6eb18700f0
- 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.
184 lines
5.3 KiB
Markdown
184 lines
5.3 KiB
Markdown
# Session Summary: Phase 6 - SPARQL Query Library
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**Date**: 2025-11-22
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**Schema Version**: v0.7.0 (stable, no changes)
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**Duration**: ~45 minutes
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**Status**: ✅ COMPLETE
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---
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## What We Did
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### Phase 6 Goal
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Document comprehensive SPARQL query patterns for querying heritage custodian organizational data, collections, and staff relationships.
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### Deliverable
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**File**: `docs/SPARQL_QUERIES_ORGANIZATIONAL.md` (1,168 lines)
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---
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## What Was Created
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### 1. SPARQL Query Documentation (31 Queries)
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**Category Breakdown**:
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- **Staff Queries** (5): Curators, role changes, expertise matching
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- **Collection Queries** (5): Managing units, temporal coverage, collection types
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- **Combined Staff + Collection** (4): Curator-collection matching, department inventories
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- **Organizational Change** (4): Custody transfers, restructuring impacts, timelines
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- **Validation Queries** (5): SPARQL equivalents of Phase 5 Python validation rules
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- **Advanced Temporal** (8): Point-in-time snapshots, tenure analysis, provenance chains
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### 2. Key Features Documented
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✅ **SPARQL 1.1 Compliance** - All queries use standard syntax
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✅ **Temporal Query Patterns** - Allen interval algebra for date overlaps
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✅ **Validation Queries** - RDF triple store equivalents of Phase 5 rules
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✅ **Aggregation Queries** - AVG, COUNT, SUM for analytics
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✅ **Optimization Tips** - Filter placement, OPTIONAL usage, indexing
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✅ **Usage Examples** - Python rdflib + Apache Jena Fuseki
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### 3. Integration with Previous Phases
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**Phase 3 (Staff Roles)**:
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- Queries 1.1-1.5 leverage `PersonObservation` class
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- Role change tracking (Query 1.3)
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- Expertise matching (Query 1.5)
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**Phase 4 (Collection-Department Integration)**:
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- Queries 2.1-2.2 use `managing_unit` ↔ `managed_collections`
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- Bidirectional consistency queries (5.2, 5.5)
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- Department inventory reports (Query 3.4)
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**Phase 5 (Validation Framework)**:
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- All 5 validation rules converted to SPARQL (Queries 5.1-5.5)
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- Temporal consistency checks
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- Bidirectional relationship validation
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---
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## Files Created
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1. **`docs/SPARQL_QUERIES_ORGANIZATIONAL.md`** (1,168 lines)
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- 31 complete SPARQL queries
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- Expected results + explanations
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- Query optimization guidelines
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- Testing instructions
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2. **`SPARQL_QUERY_LIBRARY_COMPLETE_20251122.md`** (completion report)
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---
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## Key Achievements
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### 1. Comprehensive Query Coverage
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- ✅ All 22 classes queryable
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- ✅ All 98 slots accessible
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- ✅ 5 validation rules in SPARQL
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- ✅ 8 advanced temporal patterns
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### 2. Real-World Use Cases
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- Department inventory reports
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- Staff tenure analysis
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- Organizational complexity scoring
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- Provenance chain reconstruction
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### 3. Validation Integration
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- Python validator (Phase 5) for development
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- SPARQL queries for production monitoring
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- Complementary approaches
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---
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## Technical Highlights
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### Temporal Query Pattern (Allen Interval Algebra)
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```sparql
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# Find entities valid during query period
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FILTER(?validFrom <= ?queryEnd)
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FILTER(!BOUND(?validTo) || ?validTo >= ?queryStart)
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```
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Used in: Queries 1.4, 2.4, 6.1, 6.3
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### Bidirectional Relationship Validation
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```sparql
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# Detect missing inverse relationships
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FILTER NOT EXISTS {
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?unit custodian:managed_collections ?collection
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}
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```
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Used in: Queries 5.2, 5.5
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### Provenance Chain Reconstruction
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```sparql
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# Trace custody history chronologically
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?collection custodian:custody_history ?custodyEvent .
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?custodyEvent prov:wasInformedBy ?changeEvent .
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ORDER BY ?transferDate
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```
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Used in: Queries 4.1, 6.3
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---
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## Testing Status
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| Test Type | Status | Notes |
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|-----------|--------|-------|
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| **Syntax Validation** | ✅ COMPLETE | All queries SPARQL 1.1 compliant |
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| **Schema Compatibility** | ✅ COMPLETE | Verified against v0.7.0 RDF schema |
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| **Instance Data Testing** | ⚠️ DEFERRED | Requires YAML→RDF conversion (Phase 7) |
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**Note**: Full end-to-end testing requires converting test instances to RDF triples.
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---
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## Success Criteria - All Met ✅
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| Criterion | Target | Achieved | Status |
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|-----------|--------|----------|--------|
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| Query Count | 20+ | 31 | ✅ 155% |
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| Categories | 5 | 6 | ✅ 120% |
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| Examples | All queries | 31/31 | ✅ 100% |
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| Validation Queries | 5 rules | 5 queries | ✅ 100% |
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| Explanations | Clear | 31/31 | ✅ 100% |
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---
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## What's Next: Phase 7 - SHACL Shapes
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### Objective
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Convert validation queries into **SHACL shapes** for automatic RDF validation at data ingestion time.
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### Why SHACL?
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- ✅ Prevent invalid data entry (not just detect)
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- ✅ Standardized validation reports
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- ✅ Triple store integration (GraphDB, Jena)
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- ✅ Detailed error messages
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### Deliverables (Phase 7)
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1. SHACL shape file: `schemas/20251121/shacl/custodian_validation_shapes.ttl`
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2. Documentation: `docs/SHACL_VALIDATION_SHAPES.md`
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3. Validation script: `scripts/validate_with_shacl.py`
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### Estimated Time
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60-75 minutes
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---
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## References
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- **Query Library**: `docs/SPARQL_QUERIES_ORGANIZATIONAL.md`
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- **Completion Report**: `SPARQL_QUERY_LIBRARY_COMPLETE_20251122.md`
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- **Schema (v0.7.0)**: `schemas/20251121/linkml/01_custodian_name_modular.yaml`
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- **Test Data**: `schemas/20251121/examples/collection_department_integration_examples.yaml`
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- **Phase 5 Summary**: `SESSION_SUMMARY_VALIDATION_PHASE5_20251122.md`
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---
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**Phase 6 Status**: ✅ **COMPLETE**
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**Next Phase**: Phase 7 - SHACL Shapes
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**Overall Progress**: 6/9 phases complete (67%)
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