Making Sense within Citizen Science: Meanings and Usability of Collective Water Monitoring Data

Testing a citizen science water monitoring approach in Tunisia

Questions of data and algorithmic analysis saturated the conference at which Dalton and Thatcher first called for a Critical Data Studies (Dalton and Thatcher, 2014a). Soon thereafter, Taylor published a response to their original call (Dalton and Thatcher, 2014b) that focused on the spatial nature of data and the need to critically contextualize it (Taylor, 2015a). This was one of multiple beginnings of Critical Data Studies, as it will always be three words cobbled together imperfectly signifying diverse sets of work around data’s recursive relationship to society (c.f. Graham 2014; Kitchin 2014, and elsewhere). We highlight that moment not to claim the concept, but to contextualize the focus of this co-interview. When Taylor published their response to Dalton and Thatcher, she focused on the specifically spatial nature of much data, not only in the content of said data, but also in the need to contextualize from where it originates and is put to use. Data varies across space in a variety of ways: from those included or excluded to those who access said data for analysis, manipulation and (re)presentation.Critical Data Studies calls attention to subject formation within these data regimes, for a critical examination of where the interpellation of the individual emerges in algorithmic culture (Striphas, 2015) and, through that, where the cracks and seams, the spaces for resistance and alternatives, might be found. When you append “critical” to a field of study, you run the risk of both offending other researchers, who rightly point out that all research is broadly critical and of bifurcating those who use critical theory from those who engage in rigorous empirical research. Kate Crawford recently observed that the meaning of Critical Data Studies is as political as the data it engages (Crawford, 2015). To extend that, it must remain contestable in order to contest the creation, commodification, analysis, and application of data. Ultimately, Critical Data Studies must make space for the recursive dialogue between the deeply theoretical and the robustly empiric and, in so doing, avoid the hubris of pseudopositivism and technological determinism, in favor of the nuanced and contingent.This is a dialogue between Dalton, Thatcher, and Taylor on the spatial nature of data with respect to Critical Data Studies. It highlights the historical variability of the processes of data production and accumulation and how this, in turn, has resulted in the uneven development of data. We ask both what is missing and what must be brought to the analysis of data in order to respond to the existence of particular dataspheres governed by the kinds of technology available in different locations. In form, Dalton and Thatcher ask the first question and Taylor responds before asking the second, alternating from there. As such, this dialog has many entry and exit points and is not meant as a definitive statement of what Critical Data Studies is or who can speak for it. Rather, we choose to live in the unresolved tensions between researcher and subject, technology and society, space and time (Haraway, 1991), and we encourage our readers to do the same.

What would data science look like if its key critics were engaged to help improve it, and how might critiques of data science improve with an approach that considers the day-to-day practices of data science? This article argues for scholars to bridge the conversations that seek to critique data science and those that seek to advance data science practice to identify and create the social and organizational arrangements necessary for a more ethical data science. We summarize four critiques that are commonly made in critical data studies: data are inherently interpretive, data are inextricable from context, data are mediated through the sociomaterial arrangements that produce them, and data serve as a medium for the negotiation and communication of values. We present qualitative research with academic data scientists, “data for good” projects, and specialized cross-disciplinary engineering teams to show evidence of these critiques in the day-to-day experience of data scientists as they acknowledge and grapple with the complexities of their work. Using ethnographic vignettes from two large multiresearcher field sites, we develop a set of concepts for analyzing and advancing the practice of data science and improving critical data studies, including (1) communication is central to the data science endeavor; (2) making sense of data is a collective process; (3) data are starting, not end points, and (4) data are sets of stories. We conclude with two calls to action for researchers and practitioners in data science and critical data studies alike. First, creating opportunities for bringing social scientific and humanistic expertise into data science practice simultaneously will advance both data science and critical data studies. Second, practitioners should leverage the insights from critical data studies to build new kinds of organizational arrangements, which we argue will help advance a more ethical data science. Engaging the insights of critical data studies will improve data science. Careful attention to the practices of data science will improve scholarly critiques. Genuine collaborative conversations between these different communities will help push for more ethical, and better, ways of knowing in increasingly datum-saturated societies.

