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Datafication is widely acknowledged as a process “transforming all things under the sun into a data format” (van Dijck, 2017, p. 11). As data become both objects and instruments of social science, many scholars call for attention to the ways datafication reconfigures scholarly knowledge production, its methodological opportunities, and challenges (Lomborg et al., 2020). This contribution offers a reflection on the interdependence between methodological approaches taken to study datafication and concepts about it, that these approaches provide within the domains of critical data studies and media studies. Expanding on the concept of methods' performativity (Barad, 2007), I apply the notion of methods assemblages: “a continuing process of crafting and enacting necessary boundaries [and relations]" between researchers and all relevant matters (Law, 2004: 144). The key question in the presented study is what kinds of methods assemblages are being applied in current datafication research and what concepts of datafication they produce. 32 expert interviews were conducted with scholars who published empirical work on dataficaiton between 2015 and 2020. Three methods assemblages were developed. Central to distinguishing between methods assemblages are the ways of associating of the involved actors and things. In my analysis the questions of (1) what we are talking about when talking about datafication and (2) kinds of knowledges that researchers were interested in producing can be understood as such ways of associating. The methods assemblages contribute to critical data studies by producing accounts about datafication processes that are in concert with the methods assemblages applied to study these.

Data is everywhere. Increasingly woven into the fabric of everyday life, data is ubiquitous. Intensifying a ‘quantifying of the world’ (Mayer-Schonberger & Cukier, 2013) the gathering and applicati...

Although there is much discussion in scientific and law journals regarding direct-to-consumer genetic testing (DTCGT), there is a paucity of philosophical-ethical examination of how such services threaten to repeat the essentialist, racial-projects of the past. On the one hand, testing for ancestry can be cathartic: for those lacking familial history as to when and how they came to be where they are, DTCGT can offer powerful access to their lineage and identity-formation. On the other hand, DTCGT inevitably reinscribes problematic epistemologies of race—even when the companies claim that their tests can be tools to combat white supremacy. Tracing the roots of biological essentialism back to Aristotle, through the invention of raza as cocreator of modernity, and up to critical race theories today, provides a strong foundation to examine the nascent race-thinking underlying DTCGT. Borrowing heavily from Paul Taylor and Charles Mills, but also enlisting scholars from other disciplines, such as Ifeoma Ajunwa (law), Alondra Nelson (sociology), and Troy Duster (genetics), provides the broad scope necessary for thoughtful, agile engagement of that which is ameliorative, unethical, and even dangerous—for all of us—in the age of 23andMe.

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.

Data, how we conceptualize them, who uses them, and how they are used, are central to current questions about smart cities and critical data studies. This article develops a conceptual fram...

Digital media serve manifold purposes connected to communication, transition, resource allocation, and integration in the context of forced migration. Many apps and platforms rely on user data. Organizations do not always clearly communicate what data are collected for which purposes. Policies on data and privacy should convey this information, but they rarely increase clarity and transparency. This can create vulnerabilities for users and raises questions about data literacy: How much do they understand about data practices and how can organizations inform them better? This qualitative study explores 10 digital services (apps-based and web-based) with the walkthrough method in combination with a content analysis of data policies. It charts communication efforts about data practices and consequences for privacy. The findings imply that many organizations fail to address these issues efficiently. They need to critically revise their communication strategies to create transparency and build data literacy among users.

This paper discusses an explorative approach on strengthening critical data literacy using data science methods and a theoretical framing intersecting educational science and media theory. The goal is to path a way from data-driven to data-discursive perspectives of data and datafication in higher education. Therefore, the paper focuses on a case study, a higher education course project in 2019 and 2020 on education and data science, based on problem-based learning. The paper closes with a discussion on the challenges on strengthening data literacy in higher education, offering insights into data practices and the pitfalls of working with and reflecting on digital data.

This chapter is aimed at presenting two-core elements of the world of data, oneat an individual level and the other, at thecollective level. In the first unit, wewill review the concepts and skills needed to enable personal data agency,which can beunderstood as the individual’s ability to understand andchallenge the data collected about him/her. By doing so, he/she willbe able to make informed decisions about his/her data throughunderstanding the legal landscape of data protection and datarights. This will allow individuals to curate and control their (personal) data. Todo this we need to gain knowledge of these datadriven systems, beingable to identify them as well as understanding how they operate. In thesecond unit, we will present thekey elements and principles of indigenousdata sovereignty (ID-SOV). This is a relatively recent concept that can beunderstoodas the right of indigenous peoples to own, control, access and possess datathat derive from their needs andsocial reality. This is grounded on therights to self-determination and governance as affirmed in the UnitedNations Declaration on the Rights of Indigenous Peoples (UNDRIP).

