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The 3D Knowledge Graph

Every table in OpenMetadata carries a Knowledge Graph tab that renders its neighborhood as an interactive 3D force-directed graph. It is the fastest way to see, rather than query, how one asset sits in the wider catalog. 3D Knowledge Graph tab on a table
The tab is hidden unless RDF is enabled, and is marked Beta. It reads from GET /api/v1/rdf/graph/explore, which is admin-only.
Drag to orbit, scroll to zoom, click a node to select it. The graph starts focused on the asset you opened it from. A caption above the canvas states the current level, the node count, and what that level shows — for example “Data Asset Level · 125 nodes · Tables, columns, owners and queries — and the lineage between assets.”

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Levels

The Level control changes what kind of thing the graph is about. It is not a filter — it is a different question. Zooming out from asset to domain is the difference between “what feeds this table” and “which parts of the business are coupled, and through what.”

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Relationships

The Relationships control changes which kind of edge is drawn: The Ontology option is the interesting one. It hides the plumbing and draws the business model as applied to real data: two tables appear connected not because a pipeline links them, but because the concepts they carry are related. Each node shows its primary glossary term (with a +N badge when it carries more), and the caption summarizes N linked assets · M derived relationships. 3D Knowledge Graph in Ontology mode: three assets linked through the Order concept

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Derived Relationships

Ontology-lens edges between two assets are derived — inferred by overlaying glossary terms, not read from a direct technical link. Selecting one explains exactly how it was derived: The panel shows the full derivation chain as names — for example savings_account → Savings Account → Accounts → Checking Account → checking_account — so a derived edge is never a black box.

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Coverage Gaps

The Highlight coverage gaps toggle marks, in red, tables with no glossary-term mapping at all. This is the most actionable view in the product for a governance team. It answers “where is my ontology not applied?” visually, on real assets, instead of as a number on a dashboard. The gaps are where an AI agent will guess, because nothing has told it what that table means.

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Other Controls

Selecting a node opens a details panel with its type, description, mapped concepts, and neighbors — with Focus on node to re-center. Selecting a link opens an edge panel describing the relationship.

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Reading the Picture

Node color encodes entity type and node size encodes importance at the current level; the primary type for the level is emphasized so the thing you asked about stands out. Technical links are drawn blue, ontology links amber, coverage gaps red. When the server had to bound the result, the caption says so explicitly — “Showing a partial graph — some relationships were omitted for performance.” A truncated graph is labeled rather than silently misleading.

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Troubleshooting

RDF is disabled on this server, or you are not looking at a table. The tab is registered for tables and hidden when rdfEnabled is false.
RDF is enabled but the graph has not been populated. Run the RDF Knowledge Graph Indexing application from Settings → Applications.
The browser does not support WebGL, or it is disabled. Check chrome://gpu or the equivalent, and hardware-acceleration settings.
Drop Depth to 1, switch Relationships to Knowledge Graph or Ontology to halve the edges, and turn off Show columns.

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Exporting the Underlying Graph

The scene export produces a PNG. To take the data with you, use the export endpoint the tab reads from:
format accepts turtle or jsonld. entityTypes and relationshipTypes accept comma-separated filters.

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Next

Querying with SPARQL

When clicking is not enough.

Graph Insights

Importance, communities, and paths computed over the whole graph.