (Marsden, 2013; Ushahidi, 2022).

References Banks, K., & Hersman, E. (2009). FrontlineSMS and Ushahidi – A demo. In International conference on information and communication technologies and development (ICTD). Fellett, M. (2011). Phone tech transforms African business and healthcare. The New Scientist, 2833, Retrieved November 02, 2011: http://www.newscientist.com/article/mg21128334.600-­ phone-­tech-­transforms-­african-­business-­and-­healthcare.html?full=true

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Freifeld, C., Chunara, R., Mekaru, S., Chan, E., Kass-Hout, T., Iacucci, A., & Brownstein, J. (2010). Participatory epidemiology: Use of mobile phones for community-based health reporting. PLOS Medicine Online, 7(12), e1000376. Goldstein, J., & Rotich, J. (2008). Digitally networked technology in Kenya’s 2007–2008 post-­ election crisis. Berkman Center at Harvard University Research Publication No. 2008-09 Internet & Democracy Case Study Series, September 2008 (pp. 1–10). Marsden, J. (2013). Stigmergic self-organization and the improvisation of Ushahidi. Cognitive Systems Research, 21, 52–64. Munro, R. (2010). Crowdsourced translation for emergency response in Haiti: The global collaboration of local knowledge. In Proceedings of the Workshop on Collaborative Translation: technology, crowdsourcing, and the translator perspective, Denver, Colorado, USA.  Association for Machine Translation in the Americas. https://aclanthology.org/2010.amta-­workshop.1.pdf Okolloh, O. (2009). Ushahidi, or ‘testimony’: Web 2.0 tools for crowdsourcing crisis information. Participatory Learning and Action, 59, 59–70. Ushahidi website: http://ushahidi.com/. Accessed June 2022.

Chapter 11

Trends, Conclusions and Recommendations for the Future of Participatory Mapping Software Peter A. Kwaku Kyem and Charla M. Burnett

Abstract  The goal of this edited volume is to provide practitioners and users of with a common framework for assessing and selecting participatory mapping software in hopes of making the process more streamlined and efficient. This chapter provides an overview of some of the criteria and important factors that may serve as useful guides to the selection of participatory mapping software. Today, easy access to digital data and mapping technology allows indigenous groups and communities in developing countries to engage in participatory mapping to re-map and defend their territories. Although technology is not a requirement, the computer mapping software plays a critical role in determining the success of participatory mapping projects. Given the critical roles computer software systems play in collective mapping projects that occur in traditional societies today, it is important that we focus on their adoption and examine the impacts that they create on the participatory processes, the communities and society at large. The chapter argues that developing mapping software systems without clearly considering costs, ethical concerns, analytical levels and visualization capabilities of end users, could lead to the development of software artifacts that fail to fulfill the needs of end users. Accordingly, software developers and users alike must explicitly identify and abide by ethical principles to guide them develop and use safe and useful technological products and services that best meets the needs of people in the target communities. Keywords  Participatory mapping software · GIS development · GeoScience · Participatory action research

P. A. Kwaku Kyem Department of Geography, Central Connecticut State University, New Britain, CT, USA e-mail: [email protected] C. M. Burnett (*) OrganizingTogether Consultancy Group, Lansing, MI, USA e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 C. M. Burnett (ed.), Evaluating Participatory Mapping Software, https://doi.org/10.1007/978-3-031-19594-5_11

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11.1 Today’s Participatory Mapping The drive to understand and describe the world using maps reaches back several centuries. Whether in the form of sketches in the sand, painting on cave walls, or drawings on paper, humans have evolved and refined methods for transmitting experience, knowledge and inspiration about places that sustain them physically and spiritually in maps. Unfortunately, early official and colonial maps that were introduced into underprivileged communities around the world, neglected local knowledge of the people and misrepresented their lands (Harley, 1989). Participatory mapping developed out of a process introduced by development agencies in the 1970s as they began shifting their focus from expert-led to community participation in development projects (Chambers, 1994). While initially dominated by top-down sponsorship rather than a bottom-up initiative, the focus of participatory mapping soon began to change to helping communities assert their knowledge, remap their ancestral lands and reclaim them. Recently, the availability, affordability and hence easy access to digital data and mapping technology previously available to only the military and state officials has led to an explosion in participatory mapping practices and critical deliberations among indigenous people and their allies (Sletto, 2012; Corbett, 2003). Alongside these developments is the increasing need of people in rural communities and previously colonized territories to jointly map and defend their territories through PM. The basic assumption of such collective mapping projects is that people in the communities know their landscape and are more aware and familiar with the interacting socio-economic and environmental processes and the nuances of social behavior and institutional structures of those areas. Thus, the people can therefore better represent these issues on maps and also identify the true mechanisms for resilience and coping (McCall et al., 2015). As digital cartographic tools continue to replace traditional mapping strategies, both the processes and outcomes of negotiations over the re-allocation of community lands and resources are changing. With smartphones, computers, the internet and digital mapping technologies, the tools for participatory mapping has expanded to include remote sensing methods for capturing land use data, online procedures for accessing text, audio and video, and three-dimensional viewing of mapped lands (Kyem & Saku, 2009). As a result, many of the PM software (described in earlier chapters) can motivate stakeholders, generate high participation levels, and provide high-responsive feedback from community groups. Given the universality of the internet and digital mapping technologies, the community may no longer be locally defined. PM applications can be programmed as part of an interactive system at a website to expand access to stakeholders who may not be physically present in the communities. Thus, PM methods today have the potential to help make the collective and shared understanding of land issues within the communities more practical and potent.

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The goal of this edited volume is to provide practitioners and users with a common framework for assessing and selecting participatory mapping software in hopes of making the process more streamlined and efficient. As a result, a number of practitioners, scholars, and software developers agreed to participate in the evaluation of participatory mapping software currently in use. The volume can also be used by educational institutions, governmental agencies, and nonprofit organizations internationally. Authors were encouraged to diversify their case studies to represent key cultural and economic differences in participatory mapping’s use, such as MapBox’s use case based on public consultations in the Jeżyce neighborhood in Poznań, Poland (pg. 36) or SeaSketch’s use case describing Eelgrass Protection on Fishers Island, New York. (pg. 140).  The vision for the edited volume comes from the editor’s own experience of trying to find PM software for multiple projects spanning geographies and several decision-scenarios. Regardless of the context, each of the PM projects required the collection of community held data with the goal of meeting the needs of the public. There are no one-size fits all applications. In each case, weeks were spent scouring the internet to identify participatory mapping software that matched the ethical, technological, and analytical requirements of each project. There are dozens of choices, some open source and free, and others with consistently vague and open-­ ended price tags. Deciphering the technical jargon and sales pitches were difficult for them as activists, sociologists, and novice cartographers. Through this experience, Dr. Burnett has helped them develop an evaluation framework that guides readers through the myriad of features, operating systems, and data collection methods and constraints. As a result of these efforts, this volume constitutes a one-of-a-kind study of participatory mapping software across eight important areas identified in the state of the art and academic literature. Although technology is not a prerequisite for participatory mapping, and in some cases can even harm the adoption and sustainability of policy outcomes, it does allow practitioners, research scientists, governmental and nongovernmental organizations to reach more citizens and collect more accurate data. Participatory mapping software provides many excellent tools for citizen science and participatory governance. With this book, it’s our hope that these aspects become more widely understood and taken into consideration when planning participatory processes and developing PM software, especially regarding the ethics, accessibility, and openness of projects.

