Abstract:

The dynamic development of distributed ledger technologies (DLT) and the growing regulatory requirements (GDPR, DORA, NIS2, AI Act) have contributed to a redefinition of the concept of data governance.

This paper presents the evolution of data governance approaches — from centralized models (1.0), through federated ones (2.0, Data Mesh), to decentralized and trusted Data Governance 3.0 systems, based on the principles of Data as a Product, automation, and auditability.

Based on an analysis of ISO/IEC standards (38505, 27001, 8000, 22739, 23245, 23246, 23257, 23635, 6277), IEEE standards (2418.1-2021, P2145, 3447-2022, P3447.1, 2791-2022), and a literature review from 2016 to 2024, the article introduces the “Data Trust Architecture” model — combining paradigms of data quality management, data value creation, and data accountability with blockchain technologies (hashing, smart contracts, lineage and provenance) (7).

Data Governance 3.0 will become a key trust layer for AI ecosystems and interoperable data architectures, while the ongoing ISO/TC 307 standardization will serve as a framework bridging technological, organizational, and legal domains.