- Created SHACL shapes for validating temporal consistency and bidirectional relationships in custodial collections and staff observations. - Implemented a Python script to validate RDF data against the defined SHACL shapes using the pyshacl library. - Added command-line interface for validation with options for specifying data formats and output reports. - Included detailed error handling and reporting for validation results.
5.3 KiB
Session Summary: Phase 6 - SPARQL Query Library
Date: 2025-11-22
Schema Version: v0.7.0 (stable, no changes)
Duration: ~45 minutes
Status: ✅ COMPLETE
What We Did
Phase 6 Goal
Document comprehensive SPARQL query patterns for querying heritage custodian organizational data, collections, and staff relationships.
Deliverable
File: docs/SPARQL_QUERIES_ORGANIZATIONAL.md (1,168 lines)
What Was Created
1. SPARQL Query Documentation (31 Queries)
Category Breakdown:
- Staff Queries (5): Curators, role changes, expertise matching
- Collection Queries (5): Managing units, temporal coverage, collection types
- Combined Staff + Collection (4): Curator-collection matching, department inventories
- Organizational Change (4): Custody transfers, restructuring impacts, timelines
- Validation Queries (5): SPARQL equivalents of Phase 5 Python validation rules
- Advanced Temporal (8): Point-in-time snapshots, tenure analysis, provenance chains
2. Key Features Documented
✅ SPARQL 1.1 Compliance - All queries use standard syntax
✅ Temporal Query Patterns - Allen interval algebra for date overlaps
✅ Validation Queries - RDF triple store equivalents of Phase 5 rules
✅ Aggregation Queries - AVG, COUNT, SUM for analytics
✅ Optimization Tips - Filter placement, OPTIONAL usage, indexing
✅ Usage Examples - Python rdflib + Apache Jena Fuseki
3. Integration with Previous Phases
Phase 3 (Staff Roles):
- Queries 1.1-1.5 leverage
PersonObservationclass - Role change tracking (Query 1.3)
- Expertise matching (Query 1.5)
Phase 4 (Collection-Department Integration):
- Queries 2.1-2.2 use
managing_unit↔managed_collections - Bidirectional consistency queries (5.2, 5.5)
- Department inventory reports (Query 3.4)
Phase 5 (Validation Framework):
- All 5 validation rules converted to SPARQL (Queries 5.1-5.5)
- Temporal consistency checks
- Bidirectional relationship validation
Files Created
-
docs/SPARQL_QUERIES_ORGANIZATIONAL.md(1,168 lines)- 31 complete SPARQL queries
- Expected results + explanations
- Query optimization guidelines
- Testing instructions
-
SPARQL_QUERY_LIBRARY_COMPLETE_20251122.md(completion report)
Key Achievements
1. Comprehensive Query Coverage
- ✅ All 22 classes queryable
- ✅ All 98 slots accessible
- ✅ 5 validation rules in SPARQL
- ✅ 8 advanced temporal patterns
2. Real-World Use Cases
- Department inventory reports
- Staff tenure analysis
- Organizational complexity scoring
- Provenance chain reconstruction
3. Validation Integration
- Python validator (Phase 5) for development
- SPARQL queries for production monitoring
- Complementary approaches
Technical Highlights
Temporal Query Pattern (Allen Interval Algebra)
# Find entities valid during query period
FILTER(?validFrom <= ?queryEnd)
FILTER(!BOUND(?validTo) || ?validTo >= ?queryStart)
Used in: Queries 1.4, 2.4, 6.1, 6.3
Bidirectional Relationship Validation
# Detect missing inverse relationships
FILTER NOT EXISTS {
?unit custodian:managed_collections ?collection
}
Used in: Queries 5.2, 5.5
Provenance Chain Reconstruction
# Trace custody history chronologically
?collection custodian:custody_history ?custodyEvent .
?custodyEvent prov:wasInformedBy ?changeEvent .
ORDER BY ?transferDate
Used in: Queries 4.1, 6.3
Testing Status
| Test Type | Status | Notes |
|---|---|---|
| Syntax Validation | ✅ COMPLETE | All queries SPARQL 1.1 compliant |
| Schema Compatibility | ✅ COMPLETE | Verified against v0.7.0 RDF schema |
| Instance Data Testing | ⚠️ DEFERRED | Requires YAML→RDF conversion (Phase 7) |
Note: Full end-to-end testing requires converting test instances to RDF triples.
Success Criteria - All Met ✅
| Criterion | Target | Achieved | Status |
|---|---|---|---|
| Query Count | 20+ | 31 | ✅ 155% |
| Categories | 5 | 6 | ✅ 120% |
| Examples | All queries | 31/31 | ✅ 100% |
| Validation Queries | 5 rules | 5 queries | ✅ 100% |
| Explanations | Clear | 31/31 | ✅ 100% |
What's Next: Phase 7 - SHACL Shapes
Objective
Convert validation queries into SHACL shapes for automatic RDF validation at data ingestion time.
Why SHACL?
- ✅ Prevent invalid data entry (not just detect)
- ✅ Standardized validation reports
- ✅ Triple store integration (GraphDB, Jena)
- ✅ Detailed error messages
Deliverables (Phase 7)
- SHACL shape file:
schemas/20251121/shacl/custodian_validation_shapes.ttl - Documentation:
docs/SHACL_VALIDATION_SHAPES.md - Validation script:
scripts/validate_with_shacl.py
Estimated Time
60-75 minutes
References
- Query Library:
docs/SPARQL_QUERIES_ORGANIZATIONAL.md - Completion Report:
SPARQL_QUERY_LIBRARY_COMPLETE_20251122.md - Schema (v0.7.0):
schemas/20251121/linkml/01_custodian_name_modular.yaml - Test Data:
schemas/20251121/examples/collection_department_integration_examples.yaml - Phase 5 Summary:
SESSION_SUMMARY_VALIDATION_PHASE5_20251122.md
Phase 6 Status: ✅ COMPLETE
Next Phase: Phase 7 - SHACL Shapes
Overall Progress: 6/9 phases complete (67%)