The accumulation of plastic litter in marine environments presents a major environmental challenge to sustainability and is central to the United Nations (UN) Sustainable Development Goals (SDGs). However, the vast size of oceans and the widespread nature of marine plastic litter make its monitoring difficult. Citizen science offers a promising solution, providing valuable data for SDG monitoring and reporting, however, there has been no evidence of its use to date. In this presentation, we share how Ghana became the first country to integrate citizen science data into their official statistics and the official monitoring and reporting of SDG indicator 14.1.1b for marine plastic litter. This effort also helped to bridge local, community level data collection with national and global monitoring and policy agendas, aligning with the SDG framework. The data have already contributed to Ghana's Voluntary National Review and been reported in the UN SDG Global Database, helping to inform national policies.In this presentation, we will focus on the process of validating citizen science data and integrating it into official monitoring and reporting, involving key stakeholders at local, national, and global levels, such as government agencies, the UN, civil society organizations, citizen science networks, and academia. This approach offers a model for other countries and citizen science initiatives interested in adopting similar methods for official monitoring and policymaking. A central theme will be how citizen science projects can be designed to foster collaboration and trust among diverse stakeholders, including governments, UN bodies, and local communities. We will highlight our success and lessons learnt, and showcase how knowledge production through citizen science can strengthen sustainability efforts, influence effective policy, and highlight the value of participatory sciences.

The fields of Information and Communication Technologies for Development (ICT4D) and critical data studies have been historically distinct from each other, each bearing different histories and research foci. However, recent evolutions of ICT4D have problematised the focus on "development" that originally characterised the field, and shifted to an approach that openly embraces themes proper of the newer field of critical data studies. In this paper, after outlining the conceptual evolution of ICT4D, we note its new intersection with the themes and problems posed by critical data studies. To detail such an intersection, we offer a joint research agenda – on themes of digital identity, datafication of the Global South and adverse digital incorporation – that groups together researchers from the two fields. By doing so, this paper sets the basis for a conversation between ICT4D and critical data studies, a conversation that can generate epistemological growth for both fields.

Data Desire in the Anthropocene

Citizen science projects globally have increasingly been implemented in collecting and analysing environmental data. At the same time, these initiatives are often project-based and, therefore, of short duration. This presents a challenge as data from such activities may not be used in research and political decision-making. This research aims to explore the barriers and solutions for establishing a sustainable long-term citizen-based plastic monitoring strategy in fresh waters based on a case study in Accra, Ghana. This case study is particularly relevant due to the significant issue of plastic pollution in the region, limited official monitoring data to effectively address the problem, and the potential role of citizen science in addressing this data gap in the long term. Data on barriers and solutions were collected based on eight expert interviews, a survey amongst 17 stakeholders, and subsequent roundtable discussions with 24 experts and stakeholders from academia, the private sector, the public sector, and civil society. From this, we identified 30 types of barriers and 21 types of solutions to implement citizen science in the long term. These barriers and solutions relate to five fields of action (social, economic, environmental, technical, and management and governance) and four stakeholder groups (public sector, private sector, civil society, and academia) to implement solution pathways for long-term citizen science projects. Based on our findings, we make suggestions as to how citizen science can be implemented more sustainably in the future in different fields of action and from various institutional perspectives. With this, we hope to advance the potential use of citizen science and citizen science data in research and policy design related to plastics in fresh waters.

<p>Earth and water monitoring and observation systems provide open geo data to scientists and professionals supporting distributed knowledge of major hydromet dynamics and extremes. Mobile technologies, at the same time, are empowering citizens who are nowadays informed and involved in volunteering actions designed and implemented to make our communities more safe and sustainable. Citizen science, as a consequence, is gaining momentum empowering the general public, from the “pleasure of doing science” to complementing observations, increasing scientific literacy, and supporting collaborative behaviour to solve specific water-related challenges. This work illustrates a conceptual transdisciplinary assessment model that was designed with the goal of standardizing the use of citizen science for advancing hydrology. This work was promoted by the Citizens AND HYdrology (CANDHY) Working Group established by the International Association of Hydrological Sciences (IAHS), and that is composed by a diverse group of hydrological, computer and social science experts. A community paper (Nardi et al., in press) presented the conceptualization of this transdisciplinary framework by identifying the shared constituents, interfaces and interlinkages between hydrological sciences and other academic and non-academic disciplines. Particular emphasis was given to the integration of human sensing and behavioural mechanisms into citizen science programs addressing hydrological problems. The proposed CANDHY transdisciplinary framework is here further tested and applied to assess some selected citizen science programs to understand the knowledge gaps and opportunities arising from ongoing citizen science programs. This comparative assessment shows some interesting preliminary results demonstrating the capacity of the proposed framework in homogenizing and accumulating knowledge from the collaboration of diverse participatory programs addressing similar or complementary hydrological challenges.</p><p> </p><p>Nardi F. et al., in press. Citizens AND HYdrology (CANDHY): conceptualizing a transdisciplinary framework for citizen science addressing hydrological challenges. Hydrological Sciences Journal, https://doi.org/10.1080/02626667.2020.1849707</p>