En esta unidad, exploraremos el concepto de justicia de datos y las diferentesinterpretaciones de la idea de justicia de datos. También profundizaremos endiferentes enfoques de la justicia de datos, analizando sus beneficios y dificultades. Luego nos centraremos en el marco de Taylor (2017) para el diseño y la gobernanzade las tecnologías de datos. El marcoes una capacidad (Sen, 2009) y un enfoquebasado en la libertad que examina cómo las tecnologías de datos influyen en el tipode vida que la gente considera valiosa para vivir. Existe una interacción innegable entre las tecnologías basadas en datos y lavida diaria de las personas. Esta interacción es compleja y matizada y tieneimplicaciones tanto positivas como negativas. Los sistemas basados en datos tienenlacapacidad de inspirar a las organizaciones a innovar en la forma en que operan,mientras que los gobiernos pueden usar lainformación para informar políticasdirigidas al bienestar económico. Pero también los sistemas basados en datospuedenservir como una herramienta para discriminar o marginalizar comunidadesvulnerables. La forma en que se gestionan los sistemas es fundamental paraofrecer servicios y beneficios por igual a todos los ciudadanos. La justicia de datoses una respuesta a las implicaciones sociales negativas que estos sistemas tienenen nuestras vidas.

In this unit, we explore the concept of data justice and the different interpretationsof the idea. That is, we consider thedifferent approaches to data justice, lookingat their benefits and pitfalls. We then focus on Taylor’s (2017) framework for datatechnologies’ design and governance. The framework is a capability (Sen, 2009) andfreedom-based approach that examines how data technologies influence the kindof lives that people deem valuable to live. As a complement to the notion of data justice, which is mainly a conceptual one, data feminism, the data ethics canvas,and the seven inequities held in power aregoing to be described as actionableanalytical tools to address issues of data justice when working with research in the classroom. We believe that with this module the mechanisms of negotiability and agency somuch needed to be able to interact in data-driven systems can be improved.

Este capitulo tiene como objetivo presentar dos núcleos de elementos dedatos, uno a nivel individual y otro a nivel colectivo.En la primera unidad,revisaremos el concepto, los principios y las habilidades necesariaspara habilitar la agencia de datospersonales y en la segunda unidad,exploraremos el concepto de soberanía de datos indígenas (SOB-DI). En la primera unidad, revisaremos los conceptos y habilidades necesariospara habilitar la agencia de datos personales,entendida como la capacidadde los individuos para comprender y cuestionar los datos recopilados sobre ellos,para tomardecisiones informadas sobre sus datos al comprender el panorama legalde protección de datos y derechos de datos. Estopermitirá a las personas conservar ycontrolar sus datos (personales). Para hacer esto, necesitamos adquirir conocimientode estos sistemas, poder identificarlos, pero también entender cómo funcionan.En la segunda unidad, presentaremos loselementos y principios clave de la soberanía de datos indígenas (ID-SOV), un concepto relativamente reciente quepuede entenderse como los derechos de los pueblos indígenas a poseer, controlar, acceder y poseer datos que deriven de sus necesidadesy realidad social, fundamentada en los derechos a la autodeterminación y la gobernanza como se afirma en laDeclaración de las Naciones Unidas sobre los Derechos de los Pueblos Indígenas (DNUDPI).

Applications of artificial intelligence / machine learning (AI/ML) are dynamic and rapidly growing, and although multi-purpose, are particularly consequential in health care. One strategy for anticipating and addressing ethical challenges related to AI/ML for health care is co-design - or involvement of end users in design. Co-design has a diverse intellectual and practical history, however, and has been conceptualized in many different ways. Moreover, the unique features of AI/ML introduce challenges to co-design that are often underappreciated. This review summarizes the research literature on involvement in health care and design, and informed by critical data studies, examines the extent to which co-design as commonly conceptualized is capable of addressing the range of normative issues raised by AI/ML for health. We suggest that AI/ML technologies have amplified existing challenges related to co-design, and created entirely new challenges. We outline five co-design 'myths and misconceptions' related to AI/ML for health that form the basis for future research and practice. We conclude by suggesting that the normative strength of a co-design approach to AI/ML for health can be considered at three levels: technological, health care system, and societal. We also suggest research directions for a 'new era' of co-design capable of addressing these challenges. Link to full text: https://bit.ly/3yZrb3y

