NVOpen source
NVIDIA Auto Ontology
Build a semantic catalog from enterprise metadata and give agents consistent business definitions and query context.
Ontology & Semantic Modeling
Stardog Virtual Graphs
Map structured sources to RDF and query document-derived records alongside other enterprise data.
At a glance
- Input
- Relational databases, CSV, JSON and supported sources
- Output
- RDF, SPARQL results
- Provenance
- Source mappings; not document coordinates
- Scanned pages
- Not applicable; parse documents upstream
- Deployment
- Server deployment
- Availability
- Commercial
- Costs to plan for
- Enterprise quote
Semantic modeling profile
Semantic foundation
Representation and interoperability
RDF mappings and SPARQL queries over supported source systems.
Updates and versioning
Maintain source mappings and model versions as part of the application lifecycle.
Limitations to check
A mapping and query capability, not automatic ontology learning. Source connectivity and mapping maintenance are required.
Build a meaningful sample
Test ambiguous terms, conflicting metric definitions, source mappings, and schema changes. Check how revisions affect the same workload.