The Politics of Open Infrastructures - 4. Infrastructuring Openness

4. Infrastructuring Openness: Austrian Practices and Politics of Opening Up Government Data

Astrid Mager

©2026 Astrid Mager, CC BY 4.0 https://doi.org/10.11647/OBP.0528.04

Introduction

I’m sitting in a traditional Viennese coffee house, the Café Prückel. It is early May and bright sunlight falls into the large windows of the spacious, art nouveau café. I am waiting for my interview partner, who is one of the key figures in creating Austria’s data strategy. While preparing for the interview, I think how funny it is to talk about digital futures in a space that was built one hundred years ago, in a space where a wide range of newspapers is laid out and digital payment was introduced just recently. Time seems to stand still in this place. When my interview partner arrives, I am taken out of my thoughts and into the topic of our conversation: the datafication of governmental affairs. One of the first things my interviewee says is that we are meeting at a ‘revolutionary’ point in time since a new law has just been passed in Austria, the Freedom of Information law. When this law goes into force in September 2025, a long-standing feature of Austrian bureaucracy will be abandoned: ‘professional secrecy’ ( Amtsgeheimnis). The concept of professional secrecy goes back to the enlightened absolutism of the Habsburg monarchy (eighteenth century onwards) and was codified in 1925. While Austria had preserved a culture of secrecy in bureaucratic practices and procedures dating back to the time of the monarchy, the world of data has tremendously changed, and Austria’s bureaucracy is now expected to follow.

The Freedom of Information law requires the proactive sharing of data on the side of the state and the right to data access on the side of citizens—something that fundamentally challenges Austria’s bureaucratic tradition, bu... This statement points right to the heart of this chapter, the cultural, practical, and political dimensions of opening up government data in Austria—or the ‘infrastructuring of openness,’ as the title suggests, a reference to research that has conceptualised digital infrastructure as a process rather than an object (Karasti and Blomberg 2018; Musiani 2022; se... in this volume).

In our conversation, the policy maker defined three central steps in the actual implementation of Austria’s data strategy: 1) building data infrastructures, 2) increasing data use, and, most fundamentally, 3) establishing a new ‘ data culture,’ as he called it. How to practically achieve these goals, what challenges..., which provides non-personal data for free, 2) the Austrian Micro Data Center, which provides restricted access to sensitive administrative data for research purposes, and 3) the digital geoTwin of the city of Vienna, a 3D model of the city, intended to integrate different data sets in the future. While these data infrastructures fundamentally differ in terms of their degree of open-/closedness, data types, and access, as well as target groups, they all share the ambition to open up government data for secondary use—through initiatives such as creating open data applications, facilitating micro data research, or fostering data-driven city planning, as will be discussed in the following pages. To account for these differences, I speak of different ways of ‘opening up’ government data rather than open government data, which would exclude the Austrian Micro Data Center providing highly restricted access to government data. It would partly also exclude the digital geoTwin, which is a kind of hybrid on the continuum between open and restricted government data since there is one version of the geoTwin that is open to the public and one version that displays more sensitive data for internal use only.

This chapter proceeds by tracing the history of open government data approaches and positioning it within the wider context of the neoliberal ‘data welfare state’ (Dencik and Kaun 2020; Dencik 2022; Kaun and Masso 2025). After providing a brief overview of the three government data infrastructures, I dive into the multi-faceted practices and politics of infrastructure building, data sharing, and cross-organisational collaboration. To conclude, I will situate Austrian attempts at infrastructuring openness within contemporary trends of EU data policies, and discuss how to foster a more open, participatory, and collaborative data culture in the context of wider transformations of the data welfare state.

The Push Towards Open Government in the Data Welfare State

In the early 2000s, non-governmental actors started to pressure governments to pro-actively share non-sensitive data and make them freely available to use, reuse, and redistribute without any legal, technological, or social restrictions. 2 In this context, open government data were seen as central in generating a collaborative dialogue between policy makers and citizens ( Broomfield 2023). In 2009, Barack Obama pushed open government as a political agenda, with his open go... In the European Union, open government has been on the agenda for more than twenty years now, starting with its ‘eEurope’ action plans that included e-government (EC 2000). The willingness to open their governments, however, varies considerably between European member states because of cultural differences and divergent understandings of the role of government. Traditionally, Northern European countries are considered to be at the forefront of opening up government data for secondary use (Götz and Marklund 2015). Contrary to these ‘information-friendly’ democracies, the political culture of Austria has been described as ‘information-restrictive’ by Parycek and Schossböck (2015) since the flow of information between the authorities and citizens follows a ‘push principle,’ with the authorities controlling access and distribution of information—thus undermining free information as a basis for participation. Parycek and Schossböck (2015: 219) concluded that ‘the historical background with a longstanding culture of closure, state sovereignty, and the attributes of the Habsburg bureaucracy has played a signi...