The paper explores the potential and limitations of big data for researching racism on social media. Informed by critical data studies and critical race studies, the paper discusses challenges of doing big data research and the problems of the so called ‘white method’. The paper introduces the following three types of approach, each with a different epistemological basis for researching racism in digital context: 1) using big data analytics to point out the dominant power relations and the dynamics of racist discourse, 2) complementing big data with qualitative research and 3) revealing new logics of racism in datafied context. The paper contributes to critical data and critical race studies by enhancing the understanding of the possibilities and limitations of big data research. This study also highlights the importance of contextualisation and mixed methods for achieving a more nuanced comprehension of racism and discrimination on social media and in large datasets. publishedVersion

Quantification is central to the narration of the COVID-19 pandemic. Numbers determine the existence of the problem and affect our ability to care and contribute to relief efforts. Yet many communities at the margins, including many areas of the Global South, are virtually absent from this number-based narration of the pandemic. This essay builds on critical data studies to warn against the universalization of problems, narratives, and responses to the virus. To this end, it explores two types of data gaps and the corresponding “data poor.” The first gap concerns the data poverty perduring in low-income countries and jeopardizing their ability to adequately respond to the pandemic. The second affects vulnerable populations within a variety of geopolitical and socio-political contexts, whereby data poverty constitutes a dangerous form of invisibility which perpetuates various forms of inequality. But, even during the pandemic, the disempowered manage to create innovative forms of solidarity from below that partially mitigate the negative effects of their invisibility.

Information and Communication Technologies (ICT) are being used across the world to generate efficiency gains for farmers. This has led to an information and data explosion with an associated boom in new applications, tools, actors, business models, and entire industries. Agri-food systems are being transformed. Beyond the technological developments, data for and from farmers has become a growth area, driving expectations and investments in big data (but also small data), blockchain technology, precision agriculture, farmer profiling and e-extension. Investing in data-driven agriculture is expected to increase agricultural production and productivity, help adapt to or mitigate the effects of climate change, bring about more economic and efficient use of natural resources, reduce risk and improve resilience in farming, and make agri-food market chains much more efficient. Ultimately, it will contribute to worldwide food and nutrition security. Smallholders in particular have much to gain from data – small improvements in their operations are likely to provide larger gains at household level, proportionally, and, if the improvements are widely adopted, the whole agricultural sector in many countries that depend on smallholder agri-food systems can be transformed. However, for smallholders to benefit from data-driven agriculture, tools and applications need to be designed for their specific situations and capacities; they – and the organizations that support them – need to grow their capacities to become smart data users and managers; measures are needed to ensure that farmer-generated data is not exploitedor misused; and smallholders, usually the least powerful parts of a value chain, must grasp every opportunity to be included in the collective data flows within agri-food systems.

Este capitulo tiene como objetivo explorar críticamente algunas cuestiones clave en lo que se refiere a los datos que nos conciernen no solo individualmente, sino también a nivel colectivo. Se explora cómo analizamos e interactuamos con los datos, cómo los datos están dando forma a nuestra sociedad, cuáles son los marcos legales en torno a los usos de los datos y cómo podemos cuestionar los usos que se les dan a nuestros datos. En la primera unidad, se examinan los conceptos básicos de la ética de los datos. En la segunda unidad, se consideran los principios fundamentales que rigen lo que está bien y lo que está mal en el ciclo de datos, desde la recolección y producción hasta su uso. Se examinan los conceptos de privacidad de datos relacionados con las regulaciones y leyes sobre apertura, publicación, recopilación, almacenamiento y administración de datos. En la tercera unidad, se revisan los enfoques críticos de la Inteligencia Artificial (IA) y los algoritmos. Se discuten cuestiones como la opacidad y el sesgo en los algoritmos, así como las regulaciones para la toma de decisiones automatizadas y el análisis predictivo que se sustentan en desequilibrios de poder y conducen a ellos, lo que limita las oportunidades de participación. Finalmente, la cuarta unidad se centra en la agencia personal, donde el objetivo es permitir a los ciudadanos cuestionar el uso de sus datos como medio para problematizar el avance del poder de los datos.

