Data Cooperatives in Europe: A Legal and Empirical Investigation

The paper ”Data Cooperatives in Europe: A Legal and Empirical Investigation” (Mannan, M., Bietti, E., Etxeberria, A., Wong, J.) will be presented at the 11th FSR Annual Conference “From Data Spaces to Data Governance” (9-10 June, 2022).


In recent years, critics have argued that the General Data Protection Regulation [GDPR] has further institutionalized ‘Big Tech’ and undermined small players in the EU. This concerns include the outsized control of US multinational corporations over European citizens’ data and the need to incentivize the creation of neutral data intermediaries and alternative business models that prioritize commoning and altruism. Existing EU ‘data cooperatives’ (e.g., polypoly, have been formed to meet some of these concerns. Without support, these and other data cooperatives will struggle to achieve mainstream adoption. The potential and success of these organizations thus depends on the evolution of EU legal and policy frameworks.

This paper discusses the possible impact, benefits, and limitations of two EU legislative proposals introduced in late 2020 – the Data Governance Act [DGA] and the Digital Markets Act [DMA] – for data cooperatives. The DMA is addressed to providers of core platform services and lays down rules to ensure “contestable and fair markets in the digital sector across the Union”. It prohibits practices that “limit contestability” or “are unfair,” such as the combination of a gatekeeper’s data with third party data or discriminating in the gatekeeper’s marketplace. The DGA enables greater access and use of data for novel commercial and altruistic ends. It explicitly recognizes the role of data cooperatives in helping user-members make informed choices about consenting to data use and/or in negotiating with third parties about the terms and conditions under which member data can be processed. The DGA also introduces the concept of ‘data altruism’, a procedure for registering as ‘Data Altruism Organisations’, and more. If enacted, these proposals will redefine digital competition in Europe and may enable new coop-based models to flourish, but they could also present unforeseen obstacles to these nascent organisations, a concern that we explore herein.

Research Design and Expected Results:

For this paper, we combined desk-based research, with findings from interviews with existing cooperatives operating within the EU. This allowed us to better understand the opportunities and challenges they currently face, as well as their views (if any) on the proposed legislation. We were keen to understand the obstacles they have faced (including during the COVID-19 pandemic), the advantages that these frameworks offer, and its limitations. For these interviews, data cooperatives from different fields and countries were chosen with the aim of getting a more accurate vision of how these legal frameworks affect them. Among other things, our interviews reveal that data cooperatives have a keen interest in collaboration with public institutions but tend to be under-resourced and under-represented in policy discussions. Our interview findings, along with scholarship on cooperatives, inform our analyses and allow us to both make recommendations to EU policymakers as well as share practical insight for creating sustainable business models with other emerging data co-ops. By synthesizing the existing activities of co-ops and the proposals crafted by policymakers, we aim to start a constructive public-private dialogue to foster a more collaborative data ecosystem in Europe.

Our paper is structured as follows. After an introduction setting out our goals, research scope, and methodology, in Part II we discuss the nature of data and how data cooperatives fit within the cooperative landscape in Europe. We explain the purpose and different models that data cooperatives follow in the EU. In Part III, we then outline the GDPR, the DMA and DGA are relevant to the data cooperative ecosystem and assess how these changes interact with co-operative and data organisation models. Finally, in Part IV, we summarize some of our results and some future directions for policy and research, before concluding.


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