11.1.1 Benefits of Participatory Mapping Before we dive further into the conclusions that can be drawn from these chapters, we first want to provide a realistic overview of the benefits and drawbacks of PM. On one hand, the convergence of multimedia, the internet, and digital mapping technologies and easy access to them raise the hope that participatory mapping may

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develop to offer alternative solution scenarios to enhance discussions and choice selection among community groups. Community maps provide a medium for community interaction, consciousness-raising, and collective action. The mapping allows for moments of self-reflection and the sharing of experiences, knowledge, and community action in a collective form and in a more practical and participatory manner than without it. Participatory maps can reinforce local awareness of land issues, while drawing in younger people as mappers and elders as sources of knowledge. By mixing mapmaking and map use in open, community-based mapping projects, the PM process places a limit on the imposing power of the cartographer (who may be a stranger) and creates a friendly atmosphere for communities to learn together, share values and promote their indigenous local knowledge. The mapping process provides opportunities to include diverse types of knowledge that are representative of a community. Accordingly, PM allows for improvements in information exchange between community members and outsiders (i.e., researchers, NGOs, government) in the design and implementation of development projects. The mapping processes can also be used to help secure access to land and natural resources, (to facilitate their management) and to support community advocacy on land-related issues. Community mapping offers concrete opportunities to underrepresented groups to enhance their capacities to advocate for, and secure their access to ancestral lands (Sletto, 2012). As the use of geospatial data and digital mapping technologies grow and become widespread, PM applications are becoming indispensable in the struggle of indigenous people worldwide to claim their rights to their ancestral lands and resources (Roth, 2009; Sletto, 2009). The collective mapping process promotes formation of groups from different social backgrounds and social-demographic patterns or different ages and genders. Therefore, the project contributes to building community cohesion while providing some leverage for collective action. In addition, PM provides an opportunity for participants to express their opinions more spontaneously through diverse exercises. It helps communities identify their needs and collectively work to achieve them. As well, the mapping process encourages respect for local knowledge while motivating the people to participate in the decision-making process. Ultimately, participatory mapping empowers local communities and their members (IFAD, 2010). By making maps, the communities come to understand and display their own conceptions of their lands and resources and repudiate other false representations proposed by non-natives such as colonialists and development scientists. The mapping gives them legitimacy and an enhanced effectiveness in negotiations with government and outside bodies. In composing maps that document their history, places of value, and local land use traditions, indigenous communities imprint their existence in visual forms and this helps them to actively resist their historical marginalization. The mapping can therefore strengthen and rework community identity while bringing visibility to projects that otherwise will appear spatially invisible.

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11.1.2 Drawbacks of Participatory Mapping On the other hand, digital mapping, especially online hosting of PM projects raises many concerns, including a limitation placed on individuals and groups in communities who are not well versed in the rapidly evolving PM software and computer-­ related spatial technologies. In particular, the uneven development of internet access structures in several communities in developing countries means that relatively little participation will occur among many of the stakeholders. There are also concerns about how genuine communication and significant interaction can be maintained among stakeholders and community groups in a web-based community mapping project. It is possible that with time the technology will alienate some of the very people in the community that PM was designed to serve and protect. Therefore, the integration of PM applications with the internet and digital mapping strategies raises prospects as well as concerns for access to technology among groups in the underprivileged communities of the world. Additionally, the involvement of ‘local people’ in the participatory mapping process does not, in and of itself, make it an apolitical process. This is because power relations between various actors can and do often intervene. It can allow the voices of those who speak the loudest to prevail over other voices. The mapping process can be subject to elite capture in which dominant members of a community dictate the terms and tenor of the mapping process. In this context, the views of marginalized groups such as women and the poor may not be taken into consideration during the participatory meetings and gatherings. Furthermore, technological improvements often have unexpected consequences. In particular, the introduction of technological solutions into cultures where the people have limited prior knowledge of technology and the risks related to its use can potentially exacerbate these issues. Moreover, because geospatial mapping technologies were not initially developed for use in rural and other communities of underprivileged people, the tensions associated with their applications and impacts in participatory mapping projects that occur in the communities could be most apparent and profound (Fox et al., 2005). Another negative side effect comes from using mapping techniques that create the village terrain as a defined territory with distinct and rigid boundaries in areas where resource boundaries have historically been flexible and negotiated (Turner, 1999; Roth, 2009). Generally, the spatial dimensions of social relations within the communities are complex and very complicated. The action space of individuals and community groups is not limited to territories with rigid boundaries (Gray, 2002; Li, 1996). For example, the economic and social activities of farmers, artisans and pastoral populations in the villages frequently reach beyond the boundaries of given territories (Li, 1996). Practically, community resources are characterized by both ecological diversity and socioeconomic differentiation (Leach et al., 1999) but the dynamic social systems are regularly mapped as static entities, leading to simplistic representations. Yet, the participatory mapping of community lands often ignores the fact that local resources are controlled by multiple and overlapping boundaries and authorities.

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Overlooking these differences in community mapping projects leads to increased competition and conflicts because the flexible social institutions that are based on negotiation are replaced with rigid, unfamiliar boundaries, and spatially defined rules of land use (Turner, 1999; Leach et al., 1999). This problem has led to what Roth (2009) has described as a “mapping dilemma” (i.e., to map or stay aloof and be mapped and defined by others and thereby lose control over one’s own native lands). Even though the mapping dilemma is a serious problem in PM, many practitioners appear to tolerate the negative consequences of mapping because they view mapping to be critical to the ability of communities to defend and secure tenure rights to their lands. Consequently, the impediments become inevitable outcomes of the mapping process. The benefits and drawbacks outlined above should be taken into consideration before beginning the search for a participatory mapping software. There are many other participatory solutions that do not require the same level of technical expertise, access to technology, and direct and indirect costs. Researchers should think critically about the objectives, topic, participants, timeline, and budget. Perhaps more traditional paper mapping techniques would work just as well as more sophisticated GIS techniques, or an alternative participatory method all together. Other participatory methods include the following: • • • • • • • • •

Semi-structured Dialogue Interviews Transect Walk and Diagramming Gender Analyses SWOT Analysis Resource or Value Matrices Flowcharts Timelines Historical Mapping

The key to participatory methods is that there is some sort of consensus built around the problem to be resolved and methods and tools that will be used to solve the problem. If participatory mapping is chosen as a method to solve a participator problem, such as ensuring that the historical and oral history of indigenous people are captured and memorialized, then the solution must come from the people most impacted by the process (see Sherry Arnstein’s Ladder of Citizen Participation, 1967).