Data and data visualisations – in the forms of graphs, charts and maps – are becoming an increasingly important feature of social, public and political life. Yet within existing scholarship, the democratic significance of data visualisations has thus far received minimal attention. This article offers a first systematic attempt to make sense of and scrutinise the role of data visualisation in democracy. We apply deliberative systems theory in the analysis of three original case studies to elucidate how data visualisation can integrate into the overall anatomy of democracy, and to normatively assess how data visualisation contributes towards key democratic ideals. Conclusively, we highlight how critical perspectives on power, ideology and epistemology problematise any simplistic account of how data visualisation matters for democracy. publishedVersion

The increase in the price of gold, due to a shift to safe investments during the global economic crisis, has led to a rapid expansion of gold production. Alongside legal gold mines, wildcat gold mining has developed in French Guiana since the early 2000s. This phenomenon, with its social, environmental and economic consequences, is at the heart of the environmental governance of this territory. However, its difficult quantification is the subject of multiple controversies. Environmental governance is increasingly dependent on metrological regimes aimed at quantifying political action in order to objectify it. This article examines the role of metrology in implementing environmental policies in sparsely populated regions via the example of wildcat gold mining in French Guiana. Based on the study of two observatories, one managed by public authorities, the other by an NGO, we deconstruct their maps and counter-maps of wildcat gold mining. To do so, we make a distinction between measurement, commensuration and its diffusion. This focus on “measurement-commensuration-diffusion” allows us to identify three key phases in the production of nature statistics. We argue that the critical analysis of metrological processes through this three-step framework reveals methodological controversies that reflect different and even divergent political visions. The article also shows that metrological systems for environmental protection are the focus of targeted political disputes. It reports on the current disagreements—not only between the State and NGOs but also within the State itself—on the proposed solutions for fighting the impacts of wildcat gold mining in French Guiana and the broader issues of data production in Amazonia.

This article adapts the ethnographic medium of the diary to develop a method for studying data and related data practices. The article focuses on the creation of one data diary, developed iteratively over three years in the context of a national centre for monitoring disasters and natural hazards in Brazil (Cemaden). We describe four points of focus involved in the creation of a data diary – spaces, interfaces, types and situations – before reflecting on the value of this method. We suggest data diaries (1) are able to capture the informal dimension of data-intensive organisations; (2) enable empirical analysis of the specific ways that data intervene in the unfolding of situations; and (3) as a document, data diaries can foster interdisciplinary and inter-expert dialogue by bridging different ways of knowing data.

Building on their concept of metainterface, S��ren Bro Pold and Christian Ulrik Andersen analyze the change in perception and experience that bring forth the always-on(line) mode of engaging with digital content. The notion of ���spectacle���, in itself having a long history in critical theory, is employed here to discuss media politics and the struggle for power in terms of aesthetized computation, with their main driving forces being data analytics, surveillance and forensics. Pold and Andersen uncover how metainterface spectacle can also serve to empower political agency through reclaiming the apparatus.

This paper contributes to a project that maps the concept of ‘data provenance’ into qualitative data research. Data provenance is a concept from computer science that allows us to trace the history of sets of data to determine the accuracy and validity of a database. We transform this into a critical concept by arguing that data provenance can be used to trace the acts of governance and rhetoric. We then analyse the forms of discursive power that shape transactions in data. Our approach can create a history of the governance and justifications that are used to build and assemble datasets from multiple sources. Presently, data often lacks this information about its own discursive origins, unlike other forms of data provenance. Critical data provenance gives us a model for thinking about how governance could be mapped onto data. And thus, critical data provenance is also a framework for critiquing the justifications used when dataset owners acquire data–for instance, whether data stewards or users are encouraged to be ‘open’, to ‘share’, or be ‘transparent’. To this end, we demonstrate this model of thinking and provide the analytical tools necessary to redeploy these ideas into new contexts.

