Data Trust Architecture: ISO Standards and the Evolution of the Data Governance 3.0 Model in Blockchain Ecosystems - Malgorzata MICHNIEWICZ (Communications of International Proceedings, 2025)
The rapid growth of distributed ledger technologies (DLT) and new regulatory obligations (GDPR, DORA, NIS2, AI Act) are forcing organisations to rethink how they govern data as a strategic and auditable asset. However, existing data-governance models and standards only partially address trust, accountability and interoperability in decentralised ecosystems. This paper proposes the concept of Data Governance 3.0 and a corresponding Data Trust Architecture (DTA) that position blockchain as a technical trust layer for data-driven and AI-enabled systems. The study applies an interpretive review of international standards (ISO/IEC 8000, 27001, 38505, 22739, 23245–23258, 23635, 6277; IEEE 2418.x, 2145, 3447; NIST, ISACA) and academic and professional literature from 2016–2024. On this basis, it traces the evolution from centralised control (Data Governance 1.0), through federated data-product models (2.0, Data Mesh), to decentralised trust-based governance (3.0). The paper synthesises these sources into a four-layer DTA model (governance and policy; identity and access; integrity and provenance; interoperability and automation) with clearly defined organisational roles. The findings show that Data Governance 3.0 enables data to function as a self-verifiable trust asset, providing cryptographic evidence of integrity, provenance and policy compliance across organisational boundaries. The proposed DTA provides a reference framework for designing accountable and interoperable data ecosystems, integrating blockchain, AI, Data Mesh and Compliance-as-Code. The paper concludes with research directions for formalising data-trust metrics and cross-chain interoperability in future Data Trust 4.0 architectures.
Keywords: Data governance; blockchain; Data Trust Architecture; data accountability