Open government data have traditionally been linked to notions of openness, transparency, and accountability (Baack 2015; Schrock 2016; Redden 2018). In this context, citizens, often activists, are framed as active agents and co-producers of knowledge, policy action, and governmental activities (Baack 2015). Non-state actors such as civil society actors, journalists, programmers, hackers, but also start-ups and other innovators are seen as ‘ open government data intermediaries’ (Schrock and Shaffer 2017) that help to make use of open data by creating apps, infographics, dashboards, and the like. They have been described as central actors who increase ‘the utility of data, move it throughout a data ecosystem, and serve a democratizing function’ (Schrock and Shaffer 2017: 2). Critical research, however, has shown how open government data policies have been strategically used to continue the neoliberal form of state—the marketisation of public services and the privatisation of public assets, in particular (Bates 2014; see also Powell 2021: 83ff). Over the past decades, state institutions have been remodelled through new public management techniques to provide their services more efficiently while saving costs due to the pressure of resource scarcity. The datafication and automation of welfare services have been embraced as central tools to arrive at this goal—a trend that has been captured with the notion of the ‘data welfare state’ (Dencik and Kaun 2020; Dencik 2022; Kaun and Masso 2025). The data welfare state strongly relies on datafication, a ‘process whereby numbers are t...

Critical research has further shown that EU data policies increasingly conflate open government data with the reuse of public-sector information, the latter of which is rooted in the digital economy rather than citizen empowerment. Having analysed the EU’s Open Data Directive ( ODD), Broomfield (2023) argued that the two distinct concepts of open data and the reuse of public-sector information (PSI) have been ‘married’ in the directive despite their fundamentally different origins. The reuse of PSI is ‘firmly rooted in the realization of the European data economy, while open data is primarily anchored in ideas around government transparency and accountability as a way to facilitate citizen participation’ ( Broomfield 2023: 186). Broomfield (2023) concluded that principles of open data are somewhat integrated in the ODD, but that references to citizen participation tend to be reduced to acts of ‘window dressing.’ This confirms older research that discussed the process of opening up government information as fuelled by demands for both transparency and accountability and by the commercial reuse of data (Janssen and Hugelier 2013). It also corresponds to contemporary research that identifies a shift in Norwegian policy narratives from the rationale of efficiency and public sector data improving public administration towards the rationale of data-driven innovation, where ‘value creation and public sector data sharing with the private sector are central’ (Reutter and Åm 2024: 647). These rhetorical shifts may be seen as part of the EU’s aspirations to create a data-driven econom...

Opening Up Government Data in Austria

In 2012, the city of Vienna created a metadata portal for open government data (OGD), data.gv.at, in close collaboration with the open data movement. 4 The development, metadata standardisation, and governance of data.gv.at was organised through the open-ended Cooperation OGD Austria that involved the cities of Vienna, Linz, Salzburg, and Graz, along with the Open Knowledge Foundation Chapter Austria, the Danube-University Krems (Center of E-Governance) and the Open3.at association (Höchtl et... provides access to data, figures, documents, and services in formats that are machine-readable, open, and free of charge. As of June 2025, data.gv.at holds 57,728 data sets clustered in topics such as society, health, culture, government, finance, climate, and many more, and displays 750 applications of various sorts—including apps, maps, or infographics. Moreover, the city of Vienna is currently working on a digital geoTwin—a digital 3D model of the city—as a basic infrastructure for a ‘real’ digital twin that is intended to integrate heterogeneous data sets for simulating future city planning or climate-related scenarios (Lehner an..., partly for internal use only.