International audience; The rise of digital footprints has created a number of promises and expectations for the study of territorial dynamics, particularly those of tourist cities. These footprints would make the observation of visitors' spatial practices possible and make up for the lack of information on these practices at an urban scale. Thus, many studies use data from social networks to study the touristic space at different geographical scales. These studies provide several types of visualisations based on this data, thus making it possible to represent and show a supposedly new touristic space-time-from the heat map to the dashboard, the digital footprints are displayed as processed, aggregated, calculated and smoothed. All these transformations-resulting from algorithmic black boxes that do not allow a precise understanding of the methodologies (often complex and approximate)-are often not very transparent. Consequently, the technicality and opacity of this data make necessary the development of critical approaches that allow the deconstruction of these new mapping registers. Based on data collected on a widely used social network, Instagram, we wish to question digital footprints as a potential tool to observe tourist practices, by going back through the data genealogy, from the map to the footprint. Our approach consists of going back to the initial data and their associated metadata, in order to explore two fundamental dimensions, conditions prerequisite for more complex explorations: time and space. Therefore, we collected a corpus of metadata from photographs published on Instagram between 2016 and 2018 in Biarritz, France, which we analyse following these two axes. Through this exploratory study, we will demonstrate that this data, though very rich, presents a certain number of limits, whether in terms of access to the data itself or its spatiotemporal precision.; La prolifération des traces géonumériques fait émerger diverses promesses et attentes pour l’étude des dynamiques territoriales, en particulier celles des villes touristiques. Ces traces permettraient d’observer les pratiques spatiales des visiteurs et pallieraient le manque d’informations sur ces dernières à l’échelle urbaine. Ainsi, de nombreuses études utilisent les données issues de réseaux sociaux pour étudier l’espace touristique selon différentes mailles géographiques. Ces études proposent plusieurs types de visualisations à partir de ces données, permettant ainsi de représenter et donner à voir un espace-temps touristique prétendument inédit : de la carte de chaleur au tableau de bord, les traces sont présentées traitées, agrégées, calculées, lissées. Toutes ces transformations sont souvent peu transparentes, résultant de boites noires algorithmiques qui ne permettent pas de comprendre précisément les méthodologies - souvent complexes, parfois approximatives - qui sont employées. Dès lors, la technicité et l’opacité de ces données rendent nécessaires le développement d’approches critiques qui permettent de déconstruire ces nouveaux registres de fabrique cartographique. A partir de données récoltées sur un réseau social très utilisé, Instagram, nous souhaitons questionner les traces géonumériques comme outil potentiel d’observation des pratiques touristiques, en remontant dans la généalogie des données : de la carte à la trace. Notre démarche consiste alors à revenir aux données initiales, les semis de points et les métadonnées associées, afin d’explorer trois dimensions fondamentales, conditions pré-requises à des explorations plus complexes : le temps, le lieu et l’individu. Pour cela, nous avons récolté un corpus de métadonnées de photographies publiées sur le réseau social Instagram entre 2016 et 2019 à Biarritz, que nous analysons à travers ces trois axes. A travers cette étude exploratoire, nous démontrons que ces données très riches présentent néanmoins un certain nombre de limites que ce soit dans l’accès aux données elles-mêmes, que dans leur précision spatio-temporelle ou dans la possibilité effective de caractériser les usagers.

International audience; The rise of digital footprints has created a number of promises and expectations for the study of territorial dynamics, particularly those of tourist cities. These footprints would make the observation of visitors' spatial practices possible and make up for the lack of information on these practices at an urban scale. Thus, many studies use data from social networks to study the touristic space at different geographical scales. These studies provide several types of visualisations based on this data, thus making it possible to represent and show a supposedly new touristic space-time-from the heat map to the dashboard, the digital footprints are displayed as processed, aggregated, calculated and smoothed. All these transformations-resulting from algorithmic black boxes that do not allow a precise understanding of the methodologies (often complex and approximate)-are often not very transparent. Consequently, the technicality and opacity of this data make necessary the development of critical approaches that allow the deconstruction of these new mapping registers. Based on data collected on a widely used social network, Instagram, we wish to question digital footprints as a potential tool to observe tourist practices, by going back through the data genealogy, from the map to the footprint. Our approach consists of going back to the initial data and their associated metadata, in order to explore two fundamental dimensions, conditions prerequisite for more complex explorations: time and space. Therefore, we collected a corpus of metadata from photographs published on Instagram between 2016 and 2018 in Biarritz, France, which we analyse following these two axes. Through this exploratory study, we will demonstrate that this data, though very rich, presents a certain number of limits, whether in terms of access to the data itself or its spatiotemporal precision.; La prolifération des traces géonumériques fait émerger diverses promesses et attentes pour l’étude des dynamiques territoriales, en particulier celles des villes touristiques. Ces traces permettraient d’observer les pratiques spatiales des visiteurs et pallieraient le manque d’informations sur ces dernières à l’échelle urbaine. Ainsi, de nombreuses études utilisent les données issues de réseaux sociaux pour étudier l’espace touristique selon différentes mailles géographiques. Ces études proposent plusieurs types de visualisations à partir de ces données, permettant ainsi de représenter et donner à voir un espace-temps touristique prétendument inédit : de la carte de chaleur au tableau de bord, les traces sont présentées traitées, agrégées, calculées, lissées. Toutes ces transformations sont souvent peu transparentes, résultant de boites noires algorithmiques qui ne permettent pas de comprendre précisément les méthodologies - souvent complexes, parfois approximatives - qui sont employées. Dès lors, la technicité et l’opacité de ces données rendent nécessaires le développement d’approches critiques qui permettent de déconstruire ces nouveaux registres de fabrique cartographique. A partir de données récoltées sur un réseau social très utilisé, Instagram, nous souhaitons questionner les traces géonumériques comme outil potentiel d’observation des pratiques touristiques, en remontant dans la généalogie des données : de la carte à la trace. Notre démarche consiste alors à revenir aux données initiales, les semis de points et les métadonnées associées, afin d’explorer trois dimensions fondamentales, conditions pré-requises à des explorations plus complexes : le temps, le lieu et l’individu. Pour cela, nous avons récolté un corpus de métadonnées de photographies publiées sur le réseau social Instagram entre 2016 et 2019 à Biarritz, que nous analysons à travers ces trois axes. A travers cette étude exploratoire, nous démontrons que ces données très riches présentent néanmoins un certain nombre de limites que ce soit dans l’accès aux données elles-mêmes, que dans leur précision spatio-temporelle ou dans la possibilité effective de caractériser les usagers.

