LeADS Working Paper Series Part VI: Data Collaboratives with the Use of Decentralised Learning – an Interdisciplinary Perspective on Data Governance

Maciej Zuziak (ESR 6), Onntje Hinrichs (ESR 13), and Aizhan Abdrasulova (ESR 12) are the authors of the paper “Data Collaboratives with the Use of Decentralised Learning – an Interdisciplinary Perspective on Data Governance”. The paper constitutes a collaboration across three different  LeADS Crossroads, i. e. Privacy vs Intellectual Property (Onntje) Data ownership (Aizhan) and Empowering Individuals (Maciej) as well as across disciplines: whereas Onntje and Aizhan focused their research on questions related to data ownership and how conflicted interests in data can be resolved, Maciej is examining various methods of distributed learning.

Their different research interests came together in this paper which exemplified that an interdisciplinary perspective from both law and data science is necessary to tackle urgent questions in the data-dependent economy. Finding appropriate Data Governance solutions that are capable of achieving data policy objectives while at the same time being compliant with EU law requires an interdisciplinary understanding of how both disciplines can complement each other. Their Working Paper cooperation thus perfectly exemplifies the LeADS approach. The paper was presented at this year’s ACM Conference on Fairness, Accountability, and Transparency (FAccT) in Chicago.

 

Abstract of the Working Paper

The endeavor to find appropriate data governance frameworks capable of reconciling conflicting interests in data has dramatically gained importance across disciplines and has been discussed among legal scholars, computer scientists as well as policy-makers alike. The predominant part of the current discussion is centered around the challenging task of creating a data governance framework where data is ‘as open as possible and as closed as necessary’. In this article, we elaborate on modern approaches to data governance and their limitations. It analyses how propositions evolved from property rights in data towards the creation of data access and data sharing obligations and how the corresponding debates reflect the difficulty of developing approaches that reconcile seemingly opposite objectives – such as giving individuals and businesses more control over ‘their’ data while at the same time ensuring its availability to different stakeholders. Furthermore, we propose a wider acknowledgement of data collaboratives powered by decentralised learning techniques as a possible remedy to the shortcomings of current data governance schemes. Hence, we propose a mild formalization of the set of existing technological solutions that could inform existing approaches to data governance issues. By adopting an interdisciplinary perspective on data governance, this article highlights how innovative technological solutions can enhance control over data while at the same time ensuring its availability to other stakeholders and thereby contributing to the achievement of the policy goals of the European Strategy for Data.