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References: Graph Data Modeling for Context

  1. Graph Database - Wikipedia - Covers graph database architectures including property graph models, index-free adjacency, and constraint enforcement — directly relevant to this chapter's context graph index design, cardinality patterns, and graph constraint enforcement sections.

  2. Slowly Changing Dimension - Wikipedia - Defines the SCD Type 1/2/3 patterns from data warehousing for managing time-varying attributes — directly supporting this chapter's application of SCD Type 2 to context graph node properties that must retain history for accurate historical queries.

  3. Temporal Database - Wikipedia - Explains bitemporal database concepts including valid time, transaction time, and the SQL:2011 temporal extensions — foundational for this chapter's core topic of bitemporal modeling applied to context graph nodes and edges.

  4. Graph Databases (2nd ed.) - Ian Robinson, Jim Webber, Emil Eifrem - O'Reilly Media - Chapters 5–8 cover property normalization decisions, cardinality design, index strategy, and schema evolution for production graph deployments — directly matching this chapter's complete graph data modeling toolkit for context graphs.

  5. The Data Warehouse Toolkit (3rd ed.) - Ralph Kimball, Margy Ross - Wiley - Chapters 5–6 provide the canonical treatment of slowly changing dimensions, temporal fact tables, and audit columns — foundational for this chapter's application of SCD patterns and bitemporal modeling to context graph temporal edge design.

  6. Entity–Relationship Model - Wikipedia - Covers entity-relationship modeling including cardinality notation and normalization principles — supporting this chapter's sections on context graph cardinality design, property normalization, and cross-graph reference patterns.

  7. Cypher (query language) - Wikipedia - Documents Cypher query patterns for temporal filtering, subgraph extraction, and constraint enforcement — directly supporting this chapter's bitemporal query examples and subgraph extraction traversal descriptions.

  8. Data Lineage - Wikipedia - Covers lineage graph structures and append-only event capture patterns — supporting this chapter's event-driven graph update architecture and the requirement that temporal properties are managed with append-only semantics rather than in-place updates.

  9. openCypher Standard - openCypher Project - Documents the openCypher specification for graph constraint syntax, index declarations, and schema management — directly relevant to this chapter's context graph constraint types and schema evolution principles using standard Cypher-compatible tooling.

  10. Embedding (machine learning) - Wikipedia - Explains vector embeddings and approximate nearest-neighbor indexes (HNSW) — supporting this chapter's vector embedding index section and the complementary hybrid retrieval pattern combining semantic embedding search with graph traversal for context assembly.