While the data.gv.at platform centralises metadata from public institutions at all levels (federal government, cities, municipalities) that is freely accessible, the Austrian Micro Data Center ( AMDC) 5 centralises administrative data only for accredited research institutions and for a relatively high fee. After the COVID-19 crisis—and after increased lobbying by researchers and the Plattform Registerforschung ( platfor... —a change of the Research Organization Act (Forschungsorganisationsgesetz) paved the way towards opening up statistical and administrative data for research purposes. To this end, the AMDC was created in 2022 to manage access to sensitive statistical and administrative data for research purposes as part of Statistics Austria. The AMDC holds pseudonymised microdata on individuals and firms from Statistics Austria and the Austrian federal government. Different microdata sets from Statistics Austria, administrative registers, and microdata brought in by researchers themselves can be linked via ‘unique pseudonymized identifiers’ (Fuchs et al. 2023)—an aspect that elicited a range of differing opinions from my interviewees.

To empirically examine the multi-faceted practices and politics of opening up government data in Austria, I conducted desk research, website analyses, and thirteen qualitative expert interviews (Bogner and Menz 2009) with stakeholders involved in building and governing the three data infrastructures. My interviewees... portal, the Open Commons Linz initiative, the AMDC, the Plattform Registerforschung, the digital geoTwin of Vienna, as well as policy makers, open data and digital rights activists, and researchers working with open and administrative data more generally. The interviews were conducted in 2023 and lasted between 45 and 120 minutes. They were transcribed and analysed with MAXQDA following a Grounded Theory approach (Glaser and Strauss 1968) that enabled me to code the material along the three research questions from top down, while allowing me to come up with new categories that emerged from the interviews, such as Austria’s ‘ data culture.’

Infrastructure Building and Data Work

Talking about the early days of data.gv.at, one of the founding members said that ‘community work’ was a central driver for opening up government data in Austria. This work included communal meta-standard setting, quality control, data care and repair, as well as practices of creating apps, infographics, and other digital services—often conducted by intermediaries for fre... Both the relational dimension of infrastructure building and the invisibility of the multi-faceted data work resonate with central findings from infrastructure studies ( Bowker and Star 2000). Zakharova and Jarke (2024: 5) speak of ‘ care work’ in the context of organisational practices, which is needed to build and maintain data infrastructures—‘ care work that sustains and enables the production, processing, circulation, and use of data.’

Besides the multi-layered ‘care work’ that is needed internally, there is a great deal of translational work done by actors outside of public administration. One illustrative example that was mentioned by multiple interviewees was a public transpo... portal, a city employee bemoaned that many industry actors would take open data to build their commercial apps without feeding them back to the portal, following business models that resemble acts of information commodification (Bates 2014). At the same time, companies hold valuable city data locked up in closed infrastructures. An open data activist therefore concluded that e-scooter companies, for example, should be pressured to share their data if they are allowed to provide their services in the city. Such quotes allude to the economic rationale undermining not only data policies, but also actual practices of opening up and aggregating data, as will be further discussed in the next section.

Practices of Data Aggregation

My interviewees agreed that the integration of different data sets adds value to government data. Just like the ‘assetization’ (Birch et al. 2021) of corporate data relies on the aggregation of large amounts of data, government data also benefit from being interlinked. A digital rights activist put it like this: ‘It is clear that we are heading towards a world where we’d like to make evidence-based statements about society on the basis of aggregated data. And it is one of the biggest tensions of our time, how to reconcile the protection of the individual and the benefits of large-scale data sets and aggregation.’ Alluding to the economic value of government data, the policy maker responsible for Austria’s data strategy said: ‘Then, in the light of the European data strategy, or considerations about the creation of the Digital Single Market, economic rationales increasingly came to the fore.‘ Referring to far-fetched plans to build European Data Spaces, he added that companies would increasingly realise that ‘hording data on its own’ is no longer wise, but that ‘market value lies in the sharing of data.’ The value of data, however, significantly grows when data are interlinked, especially when stemming from different ‘silos,’ as he put it. Accordingly, the aggregation of administrative data requires a high degree of protection in Austria.

