Data trust for personal data: From trusts to collective management organisations

The widespread use of data presents significant managerial challenges, particularly when this information is legally protected. Privacy regulations mandate the rightsholder’s prior, explicit, and informed consent if the processed asset is personal data. However, when there is a large amount of data with dispersed rightsholders, this legal task incurs high transaction costs. Collective governance models like data trust offer a potential solution. While this managerial model is rooted in the Anglo-Saxon trust, it deals with an intangible asset distinct from the traditional trust objects. It involves personal rights that are essentially inalienable in general. Therefore, negotiating personal rights through an economic scheme involves complex incentives and cost-benefit trade-off problems, presenting economic inefficiencies. Trust and privacy regulations, while important, are limited frameworks in this context. However, the copyright system can complement and reconcile the legal nature of the collectively managed rights over intangible assets. This cross-disciplinary research proposes migrating data trust agreements to data collective management entities, combining
legal dogmatic and economic approaches with systems thinking methodologies. This proposal offers an integrated and diverse perspective for ongoing academic discussions and future legislation and public policies in the field, potentially leading to more efficient and sustainable data governance and information management.