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 by privacy regulations. When managing a large amount of data with dispersed rightsholders, obtaining their legal consent incurs high transaction costs. Collective governance models like data trust offer a potential solution. However, traditional trust objects differ from personal data, as 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, but 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 for future legislation and public policies in the field, potentially leading to more efficient and sustainable data governance and information management.