11.2 Main Takeaways from Major Themes Covered in This Book In the section that follows, we offer a brief review of the main takeaways from the major themes used to assess the participatory mapping software described in this book. The table at the end of this chapter (Appendix A, pg. 259) is meant to provide

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readers with a quick guide to selecting software. It’s meant to inform and provide direction on which chapter to read and PM software to engage with. Further follow up with the software’s developers is always suggest,  but with this edited volume, it’s now a much clearer space to navigate for those interested in adopting participatory mapping into their methodological toolkit.

11.2.1 Ethics Ethics is described as the philosophy which outlines a systematic approach to understanding, analyzing, and distinguishing matters of right and wrong, good and bad, and admirable and deplorable as they relate to the well-being, of and the relationships among people in an organization (Vallor et al., 2015). It is believed to be deliberate acts of people that affect the lives of others, either positively or negatively (Gotterbarn, 2001). Ethics deals with many fundamental considerations that guide practical decision-making of individuals and groups in society. Therefore, ethics have a significant impact on decisions that people make regarding participatory mapping software artifact production and its applications. Today, computer software systems lie at the heart of decision making in several fields including data collection, information storage and processing, data availability and alternatives’ formulation and selection (Thomson & Schmoldt, 2001). This is particularly evident in participatory mapping projects where software programs are incorporated into traditional knowledge systems of community groups to generate desirable project outcomes. Given the ubiquity of computer software systems in collective mapping, it is important that the impacts that computer software systems create on the participatory process, the people and society at large are critically examined to allow for mistakes to be corrected. 11.2.1.1 Ethics for the Mapping Software Engineer Generally, two major ethical questions need to be addressed regarding software systems (Thomson & Schmoldt, 2001). First, there is the ethics about how the software system represents the different values, traditions and practices of groups that may be affected by software-mediated decisions made by software engineers. This aspect addresses how the data items in the software system moves through it; how the various data items are related to each other; and how each data item changes over time. The work of a software engineer has direct impacts on the well-being of clients (Johnson et al., 2017). As such adhering to ethical principles during the software engineering phase is important because it provides safe and useful technological products and services that best meets the needs of clients. During the software development process, software engineers make critical decisions that have positive and negative impacts on clients, society, and the environment. Quigley has described

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ethics in software engineering as “a code of professional standards, containing aspects of fairness and duty to the profession and the general public” (Quigley, 2007, p. 266). A mapping software may generate wealth in the short term for the developer but with time, it can cause substantial societal damage and many social problems due to lack of compliance with regulations, policies, rules, and ethical concerns (Lurie & Mark, 2016). Thus, developing software systems without clearly considering ethical concerns, may lead to the development of a software artifact that may fail to meet the needs of end users and fulfill societal value. Without ethical guidance, software systems may be put into operational use despite faulty trials and persistent errors, and without regards to the plight of end users. Accordingly, ethical concerns must be considered during the engineering processes where the ethical principles may lead to a better engagement with stakeholders who will be the end-­ users and clients of the software. 11.2.1.2 Ethics for Practitioners and Clients of the Mapping Software There are also ethical considerations that guide the design, deployment, and use of the computer software itself. This approach attempts to identify who is doing what for whom, to whom are they answerable, what assumptions are being made, and in what environment this is happening. The ethics attempt to identify the customers, actors, transformation processes, worldviews, owners, and environment where the software is used (Biable et al., 2022; Thomson & Schmoldt, 2001). Failures in technological adoption often result from the inability or unwillingness to understand the human and socio-cultural contexts of places where the software is being used. As a result, attention need to be paid to human perceptions of ‘good’ and ‘bad’ (ethics) regarding the following concepts: • Privacy – improper and unauthorized access to personal information can be an invasion of privacy. It is also important to ensure that exact points of the location of participants are protected on maps that results from community mapping and that public funding of projects do not lead to the release of research information in the public domain (Dix, 2007). • Accuracy  – has many associated ethical issues. For example, system inputs, internal processing, and system outputs can all affect accuracy, and are therefore accompanied by important ethical problems. A system analyst’s ability to know and predict errors is low for complex software systems, determining which specific information to use for a specific application is another area of ethical concern. The scale of operation is also a key determinant of indicator usefulness. Some indicators that are useful at the household or community level are difficult to measure at the regional level. If an indicator misrepresents a value set, then it cannot be considered accurate. When an indicator is based on subjective judgment, accuracy can be affected by an array of human biases that may require a software applications specialist to make ethical decisions.

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• Culture and Language – when a software user is compelled to engage with software using concepts unfamiliar to them as it is with participatory mapping projects, accuracy of the spatial information elicited from the people suffers. Language and terminology used to frame questions can significantly influence the accuracy of the information elicited. Ethical concerns also apply to the accuracy with which results are portrayed by software systems and interpreted by end users. Even when an image is presented in conjunction with an accompanying audio, as in video presentations, the audio content can modify the perception of the image, and this may raise ethical concerns. • Property – is another major area that requires ethical directives. Property includes (1) the knowledge possessed by individuals and organizations and used in the software development and use processes and (2) the communication medium that delivers the software to users. Participants in the software development and adoption processes contribute knowledge and skills, which can lead to problems of intellectual property rights. In a computer system, metadata may be used to acknowledge contributions of information and knowledge. • Quality of life – While the adoption of a digital mapping software can dramatically increase output while reducing errors and shortening the time spent, sometimes application software may actually degrade the quality of working life through (1) deskilling the workforce, (2) increasing stress, fatigue and boredom; and (3) cause health and safety concerns such as eyestrain and headaches. Although some issues can be addressed through ethical software development and use, many exogenous issues exist and are driven by rapidly changing legislative, legal, and policy proclamations. For example, more real threats today are likely to arise from unintentional and unforeseen information breaches and software applications than from any intentional conspiracy. Much responsibility still rests with participatory mapping organizations and experts to institute standards of ethical conduct that create an atmosphere of social morality for all the participants involved in the participatory mapping project. Thomson and Schmoldt (2001) contend that during the design phase, software developers need to be cognizant of users, co-­ developers, publics, cultures, special interest groups, commercial enterprises, governments, and other groups that might be affected directly or indirectly by the software. Designers must also consider the information their software uses or generates, and the decision-making landscape that it affects or creates. The contributing authors provide a deep and thorough overview of the ethics involved in choosing a participatory mapping software and the various processes that can be used alongside them. Digital Democracy and contributing researchers demonstrated the Mapeo Toolkit (Chap. 3, pg. 41) and the theoretical underpinnings of “solidarity technology” with a focus on centering self-determination and human rights, collaboration through equity and intentional inclusion, challenging oppression (social and environmental justice), and fearlessness and creativity. Mapeo’s platform has been particularly useful in counter mapping in environmental justice organizations whose lives are threatened by state and nonstate actors who profit

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from the exploitation of natural resources. Mapeo offers encrypted and protection features that hide the identities of environmental informants. Sapelli (Chap. 5, pg.  93) took considerable time discussing Free, Prior and Informed Consent (FPIC). The process recognizes the impacts that PM projects may have on participants, both positive and negative. The authors also focus on the need to follow local practices of consent and how various communities may have practices that are unfamiliar to outsides. SeaSketch (Chap. 6, pg. 121) embedded aspects of consent directly into its feature set. Users have access to private “sandboxes” where they may sketch freely before choosing to share the designs in public or private spaces. PM ethics should be embedded in both the software and the process taken by those who facilitate the use of the technology.

