Topic starter
24/06/2026 7:34 pm
TL;DR: Open Semantic Interchange and governed semantic layers aim to make data definitions, lineage, and access controls consistent across Snowflake and Collibra workflows, which matters as unstructured data and AI models depend on trusted context, according to Collibra. The deeper shift is that governance now has to travel with the data and the semantics, not sit beside them.
Editorial analysis by NHI Mgmt Group, based on content published by Collibra: “Accelerating data delivery using OSI with Snowflake and Collibra”.
Key questions
Q: How should teams govern semantic layers for agentic AI systems?
A: Teams should govern semantic layers as authoritative decision infrastructure, not as a reporting convenience.
Q: Why do inconsistent semantics create risk for IAM and AI governance?
A: Inconsistent semantics cause different systems to make decisions from different interpretations of the same term.
Q: What breaks when access policy and semantic meaning are managed separately?
A: Policy may still block or mask data correctly, but the organisation can end up authorising the wrong business meaning.
Practitioner guidance
- Define semantic assets as governed objects Inventory the metrics, dimensions, formulas, and business terms that must stay consistent across BI, warehouse, and AI workflows.
- Translate policy into native controls Map plain-language access rules to row-level filtering and dynamic masking so governance is enforced where users and agents query data.
- Require lineage for AI inputs Track which training tables, facts, and semantic definitions feed each model so the organisation can trace why an answer was produced.
Bottom line: Open semantic interchange is really about moving trusted meaning with the data, not just moving data between systems.
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25/06/2026 4:56 am
Open semantic interchange turns governance from a static control layer into a portable trust layer. The important change is not simply that definitions are shared across tools, but that governance context can move with data as it is consumed by humans and AI systems. That shifts the burden from reconciling outputs after the fact to enforcing meaning before consumption. Practitioners should read OSI as a governance portability problem, not a formatting exercise.
A question worth separating out:
Q: How do organisations know whether semantic governance is actually working?
A: Semantic governance is working when critical definitions are consistent across tools, changes are approved, and lineage can explain how a decision was derived. If users still argue about what a metric means, or if AI outputs vary because upstream terms drift, the governance layer is not effective.
👉 Read our full editorial: Open semantic interchange changes how data governance scales