New Framework Proposed for Data Governance in U.S. Data Collaboratives
A new paper, titled "Orchestrating and Designing Data Collaboratives: What Governance Model is Fit for Purpose?", introduces a purpose-driven framework for selecting and combining data governance models. This framework is designed to address specific challenges within data collaboratives in the United States. The paper identifies seven distinct governance archetypes: data intermediaries, data unions, data trusts, data commons, data cooperatives, data sandboxes, and data spaces. Each archetype is detailed in terms of the unique coordination, power, legitimacy, ownership, uncertainty, and scaling challenges it is best suited to tackle. Rather than viewing these models as competing options, the paper advocates for an approach called "institutional orchestration." This method suggests that data stewards should strategically choose, combine, and adapt various governance arrangements as data ecosystems evolve and their needs change. The research is intended for a broad audience, including federal, state, local, ...