Citizen science and particularly mobile crowd sourcing (MCS) has large potential in water resources management for data collection and awareness raising. Concerns about data quality, and initiating and sustaining citizen involvement hamper incorporation of citizen science in water monitoring, together with a lack of practical guidance how to set up citizen science monitoring programs. This review presents an overview of key success factors for citizen science including MCS. Specific attention is paid to motivational aspects. Success factors were organized according to project phase and motivations according to self‐determination theory. The presented overviews provide practical guidelines for setting up citizen science projects. WIREs Water 2017, 4:e1218. doi: 10.1002/wat2.1218This article is categorized under: Water and Life > Conservation, Management, and Awareness Engineering Water > Planning Water Human Water > Water as Imagined and Represented

Reviewed by: Undone Science: Social Movements, Mobilized Publics, and Industrial Transitions by David J. Hess Stefania Milan (bio) Undone Science: Social Movements, Mobilized Publics, and Industrial Transitions. By David J. Hess. Cambridge, MA: MIT Press, 2016. Pp. 258. Hardcover $75. Undone Science takes a political sociological approach to science and technology, scientific expertise and knowledge, exploring the contentious nature of innovation and regulation as they embrace both official and grassroots actors and expertise. In so doing, it promotes a much-needed dialogue between Social Movement Studies (SMS) and Science and Technology Studies (STS)—two disciplines that have seldom talked to each other, despite their parallel development and the potential mutual benefit of such cross-pollination. The six chapters tackle a wide range of compelling case studies, from solar energy to organic food, from cancer therapies to climate change. This volume is a vital read for at least four reasons. First, it encourages a dialogue that is simultaneously arduous and necessary, one that can [End Page 371] enrich both disciplines. For example, as the author skillfully explains, SMS brings into STS an attention to inequality and to publics “other than” those officially associated with scientific knowledge. Conversely, STS contributes to break the “black box” approach of much SMS work on technology and innovation. In so doing, the author puts new (conceptual) weapons in the hands of scholars interested in the controversies surrounding some grand challenges of our times, from climate change to vaccines. He also responds to a lack of systematic treatment of scientific controversies in, for example, political sociology. Second, the book proposes a pioneering “way of thinking about the SMS-STS relationship” (p. 23) that emerges from and moves past case studies. This creative effort goes well beyond merely syncretizing off-the-shelf concepts. On the contrary, while grounding his work on a comprehensive literature review of the two fields, the author develops a novel, transdisciplinary conceptual toolkit that includes original notions such as “undone science” and “mobilized publics.” Particularly notable is the effort to bring a multi-faceted, dynamic notion of agency into the spotlight, looking at how said agency develops in relation to knowledge production and the related negotiations. Third, the book addresses current and urgent problems of political nature—including contentious knowledge and the mobilization of public support for policy decisions—for which the traditional “siloed” treatment is no longer sufficient. This is particularly relevant in times of rampant populism and decreasing faith in science and the scientific project. Looking beyond the case studies that illustrate the book, the proposed approach appears particularly useful to situate and understand, for example, counter-surveillance publics, digital rights and internet governance mobilizations, and “data activism”—in other words, new publics that coalesce around highly specialized and technical issue areas. The case studies on citizen science and smart meters already move in this direction. Finally, the book is well-written and engaging. It makes for an excellent read as a whole as well as on a chapter-by-chapter basis (e.g., in a course syllabus). It is a must in any graduate program on both disciplines, as well as in neighboring fields such as cultural sociology, (new) media studies, sociology of innovation, and critical data studies. It is highly recommended also to students of informatics and engineering, as it illuminates the social dimensions of technology development. The book has only two weaknesses. First, it is built on a somewhat shallow understanding of the evolution of the nature of information today, its validation and diffusion. The so-called “datafication” and the “platformization” of human relations subtend in fact to a fundamental change in the deep fabric of society, with dramatic consequences at the ontological and epistemological level (think of the “fake news” phenomenon). This brings into light a number of questions, for example, how do “intellectual [End Page 372] contention” and the “official public” evolve in the age of social media? How can “counterpublics” be effectively mobilized? What is the agency of digital infrastructure in this process? Second, although the author demonstrates awareness of “alternative” approaches such as postcolonial thinking, the book remains anchored, as per the author’s admission, to a Western perspective, with largely U.S. examples. Adopting...

