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References: Decision Traces: Anatomy and LPG Patterns

  1. Audit Trail - Wikipedia - Defines audit trails as chronological, tamper-evident records of actions and decisions — directly foundational for this chapter's treatment of decision traces as organizational audit records with timestamped actors, policy versions, and approval chains.

  2. Property Graph - Wikipedia - Explains the property graph model with typed nodes and edges with key-value properties — directly supporting this chapter's complete LPG schema specification for decision trace nodes, actor nodes, policy version nodes, and the eleven edge type vocabulary.

  3. Data Provenance - Wikipedia - Covers provenance records including custody chains and transformation histories — foundational for this chapter's cross-system synthesis layer and source data node schema that captures what data was consulted with what quality score at decision time.

  4. Graph Databases (2nd ed.) - Ian Robinson, Jim Webber, Emil Eifrem - O'Reilly Media - Chapter 3 on graph data modeling and Chapters 7–8 on write paths and indexes directly support this chapter's decision trace schema design, trace completeness validation, and the four standard read-path indexes.

  5. The Model Thinker - Scott E. Page - Basic Books - Chapters on formal decision modeling, precedent reasoning, and organizational learning provide theoretical framing for this chapter's treatment of precedent chain patterns, exception logic crystallization, and judgment call documentation.

  6. Cypher (query language) - Wikipedia - Documents the Cypher query patterns used to traverse decision trace schemas — directly supporting this chapter's worked example traversal for the compliance audit query and the read-path query patterns for precedent retrieval.

  7. Knowledge Graph - Wikipedia - Covers knowledge graph entity nodes and relationship types — providing the foundational context for this chapter's APPLIES_TO edge connecting decision trace nodes to entity nodes in the enterprise knowledge graph.

  8. Process Mining - Wikipedia - Explains process discovery and conformance checking from event logs — directly relevant to this chapter's treatment of exception patterns that emerge across decision traces and the counterfactual trace concept for evaluating decision quality.

  9. Provenance (information science) - Wikipedia - Covers the W3C PROV standard for provenance records including attribution, derivation, and entity provenance — supporting this chapter's actor node pattern, DECIDED_BY and APPROVED_BY edge types, and policy version reference schema.

  10. Explainable Artificial Intelligence - Wikipedia - Covers XAI requirements for transparent decision records including factor attribution and decision justification — directly relevant to this chapter's emphasis on capturing exception logic justification text and cross-system synthesis records as the basis for AI decision explainability.