Talking about the Austrian Micro Data Center, the digital rights activist explained the controversy that sparked around its introduction. The aggregation of citizen data from different sectors was considered a delicate endeavour that would need to follow strict safeguards since it sets aside one of the central principles of Austrian data protection: the strict segregation of citizen data into different ‘silos’ to prevent the state from gaining an ‘overall picture’ of the life of citizens. What constitutes strict safeguards was discussed in different ways, however. While the digital rights activist argued that more measures should have been taken to protect citizens, the representative of the AMDC explained that they followed strict procedures oriented towards data minimisation and ‘control work’ to avoid risks of re-identification (Fuchs et al. 2023). She said the AMDC is aware that giving out one or two more individual variables to researchers could be enough to re-identify people, or institutions, even though each data set was properly pseudonymised. They thus assess with care each project proposal, the data sets required, and the scientific output that is created on the basis of micro data—creating a huge bureaucratic process and requiring a whole range of new data work, skills, and resources.

Furthermore, commercial interests are at stake considering the high value of micro data. The issue centres around the question of accreditation and what constitutes a research institution in the first place—for example, pharmaceutical companies do research too, but are excluded from access to micro data at present. All these examples show the differing ways that the aggregation of administrative data has been discussed and how it involves essential and sometimes competing values. To master such balancing acts in the public interest, collaboration has been demanded by my interviewees.

Call for Collaboration

The call for collaboration was expressed as a response to the deep concerns involved in data sharing that were described as being rooted in Austria’s culture of secrecy. Talking about the organisational implementation of the data strategy, the policy maker framed the Austrian situation as follows: ‘So far, the Austrian viewpoint was strongly characterised by... platform referred to the culture of ‘professional secrecy’ when talking about the early days of the platform: ‘Well, the idea of openness was not in our DNA at all, right?’ An open data activist labelled the Austrian data culture as an ‘imperial and royal [kaiserlich und königlich] culture of administration’, a reference to the highly stratified and bureaucratic culture of the former monarchy. This comment corresponds to what Parycek and Schossböck (2015) framed as a ‘longstanding culture of closure, state sovereignty, and the attributes of the Habsburg bureaucracy.’

Moreover, my interviewees described a deep anxiety among public institutions that mistakes, misconduct, or other misbehaviour would come out if they opened up and allowed people to peek into their inner workings. Talking about the elevator app for disabled citizens, the open data activist said that Viennese public transport was initially against sharing its real-time data since they were afraid that ‘the political counterpart’ would use it as ‘ammunition’ to damage them if the app showed that many elevators did not work. Only when it turned out that the opposite was the case—that the elevators worked comparably well in Austria—did Viennese public transport see the gain of sharing their data. The Open Commons Linz representative summarised these deep anxieties like this: ‘Will the shitstorm hit us? Those are the fears.’ A potential loss of ‘ sovereignty’ over political decision-making was additionally mentioned as a perceived obstacle to opening up government data—the flipside of transparency.

Talking about the building of complex, distributed data infrastructures, a city employee working on the digital geoTwin expressed a strong desire for collaboration—both on the technical and the organisational side. In addition to communication between public bodies, responsibility for data was raised as a critical issue. While the responsibility for single data sets would stay with the respective departments, the city employee said, the responsibility for data integration—and the added value it creates—was up for debate. Another interviewee involved in the digital geoTwin referred to the coordination work that would be needed to build such a distributed data infrastructure as crucial and concluded by saying: ‘It is a topic where everyone needs to collaborate. It is a topic of communication and organisation. And we cannot pass it on to one individual.’ This illustrates that public infrastructures, just like research infrastructures, need to be negotiated among different actors, backgrounds, and across sites (Star 1999; Karasti et al. 2010). Sometimes this negotiation can have high political stakes. If a digital twin visually displays detailed information about tunnels, water pipes, or the Viennese underground, it could become a matter of national security if such information is (mis)used for a terrorist attack. As the city employee concluded, ‘Well, sometimes there is a conflict of interest between transparency and security.’ To balance such delicate conflicts of interest, collaboration and stakeholder-engagement were suggested by my interview partners.

Contrary to government employees, who were reluctant to share data, the digital rights activist emphasised the positive effects collaboration could create: ‘I think that public institutions would benefit from each other if they were more transparent, if they would know what others do. Because you don’t have to invent everything on your own, you can learn from each other.’ The cultural shift that would be required for this to happen, according to the policy maker, includes a ‘fundamental rethinking in the public sector altogether, that you don’t think about yourself, your own data silo, but rather: ‘How can I make my data useful for someone else?’ In the next and final section, I will address the question of how to foster more collaborative ways of opening up data, building infrastructures, and governing datafication in public sectors.