The main objective of this paper is to introduce and summarise an exploratory study (Mayer, Stampfer, Strassnig & Zingerle, 2019) commissioned by the City of Vienna in 2018 to map activities for the creation of a new vision and framework for a city’s digital transformation strategy, and in particular to propose a programme and instruments for implementation at the crossroads of science and society. The Vienna City Administration aims to actively shape this strategy in line with the city’s humanistic tradition. Digital Humanism was developed as a guiding vision to offer alternatives to technocratic concepts of digitalisation. It aims to address many concerns, negative effects and challenges arising in transformative digitalisation processes such as accelerated monopolisation of data and services, complete transparency of people and their behaviour (not only direct users) and losing grounds in the creation of digital commons, while at the same time procedures of the private sector remain secret, social polarisation in social media is further fuelled, advertising tech is neglecting regulations, and surveillance by governments and notions of responsibility, objectivity or neutrality are increasingly delegated to automated decision-making processes. Our 2019 study aimed to lay ground on already existing initiatives countering these trends in Vienna. We explored, which subject areas and actors could support and enrich the concept of Digital Humanism in Vienna. To generate relevant insights for policy advice, we drew on interviews with experts and stakeholders and followed selected communities of practice to learn from key actors and to identify challenges and priorities. In the following we will fi rst outline the conceptual development of Digital Humanism as guiding principle for the digital transformation of Vienna, explain the methodological approach and fi nally summarise the results of the study. We identified many actors from research, business and civil society and mapped fi elds of action such as digital justice and netpolitics, data science, artifi cial intelligence, security and surveillance studies, and digital literacy to name but a few. These domains and their experts will co-shape the coming priorities for digital economy, education and work in the digital age, democracy and participation, data protection and security, cultural heritage, eHealth and (social) media and the public sphere.

Participation in democracy, in today’s digital and datafied society, requires the development of a series of transversal skills, which should be fostered in higher education (HE) through critically oriented pedagogies that interweave technical data skills and practices together with information and media literacies. If students are to navigate the turbulent waters of data and algorithms, then data literacies must be featured in academic development programmes, thereby enabling HE to lead in the development of approaches to understanding and analysing data, in order to foster reflection on how data are constructed and operationalised across societies, and provide opportunities to learn from the analysis of data from a range of sources. The key strategy proposed is to adopt the use of open data as open educational resources in the context of problem and research-based learning activities. This paper introduces a conceptual analysis including an integrative overview of relevant literature, to provide a landscape perspective to support the development of academic training and curriculum design programmes in HE to contribute to civic participation and to the promotion of social justice.

