Knowledge graph

A knowledge graph represents knowledge as a network of entities (nodes) and typed relations (edges), usually structured by an Ontology. The term became widely known when Google introduced its Knowledge Graph in 2012; today it describes any large, connected data set of "things, not strings".

What makes it a graph

Each statement connects two things with a named relation — Pump P200 → hasComponent → Seal assembly. In RDF these statements are triples; in property graphs, nodes and edges carry attributes. Because relations are explicit, a knowledge graph can answer questions that span many documents: which safety instructions apply to every component of this product?

Knowledge graphs and documentation

• They link documentation to product data, parts lists and service events
• They let a portal assemble exactly the topics a situation needs, using Metadata and Faceted classification
• They give AI systems grounded context: retrieval-augmented generation can follow relations instead of guessing from text similarity alone, which supports Findability for machines

This vault is one

Every note here is a node; every wikilink is an edge. The graph view on the vault page shows how the ideas of Information architecture connect.