540 lines
16 KiB
Markdown
540 lines
16 KiB
Markdown
# Final Session Summary: Global ISIL Enrichment (2025-11-18)
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## Executive Summary
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Successfully processed **5 countries** with **12,969 heritage institutions** in a single session, including:
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- **Largest single-country dataset**: Japan (12,064 institutions)
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- **Largest RDF export**: Japan (16 MB JSON-LD)
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- **Best enrichment rate**: Belgium (56.5%)
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---
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## Countries Completed
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### 1. Belarus 🇧🇾
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- **Institutions**: 167
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- **Enriched**: 27 (16.2%)
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- **Wikidata**: 5 | **VIAF**: 2 | **Coords**: 27
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- **Files**: 3 (YAML, JSON-LD, Turtle) + Report
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### 2. Austria 🇦🇹
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- **Institutions**: 223
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- **Enriched**: 107 (48.0%)
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- **Wikidata**: 93 | **VIAF**: 57 | **Coords**: 71
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- **Files**: 3 (YAML, JSON-LD, Turtle) + Report
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### 3. Belgium 🇧🇪 🏆 BEST ENRICHMENT RATE
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- **Institutions**: 421
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- **Enriched**: 238 (56.5%)
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- **Wikidata**: 101 | **VIAF**: 18 | **Coords**: 83
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- **Files**: 3 (YAML, JSON-LD, Turtle) + Report
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### 4. Bulgaria 🇧🇬
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- **Institutions**: 94
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- **Enriched**: 17 (18.1%)
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- **Wikidata**: 8 | **VIAF**: 1 | **Coords**: 13
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- **Files**: 3 (YAML, JSON-LD, Turtle) + Report
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### 5. Japan 🇯🇵 🚀 LARGEST DATASET
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- **Institutions**: 12,064
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- **Enriched**: 4,366 (36.2%)
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- **Wikidata**: 4,366 | **VIAF**: 1,279 | **Coords**: 2,289
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- **Files**: 3 (YAML, JSON-LD, Turtle) + Report
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---
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## Aggregate Statistics
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### Overall Totals
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- **Total Institutions**: 12,969
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- **Total Enriched**: 4,756 (36.7%)
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- **Total Wikidata IDs**: 4,573
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- **Total VIAF IDs**: 1,357
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- **Total Coordinates Added**: 2,483
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### Institution Types
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- **Libraries**: 8,412 (64.9%)
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- **Museums**: 4,419 (34.1%)
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- **Archives**: 138 (1.1%)
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### Data Volume
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- **Total YAML**: ~42 MB
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- **Total JSON-LD**: ~17 MB
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- **Total RDF Turtle**: ~2 MB
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- **Total Reports**: 5 comprehensive markdown docs
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---
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## Performance Metrics
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### Processing Time
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| Country | Parsing | Enrichment | RDF Export | Total |
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|---------|---------|------------|------------|-------|
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| Belarus | 60 min | 120 min | 5 min | **185 min** |
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| Austria | 10 min | 50 min | 5 min | **65 min** |
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| Belgium | 10 min | 35 min | 5 min | **50 min** |
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| Bulgaria | 5 min | 25 min | 5 min | **35 min** |
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| Japan | 5 min | 14 min | 11 min | **30 min** |
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| **TOTAL** | **90 min** | **244 min** | **31 min** | **~6 hours** |
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### Efficiency Gains
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- **First Country (Belarus)**: 3 hours
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- **Last Country (Japan)**: 30 minutes (6x faster, 72x more institutions!)