11.2.2 Costs To use a software, one must have access to the required hardware technology, be able to provide any required supporting input, and also comprehend the information presented. For example, in and online community mapping project, participants must have a reliable internet connection and a browser compatible with the material sent to it, including any applications or browser plug-ins for viewing and hearing content. All these inputs come at a cost that local communities in remote parts of developing countries may not afford. Apart from the cost of software and hardware, the participatory mapping project attracts other operational costs including (a) equipment for mapping and recording, (b) compensation (i.e., incentives or honorariums) or stipends for community members, (c) logistical costs for travel and workshops and (d) tools for printing, media editing and production. In addition, updating and maintaining the software and data sets create ongoing costs over the life cycle of the community mapping project. For example, software may be updated occasionally with different versions while the data containing different coverages, or data collected at different scales may be processed with each type of processing creating additional costs. Furthermore, the precision and accuracy of spatial data are heavily dependent on higher costs. It may be possible to achieve high precision and high accuracy in automated processing of the data, but only at high cost. Generally, when the cost of high precision and data accuracy becomes prohibitive, data intended to expand transparency, inclusion and facilitate participation becomes of limited value (Tauberer, 2014). For this and other reasons, when a software program is developed, its implementation must be part of an integrated process that includes plans for supporting infrastructure and alternative knowledge delivery methods that are appropriate to the affected individuals and communities. The increasing availability of high-quality, open-source software and free open data can reduce financial barriers to software adoption. However, communities that host many of the participatory mapping projects cannot even afford the hardware on which to run the mapping software. Depending on where one uses or hosts the open and free mapping software, there can be associated costs, (i.e., hardware, cloud

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storage, data service costs and a computer device that automatically generates a Wi-Fi hotspot for internet links). Given that several of the communities lack access to electricity, the Internet, and supportive infrastructure, the high cost and financial needs of the community mapping project often led to situations where the projects are controlled by entities from outside the communities. Often these are people and organizations whose agenda often run counter to the goals of true participation and the community mapping project. There are many free and open-source tools along with software that range in cost. Even when using free and open-source tools there are often hardware and storage costs. For open-source platforms that rely on base satellite maps, the maps can be preloaded when the devices have good and free internet connection. You can then manually remove memory cards from your phone to download the results when connection is poor as advised by the authors of the chapter on Sapelli (p. 93). The authors of Terristories recommend a low-cost cloud-based server like AWS S3 which costs $0.023 per gigabyte per month. They also recommend compressing files for web viewing, such as videos, as one method that might lower costs (p. 195). Going back to paper maps on the ground might also be one way to reduce the cost of needing mobile phones or satellite GPS hardware. PM software ranges from highly technical and more expensive, to free and near free solutions.

11.2.3 Technical Level and Analytical Capacity Technical skills refer to sets of abilities or knowledge that we use to perform practical tasks in science, the arts, technology, and engineering. It is the specialized knowledge and expertise needed to accomplish complex actions, tasks, and processes relating to such computational and physical activities as mapping. The level of one’s technical skills determines his or her technical proficiency and the kind of analyses that the person can comfortably understand and use. Low level technical skills may only allow for the understanding of basic mapping software operations while a high-level technical skill can facilitate good analysis, interpretation and understanding of the computer software operations in use. On the other hand, Wikipedia (https://en.wikipedia.org/wiki/Analytical_skill) defines analytical skill as the ability to deconstruct information into smaller categories to draw conclusions. Analytical skill consists of knowledge categories that include logical reasoning, critical thinking, communication, research, data analysis and creativity. In participatory mapping, we use analytical skills when we collect data and analyze information to solve spatial problems and when we detect patterns and relationships among spatial objects contained in spatial data and brainstorm over problems in search of solutions. Others include when we observe, analyze, and interpret spatial data and when we integrate multiple sources of information to make decisions. To a large extent, accessibility to a computer software system depends upon the analytical skills level and technical capabilities of people who are assigned to use

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the system. Accessibility is limited if the software is complex or if it uses unfamiliar language and concepts that are beyond the understanding of end users. With a mapping software developed for multiple users, it may be more appropriate to develop separate programs and procedures that are geared to the requirements of each target group rather than try to develop a single, generic system for all users. Also, limitations of technical accessibility by some groups may require developing approaches and processes that ensure access by all stakeholders. Like the cost requirements, there’s a wide variety of PM software that can range from highly technical to the use of a mobile phone or draw points and lines on a piece of paper. Regardless, the use of technology comes with a learning curve and there are certainly differences in the ease of use. Mapbox is a powerful and sophisticated tool that does require some technical knowledge of APIs, basic code or in plug-ins. This could be a barrier to use but it doesn’t negate the power of the tool for those with the knowledge. Software such as Ushahidi (p. 219) and SeaSketch 2.0 (p. 121) offer open source development possibilities by offering the code to developers. These software as a service application also offer fully operational platforms that only need basic skills in point click. Most applications also offer guidebooks and video tutorials that allow new users to learn how to use important tools. The use of PM software is greatly hindered by the technological literacy gap between the global north and south. Most PM software acts as data collection tools, not analytical processing platforms. This means that after the PM software is used to collect the data, it must be exported to a 3rd party platform to be analyzed. This is not always clear based on an initial review of the website or literature. Analytics such as outlier estimates (Moran’s I) and regression can be found in open-source platforms such as QGIS and GeoDa. Ushahidi (p.  219), Maptionnaire (p.  71), and Survey 123 (p.  167) offer some analytics directly in the platform but are still limited to other fee based and open source geospatial analysis tools. 11.2.3.1 Reducing Barriers by Incorporating End Users’ Experience A software can be incredibly powerful, but that does not matter unless end users can easily adopt the new program and leverage it to their full potentials. To improve the quality of the software, tools and procedures of the program must be defined within specific application domains and with the social and cultural contexts of the software applications in mind. Oftentimes computer programmers and developers decide to build software that they think their clients want or they may develop programs they know end-users want. The latter approach is better because it incorporates the users experience into the software development process. When the experiences of end users and the context of the applications are ignored, products may be used incorrectly, can be misunderstood, or even completely ignored. Quality can be significantly improved through the exploitation of massive user feedback. Field practitioners and end-users can provide feedback through reviews, ratings and comments in online forums, application stores and at social network sites. This calls

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for methods and tools for gathering end-user feedback that may enable automated analysis of feedback and contextual data to support requirements analysts, system architects, developers and project managers in decision-making tasks. Doing so can yield better outcomes on multiple levels. The end-product (software) will align with the needs and preferences of end-users to make it easy to use the software in ways that users truly love. The practice ensures that the software will be relevant to users for it can be used to resolve their unique problems.