Conclusions

In this chapter, I have discussed practices and politics of opening up government data in the Austrian context by focusing on three government data infrastructures: the open government data portal data.gv.at, the Austrian Micro Data Center, and the digital twin infrastructure of the city of Vienna. I have traced what a shift from professional secrecy towards a more open ‘ data culture’ entails in practice, as the policy maker put it at Café Prückel. But what can we learn from Austrian attempts at infrastructuring openness in light of recent EU data policies and wider transformations of the ‘data welfare state’ (Dencik and Kaun 2020; Dencik 2022; Kaun and Masso 2025)?

Datafication of public administration, among other sectors, has become a central component of the European Data Strategy. Recent EU policy documents such as the Open Data Directive, the Data Governance Act, or the Data A... European Data Spaces are imagined in areas like health or finance, where sensitive data are supposed to be shared between different stakeholders, countries, and contexts (EU REG 2022). While data is expected to ‘flow freely’ in EU policy, my research has pointed to the multi-faceted practices of infrastructure building, data work, and the intermediaries that are needed to make data flow. This resonates with research that has deconstructed notions of data as a mere ‘by-product’ of organisational practices that could simply be ‘harvested’ (Jarke and Büchner 2024). Moreover, crucial tensions and ambivalences arise when implementing EU data policies into national data cultures, institutional contexts, and bureaucratic routines.

Austrian bureaucracy has its roots in the Habsburg monarchy, inheriting a tradition with secrecy at its core rather than transparency. Historic experiences of national socialism further contributed to Austria’s strong stance towards data protection, which is encoded in strict data protection policies and rules (Mager 2017). In this cultural context, calls for opening up sensitive personal data would need to be met with strict safeguards to protect citizens (and institutions) from surveillance and discrimination that may result from re-identification, according to digital rights experts. Kaun and Masso (2025: 28) speak of the ‘ openness paradox’ to describe the tensions between the push for open government data and the imperative to safeguard data due to privacy concerns and other risks. Moreover, the benefits of opening up government data were seen to be balanced with economic rationales of ab/using data for profit maximisation. This relates to broader tensions running through EU technology politics, which is torn between Normative Power Europe and Market Power Europe (Ulnicane 2021). It further relates to strategic uses of open government data to foster neoliberal principles such as the privatisation of public assets or the marketisation of public services (Bates 2014), if we consider larger trends in the data welfare state (Dencik and Kaun 2020; Dencik 2022; Kaun and Masso 2025).

To master the complex balancing acts between the different actors, interests, and values at stake, my research participants have suggested participatory stakeholder processes. Collaborative efforts and transdisciplinary expertise may help to sensitively implement Austria’s data strategy in organisational practices and find ways to carefully govern data in distributed infrastructures. This could facilitate mutual learning across contexts, but also across countries, while still considering local specificities and ‘situated ethics’ (Mager et al. 2025). Nordic countries, for example, have been framed as transparent and ‘information friendly’ in the past (Parycek and Schossböck 2015), but have experienced severe scandals emerging from datafication and automation in public sectors more recently. Just think of the Dutch childcare benefits scandal, where the risk scoring algorithm used to detect welfare fraud showed serious effects of algorithmic bias and discrimination. Amnesty International labelled the software a ‘xenophobic machine’ because it particularly discriminated against migrant families and other socially vulnerable groups ( Amnesty International 2021). Despite this criticism, a similar fraud detection algorithm has been introduced in Denmark just recently and showed similar effects of ‘coded injustice’ ( Amnesty International 2024), confirming research on algorithmic discrimination of (semi)- automated decision-making tools in public administration (Dubois et al. 2018; Allhutter et al. 2021). Sharing and broadening experiences and expertise would help stakeholders to c...