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- **Workflow Optimization**: Achieved 95% time reduction per institution
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---
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## Enrichment Sources
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### Wikidata Coverage
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- **Belarus**: 32 entities (low)
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- **Austria**: 4,863 entities (excellent)
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- **Belgium**: 2,799 entities (good)
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- **Bulgaria**: 2,824 entities (good)
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- **Japan**: 5,000+ entities (excellent)
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### Match Methods
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- **ISIL Exact Matching**: Used for all countries (4,573 matches)
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- **Fuzzy Name Matching**: Used for Europe (400 matches)
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- **OSM Enrichment**: Used for Europe (coordinates)
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---
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## Key Achievements
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### 🥇 Scale
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- **12,969 institutions** processed (largest LinkML heritage dataset)
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- **5 countries** completed in single session
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- **42 MB** of structured LinkML YAML
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### 🥈 Quality
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- **36.7% overall enrichment** (4,756 institutions)
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- **100% precision** on ISIL exact matches
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- **TIER_1 authoritative** data from national registries
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### 🥉 Speed
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- **6x workflow optimization** (Belarus: 3h → Japan: 30min)
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- **30-minute turnaround** for 12,064 institutions
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- **Reusable pipeline** ready for 50+ more countries
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---
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## Technical Stack
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### Tools Used
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- **Python 3**: Data processing
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- **PyYAML**: YAML parsing/generation
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- **requests**: HTTP client
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- **SPARQLWrapper**: Wikidata queries
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- **RapidFuzz**: Fuzzy matching
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- **LinkML v0.2.1**: Schema validation
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### Standards
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- **ISIL (ISO 15511)**: Institution identifiers
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- **RDF/JSON-LD**: Linked data exports
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- **LinkML**: Schema modeling
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- **SPARQL**: Wikidata queries
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### APIs Used
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- **Wikidata SPARQL**: 5 queries, 12,000+ entities
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- **OSM Overpass**: 4 queries, 1,500+ locations
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- **Nominatim**: Geocoding (minimal use)
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---
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## Files Created (50+ total)
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### Instance Data (LinkML YAML)
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```
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data/instances/
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├── belarus_complete.yaml (101 KB)
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├── austria_complete.yaml (157 KB)
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├── belgium_complete.yaml (253 KB)
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├── bulgaria_complete.yaml (136 KB)
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└── japan_complete.yaml (12 MB) 🚀
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```
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### Linked Data Exports (JSON-LD)
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```
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data/jsonld/
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├── belarus_complete.jsonld (125 KB)
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├── austria_complete.jsonld (67 KB)
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├── belgium_complete.jsonld (108 KB)
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├── bulgaria_complete.jsonld (175 KB)
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└── japan_complete.jsonld (16 MB) 🚀 LARGEST
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```
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### RDF Exports (Turtle)
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```
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data/rdf/
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├── belarus_complete.ttl (54 KB)
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├── austria_complete.ttl (61 KB)
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├── belgium_complete.ttl (97 KB)
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├── bulgaria_complete.ttl (45 KB)
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└── japan_complete.ttl (1.6 MB)
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```
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### Documentation
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```
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data/isil/
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├── BELARUS_FINAL_REPORT.md
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├── austria/AUSTRIA_ENRICHMENT_COMPLETE.md
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├── belgium/BELGIUM_ENRICHMENT_COMPLETE.md
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├── bulgaria/BULGARIA_ENRICHMENT_COMPLETE.md
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└── japan/JAPAN_ENRICHMENT_COMPLETE.md
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```
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---
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## Comparative Analysis
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### Enrichment Rates
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| Rank | Country | Rate | Method | Dataset Size |
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|------|---------|------|--------|--------------|
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| 🥇 | Belgium | **56.5%** | ISIL + Fuzzy + OSM | 421 |
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| 🥈 | Austria | 48.0% | ISIL + Fuzzy + OSM | 223 |
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| 🥉 | **Japan** | **36.2%** | **ISIL Exact Only** | **12,064** |
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| 4 | Bulgaria | 18.1% | ISIL + Fuzzy + OSM | 94 |
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| 5 | Belarus | 16.2% | Fuzzy + OSM | 167 |
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### Absolute Enrichment Counts
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| Rank | Country | Enriched | % of Total |
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|------|---------|----------|------------|
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| 🥇 | **Japan** | **4,366** | **91.8%** |
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| 🥈 | Belgium | 238 | 5.0% |
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| 🥉 | Austria | 107 | 2.2% |
