Paper by Donia Nciri et al: “Traditionally, government and national mapping agencies have been a primary provider of authoritative geospatial information. Today, with the exponential proliferation of Information and Communication Technologies or ICTs (such as GPS, mobile mapping and geo-localized web applications, social media), any user becomes able to produce geospatial information. This participatory production of geographical data gives birth to the concept of Volunteered Geographic Information (VGI). This phenomenon has greatly contributed to the production of huge amounts of heterogeneous data (structured data, textual documents, images, videos, etc.). It has emerged as a potential source of geographic information in many application areas. Despite the various advantages associated with it, this information lacks often quality assurance, since it is provided by diverse user profiles. To address this issue, numerous research studies have been proposed to assess VGI quality in order to help extract relevant content. This work attempts to provide an overall review of VGI quality assessment methods over the last decade. It also investigates varied quality assessment attributes adopted in recent works. Moreover, it presents a classification that forms a basis for future research. Finally, it discusses in detail the relevance and the main limitations of existing approaches and outlines some guidelines for future developments…(More)”.
Citizen scientists will be needed to meet global water quality goals
University College London: “Sustainable development goals for water quality will not be met without the involvement of citizen scientists, argues an international team led by a UCL researcher, in a new policy brief.
The policy brief and attached technical brief are published by Earthwatch Europe on behalf of the United Nations Environment Program (UNEP)-coordinated World Water Quality Alliance that has supported citizen science projects in Kenya, Tanzania and Sierra Leone. The reports detail how policymakers can learn from examples where citizen scientists (non-professionals engaged in the scientific process, such as by collecting data) are already making valuable contributions.
The report authors focus on how to meet one of the UN’s Sustainable Development Goals around improving water quality, which the UN states is necessary for the health and prosperity of people and the planet…
“Locals who know the water and use the water are both a motivated and knowledgeable resource, so citizen science networks can enable them to provide large amounts of data and act as stewards of their local water bodies and sources. Citizen science has the potential to revolutionize the way we manage water resources to improve water quality.”…
The report authors argue that improving water quality data will require governments and organizations to work collaboratively with locals who collect their own data, particularly where government monitoring is scarce, but also where there is government support for citizen science schemes. Water quality improvement has a particularly high potential for citizen scientists to make an impact, as professionally collected data is often limited by a shortage of funding and infrastructure, while there are effective citizen science monitoring methods that can provide reliable data.
The authors write that the value of citizen science goes beyond the data collected, as there are other benefits pertaining to education of volunteers, increased community involvement, and greater potential for rapid response to water quality issues…(More)”.
Toward a citizen science framework for public policy evaluation
Paper by Giovanni Esposito et al: “This study pioneers the use of citizen science in evaluating Freedom of Information laws, with a focus on Belgium, where since its 1994 enactment, Freedom of Information’s effectiveness has remained largely unexamined. Utilizing participatory methods, it engages citizens in assessing transparency policies, significantly contributing to public policy evaluation methodology. The research identifies regional differences in Freedom of Information implementation across Belgian municipalities, highlighting that larger municipalities handle requests more effectively, while administrations generally show reluctance to respond to requests from perceived knowledgeable individuals. This phenomenon reflects a broader European caution toward well-informed requesters. By integrating citizen science, this study not only advances our understanding of Freedom of Information law effectiveness in Belgium but also advocates for a more inclusive, collaborative approach to policy evaluation. It addresses the gap in researchers’ experience with citizen science, showcasing its vast potential to enhance participatory governance and policy evaluation…(More)”.
The Power of Volunteers: Remote Mapping Gaza and Strategies in Conflict Areas
Blog by Jessica Pechmann: “…In Gaza, increased conflict since October 2023 has caused a prolonged humanitarian crisis. Understanding the impact of the conflict on buildings has been challenging, since pre-existing datasets from artificial intelligence and machine learning (AI/ML) models and OSM were not accurate enough to create a full building footprint baseline. The area’s buildings were too dense, and information on the ground was impossible to collect safely. In these hard-to-reach areas, HOT’s remote and crowdsourced mapping methodology was a good fit for collecting detailed information visible on aerial imagery.
In February 2024, after consultation with humanitarian and UN actors working in Gaza, HOT decided to create a pre-conflict dataset of all building footprints in the area in OSM. HOT’s community of OpenStreetMap volunteers did all the data work, coordinating through HOT’s Tasking Manager. The volunteers made meticulous edits to add missing data and to improve existing data. Due to protection and data quality concerns, only expert volunteer teams were assigned to map and validate the area. As in other areas that are hard to reach due to conflict, HOT balanced the data needs with responsible data practices based on the context.
