Emerging models of data governance in the age of datafication
Open accessAbstract
The article examines four models of data governance emerging in the current platform society. While major attention is currently given to the dominant model of corporate platforms collecting and economically exploiting massive amounts of personal data, other actors, such as small businesses, public bodies and civic society, take also part in data governance. The article sheds light on four models emerging from the practices of these actors: data sharing pools, data cooperatives, public data trusts and personal data sovereignty. We propose a social science-informed conceptualisation of data governance. Drawing from the notion of data infrastructure we identify the models as a function of the stakeholders’ roles, their interrelationships, articulations of value, and governance principles. Addressing the politics of data, we considered the actors’ competitive struggles for governing data. This conceptualisation brings to the forefront the power relations and multifaceted economic and social interactions within data governance models emerging in an environment mainly dominated by corporate actors. These models highlight that civic society and public bodies are key actors for democratising data governance and redistributing value produced through data. Through the discussion of the models, their underpinning principles and limitations, the article wishes to inform future investigations of socio-technical imaginaries for the governance of data, particularly now that the policy deba…
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Data governance actors operate at different levels of power relations that produce asymmetric control.
“These actors operate at different levels of power relations that produce asymmetric control (Micheli et al., 2020).”
From Toward a trustworthy and inclusive data governance policy for the use of artificial intelligence in Africa (2024) · cites this paper as Micheli et al., 2020
There is as yet no peer-reviewed typology that takes the commons as the organizing principle, applies it across the full AI stack of data, compute, models, knowledge, and energy in the foundation-model era, and uses Ostrom's design principles as its comparative axes.
“The gap this article fills sits at the intersection: there is as yet no peer-reviewed typology that takes the commons as the organizing principle, applies it across the full AI stack of data, compute, models, knowledge, and energy in the foundation-model era, and uses Ostrom's design principles as its comparative axes.”
From Commons-Governed Artificial Intelligence: A Taxonomy of Collective Governance (2026) · cites this paper as Micheli et al. (2020)
The four emerging models of Micheli et al. (2020) (data-sharing pools, data cooperatives, public data trusts, personal data sovereignty) are classified by who holds power and to whose benefit data flows, not by commons-governance mechanism, and do not treat model or compute governance as objects in their own right.
“Its proximate taxonomy, the four emerging models of Micheli et al. (2020), namely data-sharing pools, data cooperatives, public data trusts, and personal data sovereignty, is classified by who holds power and to whose benefit data flows, not by commons-governance mechanism, and it does not treat model or compute governance as objects in their own right.”
From Commons-Governed Artificial Intelligence: A Taxonomy of Collective Governance (2026) · cites this paper as Micheli et al. (2020)
Micheli et al. (2020) identify four emerging models of data governance: data-sharing pools, data cooperatives, public data trusts, and personal data sovereignty, classified by who holds power and to whose benefit data flows.
“The closest prior taxonomy of the layer is that of Micheli et al. (2020), who identify four emerging models of data governance, data-sharing pools, data cooperatives, public data trusts, and personal data sovereignty, classified by who holds power and to whose benefit data flows.”
From Commons-Governed Artificial Intelligence: A Taxonomy of Collective Governance (2026) · cites this paper as Micheli et al., 2020
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“…of data governance in current ‘platform society’ is the one established by a few corporate big tech platforms (Srnicek, 2017; Van Dijck et al., 2018; Zuboff, 2015), but other actors beyond ‘big tech’ are progressively becoming involved in controlling personal data and producing value from it…”
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Towards transparency by design for artificial intelligence
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“These actors operate at different levels of power relations that produce asymmetric control (Micheli et al., 2020).”
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“…and climate risk, urban planning, supply chain risk, disaster management, public health, and, more recently, data governance (Ahlqvist et al., 2020; Taebi et al., 2020; Di Guilio, 2023; Hanssen et al., 2018; McHugh et al., 2021; Micheli et al., 2020; Renn, 2015; Renn and Klinke, 2016).”
Commons-Governed Artificial Intelligence: A Taxonomy of Collective Governance
Garrido-Merchán, E. C. (2026) · arXiv · doi:10.48550/arxiv.2606.15466
“The closest prior taxonomy of the layer is that of Micheli et al. (2020), who identify four emerging models of data governance, data-sharing pools, data cooperatives, public data trusts, and personal data sovereignty, classified by who holds power and to whose benefit data flows.”
- Authors
- Micheli, M., Ponti, M., Craglia, M., & Berti Suman, A.
- Affiliations
- European Commission (BE)
- University of Gothenburg (SE)
- The Tilburg Institute for Law, Technology, and Society (TILT), Tilburg University, and the Joint Research Centre, European Commission, Varese, Italy
- Corresponding author
- Micheli, Marina
- Venue
- Big Data & Society
- Publisher
- SAGE Publications
- Published
- 2020-07
- Volume
- 7
- Issue
- 2
- ISSN
- 2053-9517 (ISSN-L)
- OpenAlex
- W3082258125
- Cited by
- 332
- References
- 6
- Citations by year
- 2026: 49 · 2025: 70 · 2024: 53 · 2023: 65 · 2022: 53 · 2021: 35 · 2020: 5 · 2019: 2
- FWCI
- 53.76
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- Big Data & Society (publishedVersion, cc-by-nc)
- Research portal (Tilburg University) (publishedVersion, cc-by-nc)
- Data Archiving and Networked Services (DANS) (submittedVersion, cc-by-nc)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Joint Research Centre (European Commission) (submittedVersion, cc-by-nc)
- Funders
- European Commission
- Nederlandse Organisatie voor Wetenschappelijk Onderzoek (019.193SG.007)
- Topics
- Social Sciences › Safety Research › Ethics and Social Impacts of AI
- Social Sciences › Law › Digitalization, Law, and Regulation
- Social Sciences › Decision Sciences › Information Systems and Management › Technology's Impact on Media
- Keywords
- data governance, datafication, platform society, data cooperatives, data infrastructure, data politics, value redistribution, power relations, sociotechnical imaginaries, civil society, public bodies, small business
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