As the coronavirus pandemic continues apace in the United States, the dizzying amount of data being generated, analyzed and consumed about the virus has led to calls to proclaim this the first ‘data-driven pandemic’. But at the same time, it seems that this plethora of data has not meant a better grasp on the reality of the pandemic and its effects. Even as we have the potential to digitally track and trace nearly every single individual who has contracted the virus, we have no idea exactly how many people have had the virus, been hospitalized, or died because of it, largely due to a confluence of factors, particularly active obfuscation and mismanagement by public authorities and misinformation spread through social media and right-wing media channels. But beyond these dynamics, there also lies the less nefarious ways that the everyday, subjective practices of data collection, analysis and visualization have the potential to themselves (re)produce these very same dynamics where data is at once valorized and ignored, preeminent and completely useless. That is, the pandemic has revealed only the general inadequacy of our data infrastructures and assemblages to solving pressing social issues, but also the more general shift towards a ‘post-truth’ disposition in contemporary social life. But, as this paper argues, it would be a mistake to see the centrality of data as being somehow the opposite from the larger post-truth apparatus, as the two are instead fundamentally intertwined and co-produced.

Information systems increasingly shape our knowledge of crises such as disasters and climate change. While these tools improve our capacity to understand, prepare for, and mitigate such challenges, critical questions are being raised about how their design shapes public imagination of these problems and delimits potential solutions. Prior work in human-computer interaction (HCI) has pointed to art/science collaboration as one approach for helping to explore such questions. As an attempt to draw on this potential, our team designed and facilitated a 2-day "artathon" that brought together artists and scientists to create new works of art based on disaster and climate data. Reflecting on the artathon and its outcomes, we contribute two sets of findings. First, we articulate opportunities, suggested by the artwork, for expanding research and design in crisis informatics. Second, we offer suggestions for HCI researchers seeking to stage successful art/science collaborations or similar inter-disciplinary events.

This paper argues that data literacy today needs to go beyond the mere skills to use data. Instead, it suggests the concept of an extended critical big data literacy that places awareness and critical reflection of big data systems at its centre. The presented research findings give first insights into a wide variety of examples of online resources that foster such literacy. A qualitative multi-methods study with three points in time further investigated the views of citizens about the effects of these tools. Key findings are a positive effect particularly of interactive and accessible data literacy tools with appealing visualisations and constructive advice as well as highly insightful suggestions for future tools.

This paper offers a sketch of the complicated conflicts which arise—and metastasize seemingly daily—in the era of Big Data. Given the public’s ubiquitous-yet-ostensibly-voluntary data surrender, and industry’s ubiquitous-yet-ostensibly-anodyne collection of the same, inaction is not an option for any near-just society. By revisiting the philosophical basis for Panoptic apparatus (via Bentham and Foucault), sketching the tumultuous history of US contract law trying to protect the public from itself (from Lochner to Carpenter), and comparing existing industry codes for similarly-situated—read: terrifyingly invasive—fields (e.g., physicians, therapists, attorneys, accountants), the paper will provide a preliminary framework for identifying and confronting the galaxy of problems associated with data analytics.

This paper provides insight into the use of data tools in the American labor movement by analyzing the practices of staff employed by unions to organize alongside union members. We interviewed 23 field-level staff organizers about how they use data tools to evaluate membership. We find that organizers work around and outside of these tools to develop access to data for union members and calibrate data representations to meet local needs. Organizers mediate between local and central versions of the data, and draw on their contextual knowledge to challenge campaign strategy. We argue that networked data tools can compound field organizers' lack of discretion, making it more difficult for unions to assess and act on the will of union membership. We show how the use of networked data tools can lead to less accurate data, and discuss how bottom-up approaches to data gathering can support more accurate membership assessments.

Literature on activist archiving theorizes the power of recordkeeping to give voice to marginalised communities. However, missing from this archival literature are analyses about the political practice of preserving data as an act of grassroots resistance. Simultaneously, existing scholarly literature on grassroots data activism revolves around the creation of new statistical representations to challenge official ones. This literature has largely ignored what will happen to this data over the long-term, nor has it treated data archiving as an activist project in its own right. This theoretical article seeks to close the gap between literature on archival activism and literature on data activism, in hopes that both sets of research can draw productively from each other. There are clear affinities between activist archives and data activism: both address the failure by mainstream institutions to account for marginal voices, both have the power to make issues visible and legitimate within the public sphere, and both experiment with traditional forms of memory and statistical evidence. We believe that these two powerful forms of activity have much to learn from each other, particularly as the need to steward data over the long term will only grow.

