Ontology-Guided Data Mesh Design for Decentralized Governance

Abstract

The rise of Data Mesh as a paradigm for large-scale data management has challenged the traditional monolithic data lake approach by promoting decentralized ownership, domain-oriented architecture, and self-serve infrastructure. However, without a unified semantic layer, decentralization can lead to fragmentation, inconsistency, and governance bottlenecks. This paper proposes an ontology-guided approach to Data Mesh design, leveraging domain ontologies to ensure semantic interoperability, governance automation, and federated data product discovery. By aligning domain-specific knowledge structures with data product metadata, we demonstrate how ontologies facilitate coherent data governance across distributed teams while preserving the autonomy of individual domains. We explore architectural patterns, governance workflows, and implementation considerations, and present a case study to illustrate the application of this approach in a real-world enterprise setting.