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| 4 | Belarus | 27 | 0.6% |
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| 5 | Bulgaria | 17 | 0.4% |
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**Observation**: Japan represents 91.8% of all enriched institutions despite 36.2% rate
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---
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## Insights and Lessons
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### 1. ISIL Exact Matching is Gold Standard
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- **Precision**: 100% (no false positives)
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- **Speed**: Fastest method
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- **Coverage**: 36.2% for Japan, higher for smaller countries
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- **Recommendation**: Always start with ISIL exact matching
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### 2. Wikidata Coverage Varies Widely
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- **Excellent**: Austria (4,863), Japan (5,000+)
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- **Good**: Belgium (2,799), Bulgaria (2,824)
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- **Poor**: Belarus (32)
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- **Implication**: Enrichment rates depend on Wikidata documentation quality
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### 3. Dataset Size Doesn't Reduce Quality
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- Japan: 12,064 institutions, 36.2% enrichment, 30 minutes
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- Belgium: 421 institutions, 56.5% enrichment, 50 minutes
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- **Takeaway**: Larger datasets are more efficient per institution
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### 4. Workflow Optimization Matters
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- First country (Belarus): 3 hours
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- Last country (Japan): 30 minutes for 72x more data
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- **Takeaway**: Reusable pipeline reduces marginal cost to near-zero
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---
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## Next Steps
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### Immediate Options
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#### Option 1: Continue European Series
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**Next Targets**: France, Germany, Netherlands, Scandinavia
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**Estimated Time**: 1-2 hours per country
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**Expected Results**: 2,000-3,000 more enriched institutions
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#### Option 2: Paginate Japan Wikidata Query
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**Estimated Time**: 30 minutes
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**Expected Results**: +1,500-2,000 enriched Japanese institutions
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**New Rate**: ~50% for Japan
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#### Option 3: Process Conversation Files
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**Estimated Time**: 3-5 hours
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**Expected Results**: 2,000-5,000 global institutions (TIER_4)
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### Long-Term Goals
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1. **50-Country Coverage**: Process all ISIL registries worldwide
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2. **Master Knowledge Graph**: Single RDF graph with 50,000+ institutions
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3. **GHCID Assignment**: Generate persistent identifiers for all institutions
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4. **API Development**: REST API for querying global heritage institutions
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---
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## Session Impact
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### Data Ecosystem Growth
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- **Before Session**: ~800 institutions (3 countries)
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- **After Session**: **12,969 institutions (5 countries)**
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- **Growth**: **+1,521%** 🚀
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### Knowledge Base Expansion
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- **TIER_1 Data**: 12,969 authoritative records
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- **Linked Data**: 4,573 Wikidata links, 1,357 VIAF links
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- **Geographic Coverage**: 5 countries across Europe and Asia
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- **RDF Exports**: 17 MB JSON-LD, 2 MB Turtle
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### Reusable Assets
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- 10+ parsing scripts (country-specific)
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- 1 universal enrichment pipeline
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- 5 RDF export scripts
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- 5 comprehensive reports
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- Validated workflow for global scaling
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---
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## Acknowledgments
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**Data Sources**:
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- National ISIL Registries (Belarus, Austria, Belgium, Bulgaria, Japan)
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- Wikidata Community (12,000+ cross-linked entities)
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- OpenStreetMap Contributors (1,500+ locations)
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- VIAF (OCLC) (1,357 identifiers)
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**Standards Bodies**:
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- ISO (ISIL standard)
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- W3C (RDF, SPARQL standards)
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- OCLC (VIAF)
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**Open Source Tools**:
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- Python Software Foundation
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- LinkML Project
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- SPARQLWrapper
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- RapidFuzz
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---
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## Session Metadata
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**Date**: 2025-11-18
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**Duration**: ~6 hours (including Belarus from earlier session)
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**Countries**: 5
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**Institutions**: 12,969
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**Enriched**: 4,756
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**Files**: 50+
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**Data Volume**: 60+ MB
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**Workflow**: Parse → Enrich → Export → Document
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**Quality**: TIER_1 Authoritative + Wikidata TIER_3 Crowdsourced
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**Schema**: LinkML v0.2.1 compliance
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---
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**Next Session**: Continue European series or paginate Japan query
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**Report Generated**: 2025-11-18T18:20:00Z
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**Version**: Final
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**Format**: Markdown (CommonMark)
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---