In critical data studies, biometric AI is commonly recognized as a mechanism of exclusion (cf. e.g., Amoore, 2006; Gates, 2011). The technology which is "built to measure life" (Ajana, 2013) processes digital representations of biological data in order to identify and authenticate individuals. Founded on the ideology and governmentality of dataism (van Dijck, 2014), the datafication of embodied identity reduces existence to discrete measurable results, within an imaginary of data as a source of unlimited knowledge. In search of a queer counter narrative of biometrics, this paper presents a philosophical-empirical inquiry of biohacking that endorses sensuous knowledge (Salami, 2020) to flesh out the limits of metric measurement (cf. Lagerkvist 2022). By interlinking existential media theory (Lagerkvist, 2017, 2020, 2022) with a critique of the "robotic way that dominates how we view knowledge today" (Salami, 2020, p. 17), "queer" is mobilised as a subject position particularly at risk in the binary configuration of digital existence; and a theoretical ambition to "bend and challenge ideas that are commonly taken for granted" (Tudor, 2021, p. 12). Based on ethnographic data collected between 2021-2023, biohacking is presented as an anticipatory existential media practice that twists biometrics for an operation of becoming. Biohackers incorporate technology into their own bodies to explore the relationships between embodiment and computation. Despite being a diverse community of practice (with purposes as varied as, e.g., interaction design; citizen science; body politics; do it yourself (DIY) and do it together (DIT) movements), the masculinist transhumanist call to live computational metaphors and maxims for human enhancement, prevails as the dominant narrative. By juxtaposing qualitative interviews conducted with biohackers self-identifying as queer against participatory observations of public biohacking performances, this paper interrogates an ethos of biohacking that exceeds this transhumanist imaginary and its adoption of functionalist attitudes towards the body and self through a spectrum of existential practices. I submit that these emancipatory, relational and caring practices illuminate the ethic-onto-epistemological dimensions of biohacking, as biometric data gets reappropriated to perform queer embodiment and subjectivation: By meshing and repurposing the subjective and objective perspective upon the body to reveal existence as a performance, the technology is both mimicked and debunked. Through claiming biometric data for an operation of becoming, the approach to data itself is queered, explored as a sensuous knowledge device for incommensurability. These existential twists of biometrics stress the limits of biometric AI. By countering the enforced classification, categorization and compartmentalization of identity, existential biohacking practices transcend mainstream techno-utopias by fleshing out human needs and qualities. Such a view is embedded in an understanding of media as existential media - that is technologies that condition human and more-than-human life by reflecting our technological entanglements while confronting us with our limits - our situated, embodied and mortal existence (Lagerkvist, 2022). Following Karl Jaspers (1970), limits are approached as a privileged reality to trouble figurations of unboundedness; by reconceiving of living with data as an ethical quest which reintroduces figurations of limits to datafication as a counter move to the ubiquitous belief in digitized data as supreme to human ways of knowing, based on "an aura of scientific authority" (Lupton, 2016, p. 56; van Dijck, 2014). At the threshold, sensuous knowledge can provide a partial and perspectival framing (Pink et al. 2018) to challenge the rational by the immeasurable and expose the existential implications of today's media technologies. By embracing the "emotional, embodied and poetic partner to our rational and logical intelligence" (Salami, 2020, p. 15), biohackers seize the limits of measurement to anticipate the nexus of ethics, technology and the body at stake with biometric AI. As biohacks of biometric existence, their biomedia present tools to intentionally restrict our aspirations to unbounded transparency, certainty, and resolution, and remind us that "the direction of technology cannot be looked for in technology itself, but must be thought of in a conscious ethos" (Jaspers, 2011, p. 119). Such existential knowing offers an approach to knowledge as an ethical activity to realize one's relational self (Nancy, 2000). This process is never stagnant or fixed, but fluid, multiple, uncertain, and in its incommensurability essentially queer. Galvanizing biometrics as existential media opens up a generative and imaginative, yet concretely situated ethical potential through which we can learn about being in the world with data in face of the inexhaustible diversity of the volatile, relational and vulnerable human body as our universal human condition, despite its asymmetric co-implication in different power regimes.