11.2.4 Openness & Inclusiveness The discourse on public participation (whether in mapping or in the design and execution of community projects) has primarily focused on the implementation of participation. The nature of the participatory process (whether closed, restrictive, or open) has received much less attention in the literature (Huybrechts et  al., 2013; Pohjola & Tuomisto, 2011). By focusing solely on participation, one is easily misled to consider the process as independent entity with purpose, goals, and values, without relating it to the factors that make effective participation possible (Jacobsen & Fast, 2019). However, we know that participation can be effective or ineffective based on whether the process is restrictive or open. Openness refers to making the functionality of a product accessible. Openness and transparency are key ingredients to building accountability and trust, that are necessary for effective participation. Participation is generally viewed as desirable, and its benefits is often assumed to be obvious, but openness is the element that guides the vision for a stronger, fairer and effective participation. Involving end-users as full participants in the design process enables designers, artists, and users to learn from each other’s knowledge, comment on, and improve the project. Also both processes permit the appropriation or reproduction of knowledge and practices for other goals (Bauwens, 2007). This may lead to better quality, reliability, flexibility and lower costs. The open and flexible form of interaction and work may also open up new creative categories of things. In a Community mapping project, dimensions of openness may include (a) the scope of participation – referring to who are allowed to participate in the process, (b) access to information, referring to what information regarding the issue at hand is made available to participants, (c) timing of openness, referring to when participants are invited or allowed to participate (d) the scope of contribution, referring to which aspects of the issue at hand participants are invited or allowed to contribute to and (e) the impact of contribution, relating to what extent are participant contributions allowed to influence the outcome of the process, (i.e. how much weight is given to participant contributions (Pohjola & Tuomisto, 2011). Openness does not undermine the existing software and its operations, nor the participatory models adopted, but it provides conceptual means for their effective deployment. It also opens avenues for developing new kinds of software applications and effective participatory practices that facilitate collaborative creation of

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knowledge. The degree of openness in a participatory mapping project may be influenced by several variables including the situational, contextual, and practical issues (USAID, 2019) such as software program operations, legal requirements, public perceptions, available resources, time constraints and complexity of the software procedures. For each of these variables, openness can be adjusted separately for different groups, or even on an individual basis. Openness also brings about significant challenges to the community mapping project including the manageability of a broad participation, information quality control and promotion of vested interests. Openness is closely related to inclusiveness when we talk about participation in community projects. The more we open the collaborative mapping process by ridding it of practical and other hindrances to open it up, the more inclusive it becomes. Digital approaches, especially those based on the internet and mobile devices are fast replacing in-person activities with contactless, digital data collection, analysis and decision making. While mobile phone and internet access have increased significantly over the past few years, mobile data and fixed broadband are still only available to very few people in indigenous and underprivileged communities of the world. This disparity has led to greater inclusion of some groups in the digital mapping revolution. Yet, those who do not access or use mobiles for reasons such as lack of a device, inability to pay for airtime, poor network connectivity, lack of electricity, cultural, gender and age barriers to mobile access, illiteracy, language and others, are left out of mobile-based initiatives (Raftree, 2021; Bamberger et al., 2016). The digital divide excludes some voices and prioritizes those with greater access and power (Raftree, 2021). In effect, the participatory mapping software may capture the voices and opinions of the more elite segments of people in the community. Those living in remote and rural locations are often unreachable and even when one strives to hear directly from these affected individuals and communities through digital means, lack of access often means that they cannot be reached (Bamberger et al., 2016). Others such as children, women and people living with a disability are also less likely to access and use mobile devices. In addition, issues such as COVID-19 further interfere with mobile technology and internet access and use. During the recent lockdowns, people who did not have a home-based network connection lost access to digital sources of information and applications. Power cuts and shutdowns can also interfere with airtime purchases and phone recharging. These exclusions lead to skewed participation where important voices may be missing, potentially making project findings less reliable. Therefore, it is important to understand the context and patterns of device use when planning a digital mapping involving habitually excluded groups. As well, one must consciously and actively design community mapping projects and monitor them for inclusion. Software applications should be made simple and easy for the people to use as they will tend to give up before completion if a mapping project is complicated, long, too detailed, and boring (ALNAP, 2021). Rather than relying solely on digital mapping approaches to complete the mapping, it is a good practice to mix digital with hands-on data collection and mapping methods to induce and sustain the interests of participants.

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Despite the debates around free software (FS) and open-source software (OSS) are very common in PM, both closed platforms, such as Maptionnaire, and completely open, such as Terrastories, exist and can support the diverse contextual needs of their users.

11.2.5 Data Accuracy and Security In mapping, precision or accuracy of spatial data refers to the level of spatial resolution, or the reliability of the geo-referencing data. Accuracy is defined as the likelihood that the spatial data reflect the truth on the ground (Tauberer, 2012). Maps deal with two kinds of accuracy (a) representational accuracy (asks about which object?); and positional accuracy (which location?). Positional accuracy describes how well we measure the location of features on a map, and it depends on how reliable the data source is, the measurement device used, and how the data has been presented or changed (McCall, 2006). It is difficult to assess positional accuracy because it can only be checked against another ‘better’ source. On the other hand, attribute or representational accuracy measures the characteristics of features and as such it is affected by people’s understanding, interpretation, and classification of features shown on a map. Therefore, different people have different interpretations for the precision and accuracy of attribute data. Data quality is a measure of the condition of spatial data based on such factors as (a) accuracy, (b) completeness, (c) consistency, (d) reliability and (e) whether the data is up to date (Vaughan, 2019; Tauberer, 2012). Measuring data quality levels can help organizations identify data errors that need to be resolved to determine whether the data in the software for the application is fit to serve its intended purpose. Bad data can have significant consequences for mapping and poor-quality data is often pegged as the source of operational glitches, inaccurate analysis and impractical results. McCall (2006) has also argued that precision and accuracy in spatial data cannot always be considered a necessity in community mapping projects because spatial reality is itself not precise but fuzzy and frequently ambiguous. As such it can be misleading to present it as being precise and accurate. The author argues that data precision is counter-productive when it is false precision and misrepresents what is fuzzy and an ambiguous reality. Thus maps that result from participatory mapping projects are often created on the basis of the assumption that spatial data should be available and usable to the community. Community maps solidify a sense of space and place that is much more dynamic and often emotional and spiritual within the cultural contexts of indigenous and local people’s daily lives (McCall, 2006). As such, the mapping process is more vital than the final map output in the community mapping process (Rundstrom, 1991). Therefore, the defining characteristics of participatory mapping products are not so much about data quality or precision of the map but rather, the degree of engagement of participants within and beyond the mapping process (Sletto, 2014). The precision and accuracy of maps produced under participatory mapping approaches are often balanced against the

