Ontologies that survive contact with production
Most enterprise models live in a modelling tool, get exported to a diagram, and then drift. TopQuadrant manages your ontologies as governed assets: versioned, owned, validated, and connected to the data they describe, so a change to the model is a change you can trace.
Trusted to govern the data behind the world's most regulated decisions.
A model nobody governs is a diagram
The hard part of an ontology programme was never drawing the classes. It is keeping one agreed version current across a dozen teams, knowing what a change breaks before it ships, and being able to show a reviewer who approved which axiom and when. That is a governance problem, and it is the problem this platform was built for.
Prebuilt semantic models, ontologies, and vocabularies to start from, so you extend rather than begin from an empty file.
Open W3C standards underneath. Your models are OWL, SHACL, and SKOS, exportable in full at any time.
One governed version of every model, with the previous versions still queryable rather than archived in a folder.
Versioning & change control
Every change has an author, a reason, and a diff
Ontology edits move through a working copy, review, and release cycle rather than landing straight in production. Reviewers see exactly which classes, properties, and constraints changed, and releases are tagged so downstream consumers can pin to a version.
- Working copies. Model changes are staged and reviewed before they affect anything downstream.
- Semantic diffs. See the classes, properties, and axioms that changed, not a text comparison of two files.
- Pinned releases. Consumers reference a tagged version, so an in-progress edit never breaks a running system.
Ownership & stewardship
Name an owner for every part of the model
Large ontologies fail on accountability before they fail on modelling. Assign owners, stewards, and approvers by module or domain, and route each proposed change to the person who actually understands that part of the business.
- Modular ownership. Split a large ontology into governed modules with their own owners and release cadence.
- Routed review. Proposed changes reach the right steward automatically, with reminders and escalation.
- Decisions on the record. Rationale is captured alongside the change, so next year’s team knows why.
Validation with SHACL
Enforce your modelling rules automatically
Express your conventions as SHACL shapes and let the platform check every edit against them. Naming rules, mandatory metadata, permitted relationships, and cardinality constraints are validated continuously rather than caught in a review meeting.
- Rules as data. SHACL shapes are governed assets in the same graph, versioned like everything else.
- Checked on every edit. Violations surface the moment they are introduced, with the offending asset named.
- Reusable conventions. Apply one set of modelling standards across every ontology in the estate.
Impact analysis
Know what a change breaks before you ship it
Ontologies connect to the reference data, mappings, glossaries, and downstream systems that depend on them. Before you deprecate a class or rename a property, see every asset, mapping, report, and integration that references it.
- Dependency graph. Follow a concept from the model to every place it is used.
- Deprecation with a path. Retire concepts with successor relationships so consumers can migrate rather than break.
- Reuse without a fork. Import external standards and extend them locally, keeping your changes separable.