Policy-Bound Semantic Data Meshes for AI-Ready Enterprise Knowledge Foundations: A Systematic Review
DOI:
https://doi.org/10.71238/snnst.v1i02.225Keywords:
Access Control; Data Governance; Data Mesh; Data-Centric AI; FAIR Principles; Knowledge Graph; Linked Data; Responsible AI; Semantic WebAbstract
Semantically rich, policy-aware, and organizationally distributed data is an essential component of enterprise artificial intelligence (AI) efforts as they become increasingly common. Incorporating semantically rich, policy-aware, and organizationally distributed data is the foundation of enterprise artificial intelligence (AI) initiatives, as they become more ubiquitous. To define policy-bound semantic data meshes, a systematic review of 28 sources covering fields such as ontology engineering, linked data, knowledge graphs, data governance, access control, data-centric AI and responsible AI documentation was carried out. The corpus was themed into six themes, coded to five governance decision domains and mapped to the four data mesh principles. The scale of the industry knowledge graph, data cascades and the mention of ethical principles in guideline documents were compared quantitatively across sources. The results showed that 92% of the practitioners who were interviewed experienced at least one data cascade, transparency was found in 73 out of 84 ethics guidelines, and 15 FAIR principles were found to be testable to demonstrate interoperability. With industry knowledge graphs, it's possible to integrate up to 1 to 2 billion entities, making integration at scale possible. It is derived a layered reference architecture, where the ontologies, machine-readable policies and documentation artefacts are bound to each domain data product; a formal decision rule with deny-overrides semantics and a composite readiness index is proposed. The novelty is that three distinct research streams dealing with knowledge at the enterprise level are merged together in one formulation of governance by design for AI-ready enterprise knowledge.
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