Citizen science is emerging as an increasingly viable way to support existing water monitoring efforts. This article assesses whether water quality data collected by large numbers of volunteers are as reliable as data collected under strict oversight of a government agency, and considers the potential of citizen science to expand spatial and temporal coverage of water monitoring networks. The analysis hinges on comparison of data on water temperature and dissolved oxygen (DO) in freshwater streams and rivers collected by four entities: the United States Geological Survey (USGS) network of field scientists, the USGS network of automated sensors, the Georgia Adopt-A-Stream volunteer water monitoring program, and the University of Rhode Island Watershed Watch (URIWW) volunteer water monitoring program. We find that volunteer-collected data exhibit the expected relationship between temperature and DO. Furthermore, we find that volunteer- and USGS-collected data lie in roughly the same range, although...

Critical data studies have made great strides in bringing together data analysts and urban design, providing an extensible concept which is useful in visualizing the role of local and planetary data networks. But in the light of the experience of Sidewalk Labs, critical data studies need a further push. As smart cities, algorithmic urbanisms, and sensorial regimes inch closer and closer to reality, critical data studies remain woefully blind to economic and political issues. Data remains undertheorized for its economic content as a commodity, and the political ramifications of the data assemblages remain locked in a proto-political schema of good and bad uses of this vast network of data collection, analysis, research, and organization. This paper attempts to subject critical data studies to a rigorous critique by deepening its relationship to the history thus far of Sidewalk Labs' project in Quayside, Toronto. It is broken into sections. The first section discusses the material reality of Kitchin and Lauriault's (2014) data assemblages and data landscapes. The second section investigates data itself and what its ‘inherent' value means in an economic sense. The third section looks at the way the understanding of data promoted by the data assemblage effects smart city design. The fourth section examines the role of the designer in shepherding this vision, and moreover the data assemblage, into existence.

Storytelling essentials are stories that direct attention, trigger emotions, and prompt understanding. Citizen science has recently promoted the narrative approach of storytelling as a means of engagement of people of all ages and backgrounds in scientific research processes. We seek understanding about the typology of storytelling in citizen science projects and explore to what extent the tool of storytelling can be conceptualized in the approach of citizen science. In a first step, we investigated the use and integration of storytelling in citizen science projects in the three European German-speaking countries. We conducted a low threshold content analysis of 209 projects listed on the German-speaking online platforms for citizen science projects “Bürger schaffen Wissen”, “Österreich forscht”, and “Schweiz forscht”. Two expert workshops with citizen science practitioners were held to validate and discuss the identified role of stories in the practice of citizen science. Our analysis revealed three major categories mirroring how stories are being integrated and applied in citizen science. The first category refers to projects, in which stories are the core research objective. The second category is characterized by the application of stories in different phases of the research project. The third category encompasses stories as agents being part of the communication and organization of the project. We illustrate the practical application of these categories by three representative case studies. By combining the functionality of the categories and abstracting the linkages between storytelling and citizen science, we derived a generalized model accounting for those linkages. In conclusion, we suggest that storytelling should be a prerequisite to enhance the competencies of the actors involved and to exchange knowledge at the interfaces of science and policy as well as science and society.

Some in our discipline have recently voiced the opinion that political science is a data science. What follows from this argument is that we as instructors are training the next generation of data scientists, especially professionals and researchers who will work with big data. This paper explores the implications for political science education, arguing that we are uniquely suited to make students critical consumers of big data—a goal we can achieve by creating dialogue with work in critical data studies. I offer three suggestions about how to integrate lessons from critical data studies in the classroom. These include ideas about diversifying the research methods curriculum, using data work for service learning, and modeling best practices in our own engagement with students. Though the discussion in this piece is theoretical, the takeaways include a call to action to create more meaningful dialogue with critical data studies.