There have been multiple calls for integrating topics related to fair- ness, accountability, transparency, ethics (FATE) and social justice into Data Science curricula, but little exploration of how this might work in practice. This paper presents the findings of a collabora- tive auto-ethnography (CAE) engaged in by a MSc Data Science teaching team based at University of Sheffield (UK) Information School where FATE/Critical Data Studies (CDS) topics have been a core part of the curriculum since 2015/16. In this paper, we adopt the CAE approach to reflect on our experiences of working at the intersection of disciplines, and our progress and future plans for integrating FATE/CDS into the curriculum. We identify a series of challenges for deeper FATE/CDS integration related to our own competencies and the wider socio-material context of Higher Edu- cation in the UK. We conclude with recommendations for ourselves and the wider FATE/CDS orientated Data Science community

This article investigates social inclusion from the perspective of smart mobility and transport, which are core aspects of smart city policy. More specifically, it discusses older people’s mobility practice in smart city environments as a phenomenon at the intersection of age, digital ICT and data. Drawing on mobility studies, communications and critical data studies the article uses the following questions to frame its analysis of inclusive smart transport services from the perspective of old and advanced age: How transport (and) mobility practices interact with mobile ICT use in smart cities? What do we know about the transport mobilities of older people? What do we know about the mobile media and ICT practices of older people? After introducing the concepts of smart city and smart mobility the article discusses these questions through literature review, secondary data, and examples from public transportation services in the city of London, one of Europe’s principal ‘smart’ cities. The analysis highlights age-bias in inherited transport system, gaps in available data about older people’s mobility practices and their media and ICT use, and opportunities for more inclusive (and sustainable) smart transport.

Im Bildungsbereich haben Prozesse der Datafizierung und Digitalisierung zu einem nachhaltigen Wandel von Staat und Verwaltung gefuhrt, der sich in der zunehmenden Bedeutung komplexer Informationssysteme und zentralisierter Infrastrukturen des Datenmanagements sowie in der wachsenden Nutzung von Daten fur Zwecke des Bildungsmonitorings zeigt. Trotz dieses allgemeinen Trends finden sich gerade im deutschen bildungsfoderalen Kontext ohne originare Zustandigkeit des Bundes gravierende Unterschiede zwischen den Bundeslandern. Gleichzeitig mangelt es nach wie vor an Transparenz, Partizipationsmoglichkeiten sowie Kompetenzen im Umgang mit Daten (Data Literacy).

In his keynote, Neil Selwyn not only acknowledged his role as ‘outsider’ to the field of learning analytics, but also intentionally assumed the role of “idiot”. In my commentary I assume that Selwyn’s embrace of being an idiot was more than just self-deprecating humour or a disclaimer aimed to prepare the audience for his provocations. In a Medieval carnival, the clown, fool or community idiot was crowned king, and for the duration of the carnival, could make fun of the royal household, blaspheme and provoke, all licenced by his or her role at that moment in time. Selwyn acknowledged that his own position was and continue to be informed by Critical Data Studies (CDS), an emerging research focus and discourse aimed at troubling much of current accepted and unquestioned assumptions and practices in the broader context of data science. I reflect and comment on Selwyn’s keynote by firstly mapping some of the key tenets of CDS, before addressing some aspects of the keynote and two aspect of his “learning analytics wish-list” namely “giving students control” and “seeing ethics in terms of power, not in terms of protection."

This editorial introduces a special section of the Journal of Learning Analytics, for which Neil Selwyn’s keynote address to LAK ’18 has been written up as an article, “What’s the problem with learning analytics?” His claims and arguments are engaged in commentaries from Alfred Essa, Rebecca Ferguson, Paul Prinsloo, and Carolyn Rosé, who provide diverse perspectives on Selwyn’s proposals and arguments, from applause to refutation. Reflecting on the debate, I note some of the tensions to be resolved for learning analytics and social science critiques to engage productively, observing that central to the debate is how we understand the role of abstraction in the analysis of data about teaching and learning, and hence the opportunities and risks this entails. &nbsp

Theoretical debates, research approaches and discursive regimes pertaining to the datafication of everyday life, data and living environments, and the quantified control of the future. Emphasis on the production of databased knowledge and the influence data have on the material and social world. Course presentations include: Week 1 - Introduction – Data Stories and Conceptualizing data? Week 2 - Facts & Data Week 3 - Indicators & Categorization Week 4 - Mapping Week 5 - Administrative and Survey Data Week 6 - Standards Week 7 - Big Data Week 8 - Probability and Risk Week 9 - Data Infrastructure Week 10 - Data Day 4.0 Week 11 - Assemblages, Genealogies and Dynamic Nominalism