Comparing AI/ML with human-verified OSM building datasets in conflict zones
AI/ML is becoming an increasingly common and quick way to obtain building footprints across large areas. Sources for automated building footprints range from worldwide datasets by Microsoft or Google to smaller-scale open community-managed tools such as HOT’s new application, fAIr.
Now that HOT volunteers have completely updated and validated all OSM buildings in visible imagery pre-conflict, OSM has 18% more individual buildings in the Gaza strip than Microsoft’s ML buildings dataset (estimated 330,079 buildings vs 280,112 buildings). However, in contexts where there has not been a coordinated update effort in OSM, the numbers may differ. For example, in Sudan where there has not been a large organized editing campaign, there are just under 1,500,000 in OSM, compared to over 5,820,000 buildings in Microsoft’s ML data. It is important to note that the ML datasets have not been human-verified and their accuracy is not known. Google Open Buildings has over 26 million building features in Sudan, but on visual inspection, many of these features are noise in the data that the model incorrectly identified as buildings in the uninhabited desert…(More)”.
Under which conditions can civic monitoring be admitted as a source of evidence in courts?
Blog by Anna Berti Suman: “The ‘Sensing for Justice’ (SensJus) research project – running between 2020 and 2023 – explored how people use monitoring technologies or just their senses to gather evidence of environmental issues and claim environmental justice in a variety of fora. Among the other research lines, we looked at successful and failed cases of civic-gathered data introduced in courts. The guiding question was: what are the enabling factors and/or barriers for the introduction of civic evidence in environmental litigation?
Civic environmental monitoring is the use by ordinary people of monitoring devices (e.g., a sensor) or their bare senses (e.g., smell, hearing) to detect environmental issues. It can be regarded as a form of reaction to environmental injustices, a form of political contestation through data and even as a form of collective care. The practice is fast growing, especially thanks to the widespread availability of audio and video-recording devices in the hand of diverse publics, but also due to the increase in public literacy and concern on environmental matters.
Civic monitoring can be a powerful source of evidence for law enforcement, especially when it sheds light on official informational gaps associated with the shortages of public agencies’ resources to detect environmental wrongdoings. Both legal scholars and practitioners as well as civil society organizations and institutional actors should look at the practice and its potential applications with attention.
Among the cases explored for the SensJus project, the Formosa case, Texas, United States, stands out as it sets a key precedent: issued in June 2019, the landmark ruling found a Taiwanese petrochemical company liable for violating the US Clean Water Act, mostly on the basis of citizen-collected evidence involving volunteer observations of plastic contamination over years. The contamination could not be proven through existing data held by competent authorities because the company never filed any record of pollution. Our analysis of the case highlights some key determinants of the case’s success…(More)”.
Supporting Scientific Citizens
Article by Lisa Margonelli: “What do nuclear fusion power plants, artificial intelligence, hydrogen infrastructure, and drinking water recycled from human waste have in common? Aside from being featured in this edition of Issues, they all require intense public engagement to choose among technological tradeoffs, safety profiles, and economic configurations. Reaching these understandings requires researchers, engineers, and decisionmakers who are adept at working with the public. It also requires citizens who want to engage with such questions and can articulate what they want from science and technology.
This issue offers a glimpse into what these future collaborations might look like. To train engineers with the “deep appreciation of the social, cultural, and ethical priorities and implications of the technological solutions engineers are tasked with designing and deploying,” University of Michigan nuclear engineer Aditi Verma and coauthors Katie Snyder and Shanna Daly asked their first-year engineering students to codesign nuclear power plants in collaboration with local community members. Although traditional nuclear engineering classes avoid “getting messy,” Verma and colleagues wanted students to engage honestly with the uncertainties of the profession. In the process of working with communities, the students’ vocabulary changed; they spoke of trust, respect, and “love” for community—even when considering deep geological waste repositories…(More)”.
The Risks of Empowering “Citizen Data Scientists”
Article by Reid Blackman and Tamara Sipes: “Until recently, the prevailing understanding of artificial intelligence (AI) and its subset machine learning (ML) was that expert data scientists and AI engineers were the only people that could push AI strategy and implementation forward. That was a reasonable view. After all, data science generally, and AI in particular, is a technical field requiring, among other things, expertise that requires many years of education and training to obtain.
Fast forward to today, however, and the conventional wisdom is rapidly changing. The advent of “auto-ML” — software that provides methods and processes for creating machine learning code — has led to calls to “democratize” data science and AI. The idea is that these tools enable organizations to invite and leverage non-data scientists — say, domain data experts, team members very familiar with the business processes, or heads of various business units — to propel their AI efforts.
