References: Knowledge Graphs and the Enterprise Knowledge Graph

1. Knowledge graph - Wikipedia - Comprehensive overview of knowledge graphs including history, applications, and major implementations. Anchors the chapter's KG framing.

2. Ontology (information science) - Wikipedia - Detailed treatment of formal ontologies, taxonomies, and their role in knowledge representation. Foundation for the chapter's ontology section.

3. Cypher (query language) - Wikipedia - Coverage of Cypher syntax, MATCH patterns, and the path to GQL standardization. Directly supports the chapter's query-language content.

4. Building Knowledge Graphs - Jesús Barrasa and Jim Webber - O'Reilly - Practitioner reference on designing and operating knowledge graphs from Neo4j's experts; directly aligned with the chapter's apply-level outcomes.

5. Graph Databases (2nd Edition) - Ian Robinson, Jim Webber, and Emil Eifrem - O'Reilly - Foundational reference on the labeled property graph data model and graph database internals; a standard companion to this chapter.

6. Neo4j Graph Academy - Neo4j - Free interactive courses on Cypher, graph data modeling, and knowledge graphs. Excellent hands-on supplement to the chapter's KG-construction lab.

7. Schema.org - W3C / WHATWG - The lightweight ontology vocabulary referenced throughout this chapter; widely used as the starting point for enterprise ontology design.

8. GraphRAG Documentation - Microsoft - Open-source implementation of GraphRAG with concrete examples. Directly supports the chapter's GraphRAG content.

9. Amazon Neptune Documentation - Amazon Web Services - Authoritative reference for one of the major cloud graph databases, supporting both property graph and RDF models.

10. W3C SPARQL 1.1 Overview - W3C - The W3C standard for querying RDF graphs. Useful contrast to Cypher when discussing the property-graph-vs-RDF tradeoff.