Policy & Literacy for Data

In addition to the opportunities and challenges within government, governance, and technology, the third key focus area for data-driven policy research involves the policy, governance, and management issues related to developing and implementing data-driven solutions. Across the globe, different governance models and frameworks for data and associated technologies are being developed, influenced by local contexts, cultural values, and levels of public literacy and acceptance.

Regulations like Europe’s GDPR have set high standards for data practices worldwide, influencing how data is managed and protected. Additionally, laws and regulations concerning emerging technologies, such as AI and Blockchain, are increasingly being shaped through both the reinterpretation of existing laws and the introduction of new ones. Concepts like data intermediaries, data trusts, and peer-to-peer data infrastructures (such as distributed ledgers) are being explored as potential solutions for managing the complexities of sensitive data sharing and public–private collaborations.

From a management perspective, key concerns include data supply chains, ownership, provenance, sharing, linkage, and data curation. Effective governance of data and technology also depends on the availability of high-quality metadata, which must adhere to common standards to ensure interoperability across different scales.

The focus here is on understanding and managing the intricate relationships between data subjects, data controllers, and stakeholders, and on encouraging policymakers to reconsider the balance of power in data governance.