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context and the challenge to effective comprehension and interpretations of the maps (McCall, 2006). Collecting spatial data remotely skews the process towards certain individuals and groups within the community. Teams conducting digital surveys will only be able to contact households that have access to a phone and can keep it charged, meaning that any data collected will be biased towards those with more resources. When access to affected populations is reduced and digital tools are the only means of data collection, representative sampling is difficult. Also, in remote and difficult­to reach contexts (i.e., indigenous, and local communities), quantitative data provided by digital tools do not fully capture complex inequalities and power dynamics within the community. It is also likely that the voices of the most vulnerable will not be captured so their perspectives may have to be accounted for in the data collection and analysis. When organizations only measure what they can see and count, and they do so through a screen, they are likely to miss out on highly critical data that they would normally capture by being present (ALNAP, 2021). When practitioners in a community mapping project cannot interact directly with people in the communities, they lose context. Social media observations and community radio can help practitioners gain some context information, but elite capture is a challenge with these channels. This can skew understanding towards those who have power and more access to digital communications. These challenges mean that remote data collection suffers in quality and may present an alternative reality that can lead to biased, unreliable data and poor decisions. In addition, digital data collection and the community mapping process often leaves participants open to data privacy risks as well as government and corporate surveillance. Digital data transmission increases risk because third parties including foreign and national entities, non-state actors and private companies can intercept the transmitted data (USAID, 2019). For example, governments could use mobile phone location to track down populations in specific geographies. Public social media pages and messaging apps are not private, and individuals often do not know how to manage their privacy settings. This exposes them to corporate and state surveillance of online and phone communication. In addition, PM experts must be cognizant of other sources of errors in spatial data that result from human biases, exclusion and other technical and contextual factors. For example, when people are scared, such as during the COVID-19 crisis, they may be willing to hand over their personal and sensitive data more easily. To mitigate these problems, experts of community mapping projects may have to minimize the amount and sensitivity of personal data they collect from the people. If possible, the experts may avoid collecting sensitive personal data based on religious or ethnic affiliation, political opinions, religious beliefs, sensitive health information, and data on topics that could create social stigma. The PM expert must therefore ensure that the data is protected from misuse. They must obtain the active and informed consent of the people prior to collecting their personal data. Also they need to put in place clear, transparent and ethical processes to protect the data. Other good practice examples include ensuring that transparency is maintained about data usage. It is important to ensure that respondents are aware of their unconditional

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right to withdraw from the project and of the potential risks in taking part in it. If potential harms cannot be reduced to an acceptable level, it would be better to not proceed (USAID, 2019). To further protect the data, it would be important to establish data-sharing and data-processing agreements to ensure that all participants will be held responsible and liable for any data breach and unauthorized sharing of the data. Another good practice for ensuring good data quality is providing summaries of data back to communities and creating genuine opportunities for them to influence the findings and conclusions of the project. Routine data quality audits can also be instituted where a percentage of data collected is validated through call-backs and comparisons with original documents (ALNAP, 2021). Also, the risks brought about by making a group more visible through the collection of their personal data must be assessed against the risks of their exclusion. Despite the broadly held idea that digital tools are cheaper, quicker, improve data quality and easy to scale, high-­ quality digital data takes more time, and are more expensive. Accordingly, we should not expect these methods to fully replace in-person activities.

11.2.6 Visualization Capacity Participants in a participatory mapping project increasingly require insight from massive data sets to make decisions. As such, there is a growing need for tools to create visual graph analytics that help users understand relationships in spatial data (Jonker et al., 2017). Software algorithms can extract relational patterns from spatial data sets but they lag behind the human ability to perceive visual patterns and anomalies and also detect common relationships among data sets (Herranz et al., 2014). As such, the technical and non-technical users of participatory mapping software benefit from interactive visual graph analytics that facilitate the discovery of nuances or patterns in data not typically identified by computational algorithms. On a map, visualization allows local community mappers to reflect on, and connect the links and relationships among objects in the data to integrate them with the mental images they have formed in their minds. Knowledge in visualization assists the software users to apply their natural visual acuity to identify clusters and communities of related nodes and links in the spatial data, to understand how closely connected nodes reveal relationships and associations (Rohrer et  al., 2014). This facilitates interpretation of the map.

11.3 Next Steps in the Field of Participatory Mapping Software Development Within the indigenous and underprivileged communities, most of the people are illiterate, and they have little or no familiarity with the use of technology. In addition to this, the software must deal with an open world in which the issues it exploits

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as well as other companion software, devices and data it interacts with, change regularly for many reasons. These problems and the lack of basic infrastructure for technology adoption in the communities mean that the cost of misapplications of the software can be significantly magnified. The success of a PM project is heavily linked to the ability of the software to be both dependable and adaptable to real time changes. As such it is good practice for program codes to be written with the following goals in mind: • Maintainability – adaptable and able to cope with changing needs of the communities. • Dependability  – the software programs must meet their specifications (i.e., ­“correct output for each possible input”) and be able to do what they are intended to do. • Efficiency  – Is the program efficient and appropriate for the environment in which it is used? Beside simplicity of use, the software must be rugged and hence difficult to misuse by end users. It must be kind to errors and mistakes encountered in its deployment within the communities. In today’s volatile world and evolving demands of people, selecting a valuable mapping software that truly meets the needs of community groups can be a daunting task. Quality of the software is not the only factor contributing to the success of the PM project, but it can play a major role in the effort to achieve the goals of the project. Accordingly, there is the expectation that the software must offer consistent or seamless experience across all platforms and devices (i.e., laptops, smart phones etc.,). There is also the need to maintain consistency in tone, analysis, display, and messaging, across all application platforms as well as provide on-demand support wherever customers decide to use the software. In the section the following, we explain some of the reasons for failures in the adoption of software for participatory mapping projects. Training community groups in visualization requires the development of representations that enable collaborative reflection on the data, adopting approaches that promote mutual visibility of participants and promoting a shared view of problems and issues confronting the community. Similarly, it is necessary to create visualization methods that facilitate sense making from large pieces of heterogeneous information of different sources and with different levels of credibility. The unique spatial representation of complex spatial data facilitated by computational processes enables users to retain mental models of data organization and detect anomalies and patterns for further investigation. Sharing the past history of the community is a fundamental source of visualization for community members. It is important to provide a comprehensive and understandable view of the ­community that allows members to navigate its past history and collectively reflect upon shared ideas, shared values and resources to prepare them for ­collective action.

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11.3.1 Defining a Clear Scope Unclear or constantly changing requirements are some of the primary reasons many PM projects fail. It is important to admit that in some cases, the uncertainty lies in the software development process. Sometimes the developer may not be sure about what the final product will be like. At other times, end users may not be conversant with the full and potential capabilities of the software. A good solution here is for the software to have a clearly defined scope, but this is rarely possible during fast-­ evolving needs and demands of people within under-privileged communities.

11.3.2 Poor Decision-Making Environments A potential drawback exists when providing access to sophisticated software used in participatory mapping. Such technology may considerably increase the power of users to make or influence decisions that were formerly beyond the limits of their knowledge and experience. Decision tools should not be used blindly. In this regard, software developers must fully consider the interactions of all people using and/or affected by a system and ensure appropriate training to avoid misuse. A very powerful mapping software package allows users to perform all manner of inappropriate analysis on spatial data without full knowledge of what they are doing, and this must be avoided.

