# 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 `PersonObservation` class
- 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

1. **`docs/SPARQL_QUERIES_ORGANIZATIONAL.md`** (1,168 lines)
   - 31 complete SPARQL queries
   - Expected results + explanations
   - Query optimization guidelines
   - Testing instructions

2. **`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)
```sparql
# 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
```sparql
# Detect missing inverse relationships
FILTER NOT EXISTS {
  ?unit custodian:managed_collections ?collection
}
```

Used in: Queries 5.2, 5.5

### Provenance Chain Reconstruction
```sparql
# 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)
1. SHACL shape file: `schemas/20251121/shacl/custodian_validation_shapes.ttl`
2. Documentation: `docs/SHACL_VALIDATION_SHAPES.md`
3. 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`

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**Phase 6 Status**: ✅ **COMPLETE**  
**Next Phase**: Phase 7 - SHACL Shapes  
**Overall Progress**: 6/9 phases complete (67%)