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Exploration
The Learning Graph has a dedicated interactive exploration interface in the platform. It lets educators, administrators, and learners navigate the full knowledge topology, inspect relationships, and find gaps or opportunities.
Key Features
Domain selection — Start by choosing a root-level Topic domain (e.g. Arts and Humanities, Technology, Health Sciences). The graph loads the subgraph for that domain so you can work with a manageable slice.
Node search — Full-text search across all Topics and Skills. Results show matching nodes in context so you can jump directly to any point in the taxonomy.
Interactive navigation — Click any node to expand its neighbours. Topics expand into subtopics and linked skills; Skills reveal their topic domains and related skills. You can move through the ontology without leaving the graph view.
Layout modes — Choose from several automatic layout algorithms: vertical layered (default), horizontal layered, stress-based, and force-directed. Each reveals different structural patterns in the knowledge topology.
Node editing — Admins and educators can view and edit node properties, add multilingual names and descriptions, and create new nodes or relationships directly in the interface.
Discover Mode
Discover surfaces unmapped territory adjacent to an entity’s current topic mappings. It finds:
- Unmapped subtopics several levels deep below current topics
- Essential lateral topics not yet covered
- “Surprise Me”–style suggestions in the library
This supports serendipitous curriculum expansion and helps educators see where their content could grow.
All Topics and Skills in the explorer are shown in the user’s language. The graph stores names and descriptions per locale, so the exploration experience is fully localised.
Where to Find It
The Learning Graph explorer is available from the platform navigation. Use it to browse the ontology, validate mappings, and discover new topics to attach to courses, modules, or profiles.
Next Steps
- Ontology — structure of Topics and Skills
- Entity Connections — how entities connect to the graph
- AI Cataloging — how the Librarian uses the graph to map entities