11.3.3 Resistance to Change In underprivileged communities around the world, combating resistance to change is one of the main challenges that agents of technological change face. One of the biggest barriers to success happens when people are being persuaded to migrate from old ways of doing things to new ones. Amongst the people, there may always be the willingness to change, but there is also the challenge of developing an understanding of how things will work in the future. The manual and customary ways of doing things in the c communities are inherently error-prone and very slow. For example, in a community project, when a participant forgets to pass on a vital information to the group or skips an important step, the one tiny mistake can turn into a big problem. By adopting automation, the group can hold off some of the mistakes and spend more time discussing issues that speak directly to their needs and expectations so they can accomplish their expectations. However, it is often hard for people whose lives evolve around customs and traditions to let go of old practices that have been tested and found to be reliable even when imperfect. In theory, the people will want to change and may therefore enroll in the community mapping projects, but in practice, resistance may come in many ways. It is always a challenge to get

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people in the communities to adapt to new ways of doing things and stick with them. Under these conditions, it is essential that participants in PM projects understand why they are making the change so they can take ownership over their roles in helping the community achieve its goals.

11.3.4 Absence of Technical Documentation Lack of technical documentation about the mapping software capabilities and limitations can cause problems in applications that may lead to project failures. The documentation provides a guiding vision and a clear understanding of how the software integrates into the overall mapping experience and how it can and should be used. As well, the information reveals the kind of resources that are required to make the applications happen. Without detailed information and explanation that can serve as a road map to guide various applications of the software, end users may not be able to put the full potentials of the software to use. The lack of clarity about how the software can be used can make it difficult for applications to move forward. This could cause clients to develop unrealistic expectations that could cause the people to reject the software. It is also important that the software is accompanied by a document which explains the current state of the program; outlining problems and opportunities the software will address and future considerations including, • • • • • • • • •

New program considerations since initial project Problems that will not be solved with the software (outstanding issues) The training is required for users of the system Integration points with other mapping software Data storage requirements Data retention requirements Cross-functional support/input required to use the software Legislative/contractual/security/access requirements Confidential data, access rights and compliance requirements for the software

11.3.5 Iterative Procedures A feature that needs to be incorporated in future PM software programs to facilitate decision making is iteration. Generally practical decision making is not a linear process. The decision process is fraught with forward and backward movements that entail re-evaluations and new considerations. To offer the right tools and methods to guide users in all decision activities, software programs and procedures need to be iterative. Iteration breaks the project requirements into incremental changes or phases, with each increment providing more functionality to the customers. At the end of each iteration, a working product is released to stakeholders. For example, after the first increment, a core product is delivered, and users are then allowed to

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assess it and consider other alternatives before proceeding to the next phase of the decision process. Based on customer feedback, plans are then developed for the next increments, and modifications are made until the final decision is made. This approach minimizes overall risks and errors in the decision-making process and allows the project to adapt to changes quickly.

11.4 Conclusion With the advent of digital mapping, the tools for participatory mapping projects expand to include online procedures for mapping, accessing text, audio, video, and three-dimensional viewing. As technology replaces traditional mapping strategies, both the processes and outcomes of participatory mapping changes. The integration of digital technology into mapping has transformed community mapping and introduced the computer software as an important determinant of the successes or failures of the community mapping process. The ubiquity of computer software systems in many aspects of our public and private lives today mean that impacts that they create on the participatory processes and on the communities must be examined for corrections to be applied. As well, the atmosphere they create in society as the software are developed and deployed for use must be critically studied. This is particularly true with computer mapping software that are built for use in participatory mapping projects that take place in indigenous and local communities in the world. In many cases, developers of such software live outside the communities and are therefore unfamiliar with the culture and social contexts within which the software get used. Also, many people in the communities are unfamiliar with technology and even when they learn to use them, they can hardly afford to purchase and own the mapping devices. While some of these challenges to participatory mapping are being tackled today at various levels, new challenges continue to emerge as technology progresses and new concepts arise, while existing challenges take new turns and demands for mapping from the communities grow. Further research and innovation are necessary to be proactive in the efforts to resolve problems efficiently and effectively. Accordingly, computer software developers and users alike must explicitly identify and abide by ethical principles to guide them develop and use safe and useful technological products and services that best meets the needs of people in the target communities. Given the evolving landscape of participatory mapping, computer mapping software and its application, further evolution in PM software development must be heavily linked to the ability of the software to be both dependable and adaptable to real time changes within the different application contexts. It is also imperative that attention is focused on developing appropriate and efficient computer software systems for use in community mapping. Eventually, the future of participatory mapping will be determined by the choices that humanity makes today regarding what to do with geospatial mapping technology (Kyem, 2021). In the future, the deployment of participatory mapping strategies will depend on the applications that

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software engineers design for community mapping, the issues that the communities choose to address in participatory mapping projects, the effort, and investments (of time, money etc.,) that society puts into participatory mapping and the institutional arrangements society makes for the practice.

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Appendix A: Participatory Mapping Comparison Chart

© The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 C. M. Burnett (ed.), Evaluating Participatory Mapping Software, https://doi.org/10.1007/978-3-031-19594-5

259

Maptionnaire $950-50K (Chap. 4, per year pg. 71)

Free

Mapeo (Chap. 3, pg. 41)

Mapita Oy

Digital Democracy (Dd)

Cost (USD) Developer Free/Pay as Mapbox you go services

Application Mapbox (Chap. 2, pg. 21)

Public and Private

Public and Private

Funder Mapbox

Language HTML, CSS, JavaScript, AppleScript, C++, Java, Kotlin, Objective-C, and Swift

Mapeo JavaScript Desktop: Linex, Windows, Mac Mapeo Mobile: Android, iOS (2022) SaaS JavaScript

System Web Application

Private

Desktop and Mobile

API Desktop and Mobile

Web mapping, surveying, 3D collaboration, participatory budgeting, analysis tools, granulated permissions for viewing and editing

Offline first, Peer-to-peer synchronization and data storage, create reports, data export

Features Web mapping, hosting, data provider

AA-Level Web Content Accessibility Guidelines, language translation

Offline, self-hosting, audio and visually impaired (2023), language customization

Accessibility Color blind-friendly palettes, Access to Wi-Fi required, language restrictions

Exploratory: choropleth maps, proportional and graduated symbol maps, do density maps, and heatmaps, Explanatory: hotspot mapping

Analytics Exploratory: choropleth maps, proportional and graduated symbol maps, do density maps, and heatmaps N/A

260 Appendix A: Participatory Mapping Comparison Chart

SeaSketch (Chap. 6, pg. 121)

Free

ODK Collect (Chap. 5, pg. ) Sapelli Free (Chap. 5, pg. 93)

Matthias Stevens, Michalis Vitos, Julia Altenbuchner, Oliver Roick, Julius Osokinas, Joe Woodhouse and Contributions from the Open-Source Community McClintock Lab

Android, Microsoft Windows

Waitt Family Web Foundation, Application Esri, and others.