Moreover, new concepts for thinking and governing data could make it possible to meet challenges posed by the increasing aggregation of government data. Prainsack et al. (2022) suggest a solidarity-based data governance framework that builds on three pillars: 1) facilitating data use that creates significant public value, 2) harm prevention and harm mitigation, and 3) sh... arguing that the most important distinction is to be made ‘between data use that generates significant public value without posing unacceptable risks to anyone and data use that does the opposite’ (Prainsack et al. 2022: 7). The concept of data solidarity may thus serve as a guiding principle for opening up government data in the public interest. It may help to strengthen initial ideas built into open government strategies that are increasingly under threat in EU data policies that use the notion of open data as an act of ‘window dressing’ while fostering the economic rationale of the data economy, as discussed earlier. Rather than undermining public sectors with neoliberal logics by way of datafication, public administration could start thinking about how to share and govern data in a more responsible way, compared to Big Tech companies with their strategies of ‘assetization’ (Birch et al. 2021). As the digital rights activist concluded, ‘now we have the chance to lay down the tracks and define the foundational orientation that will shape our digital future in the long-term.’

Funding and Acknowledgments

This research was carried out as part of the project Automating Welfare—Algorithmic Infrastructures for Human Flourishing in Europe (project coordinator Anne Kaun, project number: CHANSE-546). Thanks to all Auto-Welf collaborators, participants of the Big Data Discourses conference in Leipzig (2024), and the Austrian Auto-Welf team, Doris Allhutter and Rafaela Cavalcanti de Alcântara, for valuable discussions on datafication and public value creation in European welfare states. Moreover, I would like to thank Fabian Fischer and Barbara Prainsack for helpful comments on an earlier version of the chapter and Mike Holohan for editing the English. The open access contributions for this chapter were funded by the Open-Access Fund of the Austrian Academy of Sciences (ÖAW) and the Institute of Technology Assessment (ÖAW). The licence of this chapter is CC-BY.

References

Allhutter, Doris, Florian Cech, Fabian Fischer, Gabriel Grill, and Astrid Mager. 2020. ‘Algorithmic Profiling of Job Seekers in Austria: How Austerity Politics Are Made Effective.’ *Frontiers in**Big Data* 3. https://www.frontiersin.org/journals/big-data/articles/10.3389/fdata.2020.00005/full

Amnesty International. 2021. Xenophobic Machines:Discrimination through Unregulated Use of Algorithms in the Dutch ChildcareBenefits Scandal. London: Amnesty International. https://www.amnesty.org/en/documents/eur35/4686/2021/en/

Amnesty International. 2024. *Coded Injustice: Surveillance and**Discrimination in Denmark’s Automated Welfare State*. London: Amnesty International. https://www.amnesty.org/en/documents/eur18/8709/2024/en/

Andreassen, Rikke, Anne Kaun, and Kaarina Nikunen. 2021. ‘Fostering the Data Welfare State: A Nordic Perspective on Datafication.’ Nordicom Review 42 (2): 207–223. https://doi.org/10.2478/nor-2021-0051

Baack, Stefan. 2015. ‘Datafication and Empowerment: How the Open Data Movement Re-articulates Notions of Democracy, Participation, and Journalism.’ Big Data & Society 2 (2). https://doi.org/10.1177/2053951715594634

Bates, Joe. 2014. ‘The Strategic Importance of Information Policy for the Contemporary Neoliberal State: The Case of Open Government Data in the United Kingdom.’ *Government**Information Quarterly* 31: 388–395.

Birch, Kean, D. T. Cochrane, and Callum Ward. 2021. ‘Data as Asset? The Measurement, Governance, and Valuation of Digital Personal Data by Big Tech.’ *Big Data**& Society* 8 (1). https://doi.org/10.1177/20539517211017308

Bogner, Alexander, and Wolfgang Menz. 2009. ‘The Theory-Generating Expert Interview: Epistemological Interests, Forms of Knowledge, Interaction.’ In Interviewing Experts, edited by Alexander Bogner, Beate Littig, and Wolfgang Menz, 43–50. Basingstoke: Palgrave Macmillan.

Bowker, Geoffrey C., and Susan Leigh Star. 2000. *Sorting Things**Out. Classification and Its Consequences*. Massachusetts, MA: The MIT Press.

Broomfield, Heather. 2023. ‘Where is Open Data in the Open Data Directive?’ Information Polity 28 (2): 175–188. https://doi.org/10.3233/IP-220053

Dencik, Linda. 2022. ‘The Datafied Welfare State: A Perspective from the UK.’ In *New Perspectives in Critical**Data Studies*, edited by Andreas Hepp, Juliane Jarke, and Leif Kramp, 145–165. Cham: Springer International Publishing.

