Open Data Infrastructure
Context Graphs for Retrieval Governance
How context graphs connect retrieval chunks, source tables, policies, owners, freshness, ranking signals, and answer evidence.
Retrieval governance starts when a chunk can explain where it came from and why it was allowed into the answer.
Retrieval needs connected evidence
A retrieval system often stores chunks, embeddings, metadata, rankings, and source links. That is useful, but governance needs relationships. Which table produced the chunk? Which policy applied? Which owner is responsible? Which freshness signal was current? Which answer used it?
A context graph connects those relationships so retrieval behavior becomes inspectable. The graph should connect chunks to source assets, transformations, permissions, quality signals, ranking evidence, and answer traces.
Policy needs to travel with retrieval
The dangerous failure is not always a bad embedding. It is a good retrieval result that the requester should not see, or a stale result that looks authoritative. Retrieval governance needs policy and freshness in the same review path as ranking quality.
That does not mean every retrieval stack needs a giant knowledge graph project. It means the minimum viable context graph should answer the questions operators actually ask during an incident.
Core idea: a context graph turns retrieval from a bag of chunks into governed infrastructure behavior.
The ODI pattern connects retrieval to data ownership
Open Data Infrastructure makes source data, metadata, lineage, policy, and quality signals available outside a single tool boundary. Context graphs use those signals to make retrieval explainable.
For adjacent context, read the context graph, retrieval governance in ODI, and AI-ready context evaluation datasets.
What breaks first
- Chunks retain source URLs but lose table lineage.
- Policy is checked before indexing but not at retrieval time.
- Freshness metadata exists in the catalog but never reaches ranking or answer review.
- Answer traces show chunks but not the owners, policies, or quality signals behind them.
Questions to ask
Ask which graph edges are required for review: chunk to source, source to owner, owner to policy, policy to decision, and decision to answer. Ask which edges are missing when retrieval fails.
Sources to start with
These primary sources anchor the technical claims in this guide.
- OpenLineage object model documentation
- W3C PROV overview
- DataHub lineage documentation
- OpenAI evals guide
Governed retrieval is retrieval that can point back to the system of record and the permission that made it usable.