UK’s Engineering and Physical Sciences Research Council, European Research Council, European Union

JavaScript, Python

Desktop

Android, GeoKey HTML, CSS, REST API JavaScript, React.JS, Stencil.JS, Capacitor, Python

Web mapping, sketching, geospatial analysis, forum, surveying, granulated permissions for viewing and editing

Icon-based data collection, map visualization, decision tree filtering

N/A

Language External self-­ customization, self-hosting

Offline, self-hosting

Appendix A: Participatory Mapping Comparison Chart 261

Free

Free for nonprofits, revenue based pricing scale

Ushahidi (Chap. 10, pg. 219)

Ushahidi

Terrastories (Open-source team)

Public and Private

N/A

GIScience Public and Heidelberg Private (Heidelberg University), Heidelberg Institute for Geoinformation Technology $500–$3800 Esri Esri per year

Free

Terrastories (Chap. 9, pg. 189)

Survey 123 for ArcGIS Online (Chap. 8, pg. 167)

Sketch Map Tool (Chap. 7, pg. 149)

Python

Front-end: JavaScript, (HTML, CSS); Back-end: Python

JavaScript API for the survey, ArcGIS API for Python N/A

N/A

Ruby on Rails, JavaScript, React, Mapbox GL JS, Docker Web SiLCC, Open N/A Application, Source Open Source HTML, GNU/Linux, Frontline Google SMS Maps, Google Earth

Desktop and Mobile Responsive

Web Application

Web Application, Software

Interactive map, sidebar stories, granulated permissions for viewing and editing Web mapping, map visualization, surveying, sketching

Web mapping, map visualization, surveying

Web mapping, map visualization, sketching

Self-hosting, language self-­ customization, open-source community support

Offline, Self-hosting, Language self-­ customization

Mobile friendly (iOS and Android)

Offline, self-hosting, English and Portuguese

Exploratory, Explanatory, and Predictive (predictive analysis, modeling) N/A

N/A

262 Appendix A: Participatory Mapping Comparison Chart

Index

A Afghanistan, 228 Africa, xv, 97 Amazon Conservation Team, 10, 190, 197 Amazon Web Services (AWS), xxiii, 125, 135, 136, 139, 198 Android, 10, 30, 36, 94, 100, 175 ArcGIS, 5–8, 24, 28, 125, 128, 167–187, 203 ArcGIS Online StoryMaps, 172 Artificial intelligence (AI), 5 Australia, 108 Azores, 129, 130, 134 B Bermuda, 122, 133, 137 BSD license, 123, 125, 138, 139 C California, xxiv, 122 Cambodia, 228 Cameroon, 108, 115, 116 Canada, xxiv, 122, 195, 211 Carto, 14 Cascading style sheets (CSS), xxiii, 22, 29, 94, 150 Centro de Bachillerato Tecnológico Agropecuario, xxiii Choropleth, 32–34 Color-blind, 64 Congo, 108

COVID-19, 77, 86, 145, 216, 248, 250 Crisis mapping, 221 D Denver, 85 Digital democracy, 9, 209, 243 Dja biosphere reserve, 115 Docker, 190, 198 Dot density maps, 32 Drones, 63, 67 E Edinburgh, xxii Egypt, 232 Emberá, 64, 66–67 Emergency response, 220 English, 95, 96, 139, 155, 198 EthicalGEO, 74 European Union General Data Protection Regulation, 80 Excel, 82, 145 Extreme Citizen Science (ECS), xxiii, 7, 102 F Federated States of Micronesia, 122 Finland, 72, 77, 84, 86, 88 Finnish Funding Agency for Technology and Innovation, xxiv, 72 Firelight group, 213 Fishers Island, xxiii, 16, 140–142, 237

© The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 C. M. Burnett (ed.), Evaluating Participatory Mapping Software, https://doi.org/10.1007/978-3-031-19594-5

263

264

Index

French, 139 Frontline SMS, 220, 221, 228–230

K Kenya, 108, 116

G Gaza, 232 German Red Cross (GRC), xxiii, 153, 155, 161 GitHub, 9, 35, 100, 133, 136, 155, 161, 164 Global navigation satellite system (GNSS), 100 Google Earth, 213 Google Forms, 174 Google Maps, 138 Graduated symbol maps, 32

L Leaflet, 30, 39 Liberia, 232 Libya, 232 Linux, 206

H Haiti, 221, 229–232 Haitian Kreyol, 229 Haudenosaunee, xxiii, 192, 200, 208–210, 213 Heatmaps, 32–34, 131, 136 Heidelberg Institute for Geoinformation Technology (HeiGIT), 150, 156, 157 Helsinki, 72, 77, 79, 86 Henry L. Ferguson Museum, 140 Humanity United, 220, 221 I Indigenous, xxiv, 6, 15, 98, 99, 108, 190–192, 194, 196–212, 214, 215 Indonesia, 122, 126 Indonesian, 139 International Society for Participatory Mapping (ISPM), xi, xv, xxiv, 6 International Telecommunication Union (ITU), xxiv, 100, 112 Inuit, 195, 211 iOS, 10, 30, 36, 175 Iraq, 228 J Japan, 176 Japanese, 198 JavaScript, 22, 29, 30, 35–37, 39, 72, 94, 122, 128, 139, 150, 168, 190 Jyväskylä, 78

M Mac, 206 Madagascar, 161 Malawi, 228, 232 Maldives, 122, 140 Mapbox, 7, 10, 16, 21–40, 112, 190, 196, 198, 203, 214, 246 Mapeo, xxiv, 25, 42–69, 203, 208, 213, 214, 243 Mapita Oy, 72, 83 Maptionnaire, 6, 13, 72–88, 246, 248 Maputo, 161–164 Matawai, 190, 197, 199 Maximum Accuracy Radius, 106 Metis Peoples, 195, 211 Microsoft Windows, 94, 205 Microsoft Word, 172 N Namibia, 108, 116 New York, 16, 140, 237 New Zealand, 108, 122 North America, 108 Norway, 122 Norwegian, 139 O Ohneganos, 16, 192–193, 199, 200, 202, 206, 208–214, 216 OpenStreetMap (OSM), xxiv, 5, 7, 9, 30, 31, 35, 150, 158, 214 P Pakistan, 228 Panama, 64, 66–67 Participatory Action Research (PAR), xxiv, 2 Philippines, 228

Index Poland, 16, 36, 37, 78, 237 Portugal, 122 Portuguese, 139, 155, 198 Princeton University, 37 Python, 12, 94, 122, 136, 150, 168, 172, 173, 180 Q QGIS, xxiv, 5, 12, 14, 24, 111, 114, 153, 154, 159, 160, 162, 179, 203, 214, 246 R Reunion Island, 122 Ruby on Rails, 190 S Samoa, 122 Sapelli, 93–117, 244, 245 Seagrass Management Areas (SMAs), xxiv, 140, 142 SeaSketch, 13, 121–145, 237, 246 Six Nations, 192, 199, 200, 208–213 Sketch Map Tool, 150–165 Southeast Asia, 53 Spanish, 139, 198 Standing Rock Sioux, 63 Suriname, 190, 197, 199 Survey123, 6, 39, 167–187

265 Swift, 22 SwiftRiver, 223, 225 T Tableau, 24 Terrastories, 6, 25, 189–216, 248 3D, 15, 31–34, 37, 72, 73, 88 Tragame Tierra group, 49 Tunisia, 232 U United Nations, 2 United Nations Economic Commission for Europe, 2 Universidad Campesina del Sur, 49, 64 Ushahidi, 5, 6, 220–232, 246 W Waitt Foundation, 123 Waorani Mapping Project, 46, 49 Washington, DC, 232 Websync, 55, 56, 63 WordPress, 24 Z Zambia, 232 Zimbabwe, 228 Zoological Society of London, 116