# Denmark GLAM Dataset - Quick Reference Card

**Last Updated**: 2025-11-19  
**Status**: ✅ Complete (2,348 institutions)

---

## Files at a Glance

| File | Institutions | Size | Purpose |
|------|--------------|------|---------|
| `denmark_complete.json` | **2,348** | 3.06 MB | ⭐ **MASTER FILE** - Use this |
| `denmark_libraries_v2.json` | 555 | 964 KB | Main libraries only |
| `denmark_archives.json` | 594 | 918 KB | Archives only |
| `denmark_library_branches.json` | 1,199 | 1.2 MB | Library branches only |

**Location**: `/Users/kempersc/apps/glam/data/instances/`

---

## Quick Statistics

```
Total Institutions: 2,348
├── Libraries (main): 555
│   ├── Public libraries: 108
│   └── Research libraries (FFU): 447
├── Archives: 594
└── Library branches: 1,199
    ├── Public branches: 594
    └── FFU branches: 605

GHCID Coverage: 998/2,348 (42.5%)
ISIL Coverage: 555/2,348 (23.6%)
Hierarchical Links: 1,176/1,199 (98.1%)
```

---

## Common Queries

### Load complete dataset
```python
import json
with open('data/instances/denmark_complete.json', 'r') as f:
    danish_glam = json.load(f)
```

### Filter by institution type
```python
archives = [i for i in danish_glam if i['institution_type'] == 'ARCHIVE']
libraries = [i for i in danish_glam if i['institution_type'] == 'LIBRARY']
main_libs = [i for i in libraries if not i.get('parent_organization')]
branches = [i for i in libraries if i.get('parent_organization')]
```

### Find institutions by city
```python
copenhagen = [
    i for i in danish_glam 
    if any(loc.get('city') == 'København K' for loc in i.get('locations', []))
]
```

### Get institutions with GHCID
```python
with_ghcid = [i for i in danish_glam if i.get('ghcid_current')]
```

### Get hierarchical structure (library + branches)
```python
def get_library_with_branches(library_id):
    """Get a library and all its branches."""
    library = next(i for i in danish_glam if i['id'] == library_id)
    branches = [
        i for i in danish_glam 
        if i.get('parent_organization') == library_id
    ]
    return {'library': library, 'branches': branches}

# Example
kb_system = get_library_with_branches(
    'https://w3id.org/heritage/custodian/dk/library/k%C3%B8benhavn-k/k%C3%B8benhavns-biblioteker'
)
print(f"{kb_system['library']['name']}: {len(kb_system['branches'])} branches")
```

---

## Top Cities

| City | Count | City | Count |
|------|-------|------|-------|
| Aalborg | 35 | København K | 30 |
| Esbjerg | 30 | Hjørring | 28 |
| Vejle | 28 | Herning | 26 |
| Aarhus | 22 | Ringkøbing-Skjern | 22 |

---

## Next Steps

**For RDF Export**:
```bash
# Generate Turtle RDF
linkml-convert -s schemas/heritage_custodian.yaml -t rdf \
  data/instances/denmark_complete.json > data/rdf/denmark.ttl
```

**For Wikidata Enrichment**:
```bash
# Query Wikidata for Danish institutions
python3 scripts/enrich_denmark_wikidata.py
```

**For Analysis**:
```bash
# Generate statistics report
python3 scripts/analyze_denmark_dataset.py
```

---

## Key Design Decisions

✅ **Library branches use parent_organization** - Reduces redundancy  
✅ **Archives get GHCID (no ISIL)** - GHCID is primary identifier  
✅ **Nordic characters normalized** - æ→ae, ø→oe, å→aa in GHCID  
✅ **98.1% hierarchical linkage** - Near-perfect parent-child matching  

---

## Session Documents

- `SESSION_SUMMARY_20251119_DENMARK_COMPLETE.md` - Full session report
- `SESSION_SUMMARY_20251119_DENMARK_ARCHIVES_COMPLETE.md` - Archive processing
- `SESSION_SUMMARY_20251119_DENMARK_ISIL_COMPLETE.md` - Library processing

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**Questions?** See `SESSION_SUMMARY_20251119_DENMARK_COMPLETE.md` for detailed documentation.