Dencik, Linda, and Anne Kaun. 2020. ‘Datafication and the Welfare State.’ Global Perspectives 1 (1): 12912. https://doi.org/10.1525/gp.2020.12912

Dove, Graham, Jack Shanley, Camillia Matuk, and Oded Nov. 2023. ‘Open Data Intermediaries: Motivations, Barriers and Facilitators to Engagement.’ *Proceedings of the**ACM on Human-Computer Interaction* 7 (CSCW1) (78): 1–28. https://doi.org/10.1145/3579511

Dubois, Vincent, Morgane Paris, and Pierre-Edouard Weill. 2018. ‘Targeting by Numbers. The Uses of Statistics for Monitoring French Welfare Benefit Recipients.’ In Creating *Target Publics for**Welfare Policies. Logic, Argumentation, and Reasoning 17,*edited byLorenzoBarrault-Stella and Pierre-Edouard Weill, 93–109. Berlin: Springer.

European Commission. 2000. eEurope 2002: An Information Society for All. Brussels, 14.06.2000, COM 330 final.

European Regulation. 2022. *Data Governance**Act.*Brussels, 30.5.2022, REG. https://eur-lex.europa.eu/legal-content/EN/TXT/?uri=CELEX%3A32022R0868

Fuchs, Regina, Tobias Göllner, Simon Hartmann, and Tobias Thomas. 2023. ‘Fostering Excellent Research by the Austrian Micro Data Center (AMDC).’ *Jahrbücher für Nationalökonomie und**Statistik* 244 (4): 433–445.

Glaser, Barney G., and Anselm L. Strauss. 1968. *The Discovery of Grounded Theory: Strategies for Qualitative**Research*. Weidenfeld & Nicolson.

Götz, Norbert and Carl Marklund. 2015. TheParadox of Openness. Transparency and Participation in Nordic Cultures ofConsensus. Leiden: Brill.

Höchtl, Johann, Peter Parycek, and F. Sedy. 2014. ‘The Development of Open Government Data in Austria.’ In *Handbook of Research on Advanced ICT Integration for Governance and**Policy Modeling*, edited by Peter Sonntagbauer, Kawa Nazemi, Susanne Sonntagbauer, et al., 19–27. Hershey, PA: Information Science Reference.

Janssen, Katleen, and Sarah Hugelier. 2013. ‘Open Data as the Standard for Europe? A Critical Analysis of the European Commission’s Proposal to Amend the PSI Directive.’ *European Journal of Law and**Technology* 4(3).

Jarke, Juliane, and Stefanie Büchner. 2024. ‘Who Cares about Data? Data Care Arrangements in Everyday Organisational Practice.’ *Information,**Communication & Society* 27(4): 702–718. https://doi.org/10.1080/1369118X.2024.2320917

Karasti, Helena, Karen S. Baker, and Florence Millerand. 2010. ‘Infrastructure Time: Long-term Matters in Collaborative Development.’ Computer Supported Cooperative Work, 19: 377–415.

Karasti, Helena, and Jeanette Blomberg. 2018. ‘Studying Infrastructuring Ethnographically.’ Computer Supported Cooperative Work 27: 233–265.

Kaun, Anne, and Anu Masso. 2025. The Data Welfare State. London: SAGE.

Lehner, Hubert, and Lionel Dorffner. 2020. ‘Digital geoTwin Vienna: Towards a Digital Twin City as Geodata Hub.’ *Journal of Photogrammetry, Remote**Sensing and Geoinformation Science* 88 (1):  63–75.

