Knowledge & Data · Data artifact
Knowledge Chunk Metadata Schema
Data artifactKnowledge & DataKnowledge & Dataarc:KnowledgeChunkMetadataSchema
A data contract for semantic-memory chunk metadata recording source document, chunk position, last-updated timestamp, temporal validity period, version and source type.
Responsibility. Specifies the provenance and temporal metadata every indexed knowledge chunk must carry.
Also known as: Temporal metadata tagging, Chunk provenance metadata, Document collection schema, Vector collection schema, Temporal markers
Relationships
configures structural
Design guidance
- MUST tag every knowledge chunk with temporal metadata so retrieval can filter or rank by validity period.
- SHOULD record source document and chunk position so retrieved chunks can be ordered, reassembled and cited.
- SHOULD be created idempotently so initialization can run on every startup or deployment.
- MUST carry publication date, last-modified timestamp and validity period for every ingested document to enable freshness filtering and recency ranking.
Classification
- Patterns
- content, source_doc, chunk_index and nested metadata (section, timestamp, author)Vectorizer module declaration per collection
- Quality attributes
- Functional suitability: correctness and validity (ISO/IEC 25010 | NIST AI RMF: valid)Transparency and accountability (NIST AI RMF: accountable and transparent)
- Risks mitigated
- Temporally confused answers mixing past and present factsInability to answer point-in-time questions
Sources
- Ch5.8: T. Nguyen, "Semantic Memory," in Mastering Agentic AI Systems: Guide for the NVIDIA NCP-AAI Exam, 1st ed. 2026, ch. 5.8. ISBN: 9798244538229.
- Ch6.2B: T. Nguyen, "Production Vector Database Deployment," in Mastering Agentic AI Systems: Guide for the NVIDIA NCP-AAI Exam, 1st ed. 2026, ch. 6.2B. ISBN: 9798244538229.
- Ch6.3A: T. Nguyen, "ETL Pipeline Fundamentals," in Mastering Agentic AI Systems: Guide for the NVIDIA NCP-AAI Exam, 1st ed. 2026, ch. 6.3A. ISBN: 9798244538229.
- Ch6.4: T. Nguyen, "Data Quality Fundamentals," in Mastering Agentic AI Systems: Guide for the NVIDIA NCP-AAI Exam, 1st ed. 2026, ch. 6.4. ISBN: 9798244538229.