Overview
The ontology defines the schema of your knowledge graph — the types of entities (nodes) and relationships (edges) that Experio uses to organize extracted knowledge. A well-designed ontology ensures that information from different sources is connected meaningfully. At runtime the graph may be backed by Neo4j or FalkorDB depending onGRAPH_PROVIDER in System Settings.
The ontology editor and schema semantics are the same; provider-specific behavior (for example certain analytics queries)
is summarized in Graph backend (Neo4j & FalkorDB).
Navigate to Admin > Graph > Ontology.
Visual Editor
The ontology is managed through an interactive visual editor:- Entity type nodes are displayed as draggable boxes on a canvas
- Relationship edges connect entity types with labeled arrows
- Zoom and pan to navigate the schema
- Drag nodes to arrange the layout
- Hide nodes from the canvas with the eye icon on the left list (session-only; not saved)
Filter by content type
The toolbar includes a content type dropdown. Use it to see which parts of the ontology a given content type actually extracts, without changing the saved schema.- Leave All content types selected to see the full graph.
- Choose a content type. Nodes and relationships that are not in that type are hidden from the canvas. This uses the same hide behavior as the eye icon on each node in the left list.
- Click a remaining node and open Attributes. Attributes defined on the ontology but not selected on that content type are greyed out. They stay editable.
- Choose All content types again to restore the full graph.
Permissions
- Read-only users can view the ontology but cannot make changes
- Write users can add, edit, and remove entity types and relationships
Entity Types
Entity types represent the categories of things in your knowledge graph. Common examples:
Each entity type has:
- Name — A unique identifier for the type
- Properties — Attributes that instances of this type can have (e.g., Person has “name”, “email”, “title”)
Relationships
Relationships define how entity types connect to each other. Examples:Saving Changes
After modifying the ontology:- Click Save. If the change renames or deletes schema elements (or otherwise breaks dependents), a confirmation modal lists the impact before anything is published.
- Confirm to persist the schema. Experio creates a new ontology revision, auto-updates matching names in content types, mappings, and related config, and sets those configs to stale or invalid as needed.
- The canvas layout (node positions) is saved with the schema.
Employee that you rename to
Person updates matching names in configs). Those configs become stale so you can review them.
Stale status warns in the admin UI; it does not block scans.
Revision history and rollback
Open History on the ontology editor, or go to Admin > Graph > Ontology > Revision history. The revisions list shows each published schema (newest first), who saved it, and a short change summary (additions, renames, breaking deletes). Select a revision to see a human-readable diff and the schema JSON.Rollback
Write-access admins can restore a previous revision:- Select the revision to restore (not the current one).
- Review the impact preview — the same confirmation used when saving.
- Confirm. Experio sets the live schema to that snapshot and publishes a new revision that records which revision you rolled back from.
Deleting an ontology
You cannot delete the default ontology. You also cannot delete an ontology that still has data mappings attached — remove or reassign those mappings first.Related: Inference Rules
After ingestion populates the graph, you can use Enrichment Rules to enrich it further. Enrichment rules process existing nodes and create new attributes, nodes, or relationships — all defined using the entity types and relationships in your ontology.Best Practices
- Start with a small, focused ontology and expand as needed
- Use clear, descriptive names for entity types
- Define relationships that reflect real-world connections in your organization
- Review the ontology periodically as your data sources grow
- After each save, check Ontology Compatibility and fix invalid configs before the next scan