Madianou, Mirca. 2020. ‘A Second-order disaster? Digital Technologies during the COVID-19 Pandemic.’ Social Media & Society 6 (3): 1–5. https://doi.org/10.1177/2056305120948168

Mager, Astrid. 2017. ‘Search Engine Imaginary: Visions and Values in the Co-production of Search Technology and Europe.’ *Social**Studies of Science* 47 (2): 240–262. https://doi.org/10.1177/0306312716671433

Mager, Astrid, Magdalena Eitenberger, Jana Winter, Barbara Prainsack, Christiane Wendehorst, and Payal Arora. 2025. ‘Situated Ethics: Ethical Accountability of Local Perspectives in Global AI Ethics.’ Media, Culture & Society 47(5): 1028–1041. https://doi.org/10.1177/01634437251328200

Mettler, Tobias, and Gianluca Miscione. 2022. ‘Is Altruism Dead? A Critical Case Study on the Paradigm Shift in Open Government Data.’ Information Polity 28 (1): 1–20. https://doi.org/10.3233/IP-220048

Milan, Stefania. 2020. ‘Techno-solutionism and the Standard Human in the Making of the COVID-19 Pandemic.’ Big Data & Society 7 (2): 1–7. https://doi.org/10.1177/2053951720966781

Musiani, Francesca. 2022. ‘Infrastructuring Digital Sovereignty: A Research Agenda for an Infrastructure-based Sociology of Digital Self-determination Practices.’ Information, Communication & Society 25(6): 785–800. https://doi.org/10.1080/1369118X.2022.2049850

Parycek, Peter, and Judith Schossböck. 2015. ‘Adopting a New Political Culture: Obstacles and Opportunities for Open Government in Austria.’ In *The Paradox of Openness. Transparency and Participation**in Nordic Cultures of Consensus*, edited by Norbert Götz and Carl Marklund, 210–236. Leiden: Brill.

Pelizza, Annalisa. 2020. ‘No Disease for the Others: How Covid-19 Data Can Enact New and Old Alterities.’ Big Data & Society 7 (2): 1–7. https://doi.org/10.1177/2053951720942542

Powell, Alison B. 2021. *Undoing Optimization. Civic**Action in Smart Cities*. New Haven, CT: Yale University Press.

Prainsack, Barbara, and Ilona Kickbusch. 2024. *Data Solidarity Glossary. Geneva:**Digital Transformations for Health Lab*. https://dthlab.org/data-solidarity-glossary/

Prainsack, Barbara, Seliem El-Sayed, Nikolaus Forgó, Lukasz Szoszkiewicz, and Philipp Baumer. 2022. White Paper Data Solidarity. https://www.governinghealthfutures2030.org/wp-content/uploads/2022/12/DataSolidarity.pdf

Reutter, Lisa, and Heidrun Åm. 2024. ‘Constructing the Data Economy: Tracing Expectations of Value Creation in Policy Documents.’ Critical Policy Studies 18 (4): 639–659. https://doi.org/10.1080/19460171.2023.2300436

Schäfer, Mirko Tobias, Karin van Es, and Tracey P. Lauriault. 2024. *Collaborative Research in**the Datafied Society: Methods and Practices for Investigation and Intervention*. Amsterdam: Amsterdam University Press.

Schrock, Andrew, and Gwen Shaffer. 2017. ‘Data Ideologies of an Interested Public: A Study of Grassroots Open Government Data Intermediaries.’ Big Data & Society 4(1). https://doi.org/10.1177/2053951717690750

Star, Susan Leigh. 1999. ‘The Ethnography of Infrastructure.’ American Behavioral Scientist 43 (3): 377–391.

Sztandar-Sztanderska, Karolina, and Marianna Zieleńska M. 2018. ‘Changing Social Citizenship through Information Technology.’ Social Work & Society 16 (2).

Twizeyimana, Jean Damascene, and Annika Andersson. 2019. ‘The Public Value of E-Government—A Literature Review.’ Government Information Quarterly 36 (2): 167–178.

Ulnicane, Inga. 2021. ‘Artificial Intelligence in the European Union. Policy, Ethics and Regulation.’ In The Routledge Handbook of European Integrations, edited by Thomas Hoerber, Gabriel Weber, and Ignazio Cabras, 254–269. London and New York: Routledge. https://doi.org/10.4324/9780429262081-19

Van Dijck, José. 2014. ‘Datafication, Dataism and Dataveillance: Big Data between Scientific Paradigm and Ideology.’ Surveillance & Society 12 (2): 197–208.

Zakharova, Irina, and Juliane Jarke. 2024. ‘Care-ful Data Studies: Or, What Do We See, When We Look at Datafied Societies through the Lens of Care?’ Information, Communication & Society 27 (4): 651–664. https://doi.org/10.1080/1369118X.2024.2316758