Addressing the governance of emerging digital automation technologies and data requires a multidisciplinary perspective. An economic perspective is needed to understand, conceptually and empirically, how data value accrues along the data value chain. A techno-legal perspective is needed to attribute data rights to data subjects, based on how value accrues and the objectives of just data governance, and it often entails trade-offs. Governing the process of individual and commercial data sharing, either through mandatory rules or by creating incentives for sharing, is central to data governance and is important for research and policy agendas. Two examples from the EU regulatory framework, the Data Governance Act and the AI Act, attempt to devise principles that might address some of the challenges related to data governance, including AI.

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