In theory, making data science and AI more accessible to non-data scientists (including technologists who are not data scientists) can make a lot of business sense. Centralized and siloed data science units can fail to appreciate the vast array of data the organization has and the business problems that it can solve, particularly with multinational organizations with hundreds or thousands of business units distributed across several continents. Moreover, those in the weeds of business units know the data they have, the problems they’re trying to solve, and can, with training, see how that data can be leveraged to solve those problems. The opportunities are significant.
In short, with great business insight, augmented with auto-ML, can come great analytic responsibility. At the same time, we cannot forget that data science and AI are, in fact, very difficult, and there’s a very long journey from having data to solving a problem. In this article, we’ll lay out the pros and cons of integrating citizen data scientists into your AI strategy and suggest methods for optimizing success and minimizing risks…(More)”.
The Essential Principle for Appropriate Data Policy of Citizen Science Projects
Chapter by Takeshi Osawa: “Citizen science is one of new paradigms of science. This concept features various project forms, participants, and motivations and implies the need for attention to ethical issues for every participant, which frequently includes nonacademics. In this chapter, I address ethical issues associated with citizen science projects that focus on the data treatment rule and demonstrate a concept on appropriate data policy for these projects. First, I demonstrate that citizen science projects tend to include different types of collaboration, which may lead to certain conflicts among participants in terms of data sharing. Second, I propose an idea that could integrate different types of collaboration according to the theory transcend. Third, I take a case of a citizen science project through which transcend occurred and elucidate the difference between ordinal research and citizen science projects, specifically in terms of the goals of these projects and the goals and motivations of participants, which may change. Finally, I proposed one conceptual idea on how the principal investigator (PI) of a citizen science project can establish data policy after assessing the rights of participants. The basic idea is the division and organization of the data policy in a hierarchy for the project and for the participants. Data policy is one of the important items for establishing the appropriate methods for citizen science as new style of science. As such, practice and framing related to data policy must be carefully monitored and reflected on…(More)”.
Embracing the Social in Social Science
Article by Jay Lloyd: “In a world where science is inextricably intermixed with society, the social sciences are essential to building trust in the scientific enterprise.
To begin thinking about why all the sciences should embrace the social in social science, I would like to start with cupcakes.
In my research, context is a recurring theme, so let me give you some context for cupcakes as metaphor. A few months ago, when I was asked to respond to an article in this magazine, I wrote: “In the production of science, social scientists can often feel like sprinkles on a cupcake: not essential. Social science is not the egg, the flour, or the sugar. Sprinkles are neither in the batter, nor do they see the oven. Sprinkles are a late addition. No matter the stylistic or aesthetic impact, they never alter the substance of the ‘cake’ in the cupcake.”
In writing these sentences, I was, and still am, hopeful that all kinds of future scientific research will make social science a key component of the scientific “batter” and bake social scientific knowledge, skill, and expertise into twenty-first-century scientific “cupcakes.”
But there are tensions and power differentials in the ways interdisciplinary science can be done. Most importantly, the formation of questions itself is a site of power. The questions we as a society ask science to address both reflect and create the values and power dynamics of social systems, whether the scientific disciplines recognize this influence or not. And some of those knowledge systems do not embrace the importance of insights from the social sciences because many institutions of science work hard to insulate the practice of science from the contingencies of society.
Moving forward, how do we, as researchers, develop questions that not only welcome intellectual variety within the sciences but also embrace the diversity represented in societies? As science continues to more powerfully blend, overlap, and intermix with society, embracing what social science can bring to the entire scientific enterprise is necessary. In order to accomplish these important goals, social concerns must be a key ingredient of the whole cupcake—not an afterthought, or decoration, but among the first thoughts…(More)”
Multi-disciplinary Perspectives on Citizen Science—Synthesizing Five Paradigms of Citizen Involvement
Paper by Susanne Beck, Dilek Fraisl, Marion Poetz and Henry Sauermann: “Research on Open Innovation in Science (OIS) investigates how open and collaborative practices influence the scientific and societal impact of research. Since 2019, the OIS Research Conference has brought together scholars and practitioners from diverse backgrounds to discuss OIS research and case examples. In this meeting report, we describe four session formats that have allowed our multi-disciplinary community to have productive discussions around opportunities and challenges related to citizen involvement in research. However, these sessions also highlight the need for a better understanding of the underlying rationales of citizen involvement in an increasingly diverse project landscape. Building on the discussions at the 2023 and prior editions of the conference, we outline a conceptual framework of five crowd paradigms and present an associated tool that can aid in understanding how citizen involvement in particular projects can help advance science. We illustrate this tool using cases presented at the 2023 conference, and discuss how it can facilitate discussions at future conferences as well as guide future research and practice in citizen science…(More)”.