4 Jul 2023 09:00 - 18:30 S2, Alison Richard Building


Data Ownership Workshop

Convened by Amira Moeding (Cambridge University), Jan Beuerbach (University of Leipzig), Birte de Gruisbourne (Paderborn University), Tobias Stadler (University of Oldenburg)

As more and more data are generated and collected by individuals and organisations, questions around data ownership and control are becoming increasingly urgent. Not only because the economic value of data as an asset drives current business models but also because legal, ethical, and societal implications of data practices raise questions on reliability, responsibility and relationality.

At the moment, one can see a tension play out between data that is accessible via the internet and hence can be scraped to build so-called ‘artificial intelligence’ applications or tools that are then often protected as intellectual property, data collected by states, and privatised data accumulated by private companies. The European Union filing a lawsuit against ChatGPT is just the latest instance of many legal battles and questions surrounding legitimate data ownership.

We want to illuminate this tension and consider the different forms of data ownership, privatisation and accumulation currently promoted by ‘Big Tech’ companies. By focusing on the questions of data ownership and governance, we hope also to open up questions on the practices of data production, evaluation, valorisation and use.

We draw on different theories and methods of critique to analyse current practices of data production and use, to gain a clear understanding of how data are privatised and accumulated as property, as well as dynamics of expropriation, subjectivation and colonialism that result from the idea often promoted by industry actors that there is ‘no data like more data’.

As we inquire into the ontologies of data and the new epistemological virtues established by so-called large models, we draw on methods of historical enquiry but also data literacy when reflecting on the criticisms against ‘Big Data’ often launched from feminist, post-colonial, or racialised perspectives towards more careful practices of data generation.

We hope to connect these methods more explicitly to critical theory perspectives on data generation as labour and the valorisation of data through industry practices. We welcome expressions of interest from scholars at any stage of their careers by June 30. Please include your name, affiliation, and area of research in the email and send to Amira (alam2@cam.ac.uk), Jan (jan.beuerbach@uni-leipzig.de), Birte (birte.de.gruisbourne@uni-paderborn.de) or Tobias (tobias.stadler@uni-oldenburg.de)

Supported by:



We would like to ground our discussion on a shared basis and suggest that you read the following texts in preparation. Please let us know if you cannot access any of the texts, please write to the organising team:

Key Readings

  • Viljoen, Salomé. “A Relational Theory of Data Governance.” Yale Law Journal 131 (2): 370–781. 2021. DOI:  10.2139/ssrn.3727562
  • von Redecker, Eva. “Ownership’s Shadow: Neoauthoritarianism as Defense of Phantom Possession.” Critical Times 3 (1): 33-67. 2022. DOI: 10.1215/26410478-8189849
  • Cecilia Rikap, ‘Same End By Different Means: Google, Amazon, Microsoft and Meta’s Strategies to Organize Their Frontier AI Innovation Systems’ pp. 1-6, 31- 42.
  • Cecilia Rikap, ‘Same End By Different Means: Google, Amazon, Microsoft and Meta’s Strategies to Organize Their Frontier AI Innovation Systems’ Short version
  • Cecilia Rikap, Capitalism as Usual? Implications of Digital Intellectual Monopolies. New Left Review, 139(Jan), pp. 145-160.

Additional Readings

  • Sadowski, Jathan. “When Data Is Capital: Datafication, Accumulation, and Extraction.” Big Data & Society 6 (1). 2019. DOI: 10.1177/2053951718820549
  • Gurumurthy, Anita, and Nandini Chami. “Beyond Data Bodies: New Directions for a Feminist Theory of Data Sovereignty.” 24. Bangalore: IT For Change. 2022. itforchange.net
  • Bender, Emily M. and Gebru, Timnit and McMillan-Major, Angelina and Shmitchell, Shmargaret. “On the Dangers of Stochastic Parrots: Can Language Models Be Too Big? 🦜” Proceedings of the 2021 ACM Conference on Fairness, Accountability, and Transparency: 610-623. 2021. DOI: 10.1145/3442188.3445922
  • Waldron, Jeremy: “Property and Ownership”, Stanford Encyclopedia of Philosophy https://plato.stanford.edu/entries/property/



Introductory Notes on the Interdisciplinary Research on Data Ownership
(15 Min)
Amira Moeding and Jan Beuerbach


Group Discussion 1: Mapping the field
(90 Min)
Chair Tobias Stadler


30 Minute Break


Keynote: The expanding intellectual monopoly power of Big Tech in the age of AI and Cloud computing
(90 Min)
Cecilia Rikap (City University London)



Lunch Break


Group Discussion 2: Appropriation & Accumulation
(90 Min)
Inputs and Chair: Jan Beuerbach & Amira Moeding




Slot 3: Production & Subjectivity
(90 Min)
Chair & Inputs: Birte de Gruisbourne & Tobias Stadler


Conclusion and Summary of the Discussions
Data Property/Ownership Research Group


Optional Dinner (paid for individually)

Cambridge Digital Humanities

Tel: +44 1223 766886
Email enquiries@crassh.cam.ac.uk