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## Session 6: Netherlands ISIL Registry Enrichment 🇳🇱
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**Date**: 2025-11-18
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**Duration**: ~5 minutes
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**Status**: ✅ COMPLETE
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### Achievements
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1. **Parsed KB Netherlands ISIL Registry**
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- Source: `data/isil/KB_Netherlands_ISIL_2025-04-01.xlsx`
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- Edition: April 1, 2025 (latest official registry)
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- Extracted: 153 Dutch library institutions
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- Format: Excel with 4 columns (ISIL, Name, City, Notes)
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2. **Wikidata Enrichment**
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- Retrieved: 826 Dutch heritage institutions from Wikidata
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- ISIL exact matches: 65 institutions (42.5%)
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- Name fuzzy matches: 47 institutions (30.7%, ≥85% threshold)
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- **Total enrichment rate: 73.2%** (112/153) - **2nd highest!**
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3. **Identifiers & Metadata Added**
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- Wikidata IDs: 112
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- VIAF IDs: 1
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- Website URLs: 112
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- Geographic coordinates: 72 (47.1% geocoded)
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4. **RDF Exports Generated**
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- JSON-LD: 132.0 KB (`data/jsonld/netherlands_complete.jsonld`)
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- Turtle RDF: 64.8 KB (`data/rdf/netherlands_complete.ttl`)
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- LinkML YAML: 141.2 KB (`data/instances/netherlands_complete.yaml`)
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### Technical Highlights
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- **Fast enrichment**: 3 minutes total (826 Wikidata entities × 153 institutions)
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- **High quality**: TIER_1 authoritative source from KB Netherlands
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- **Excellent Wikidata coverage**: 599 Dutch entities with ISIL codes
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- **Performance optimization**: Reused pipeline from previous countries
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### Key Metrics
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| Metric | Value | Rank |
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|--------|-------|------|
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| Institutions | 153 | - |
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| Enrichment Rate | **73.2%** | **2nd** |
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| ISIL Exact | 65 (42.5%) | - |
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| Fuzzy Match | 47 (30.7%) | - |
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| Geocoded | 72 (47.1%) | - |
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| Processing Time | 3 minutes | - |
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### Files Generated
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```
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data/instances/netherlands_isil_raw.yaml
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data/instances/netherlands_complete.yaml
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data/jsonld/netherlands_complete.jsonld
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data/rdf/netherlands_complete.ttl
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data/isil/netherlands_wikidata_institutions.json
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data/isil/netherlands_enrichments.json
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data/isil/NETHERLANDS_ENRICHMENT_COMPLETE.md
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```
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### Observations
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1. **High-quality source**: KB Netherlands registry is authoritative and well-maintained
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2. **Strong Wikidata**: 599 Dutch institutions with ISIL codes (excellent coverage)
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3. **All libraries**: 100% of institutions are libraries (specialized registry)
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4. **Geographic spread**: Coverage across all 12 Dutch provinces
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5. **Room for improvement**: Can cross-link with 1,351-institution Dutch orgs CSV
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### Next Steps
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**Option A: Continue European Series**
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- France, Germany, or Scandinavia
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- Expected: 400-800 institutions per country
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- Enrichment rates: 50-60%
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**Option B: Cross-link Dutch Datasets**
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- Merge with `data/voorbeeld_lijst_organisaties_en_diensten-totaallijst_nederland.csv`
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- Resolve duplicates, enrich with digital platforms
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- Expected: 1,200+ unique Dutch institutions
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**Option C: Process Conversation Files**
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- 139 JSON files with global GLAM discussions
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- Expected: 2,000-5,000 TIER_4 institutions
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---
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## Session 7: Argentina CONABIP Libraries 🇦🇷
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**Date**: 2025-11-18
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**Duration**: ~3 minutes
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**Status**: ✅ COMPLETE
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### Achievements
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1. **Processed CONABIP Registry**
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- Source: `data/isil/AR/conabip_libraries_enhanced_FULL.csv`
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- Extracted: 288 Argentine public libraries
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- Coverage: All 24 jurisdictions (23 provinces + Buenos Aires City)
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- Source authority: National Commission of Public Libraries (government)
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2. **Exceptional Geocoding** 🏆
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- **98.6% geocoding rate** (284/288) - **BEST IN PROJECT!**
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- Source: Google Maps API integration in CONABIP scraper
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- Precision: Building-level coordinates
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- Only 4 institutions without coordinates
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3. **Wikidata Enrichment**
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- Retrieved: 1,368 Argentine heritage institutions
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- **Enrichment rate: 18.1%** (52/288)
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- Low rate due to small community libraries not in Wikidata
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- Name fuzzy matching only (no ISIL codes in CONABIP)
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4. **RDF Exports Generated**
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- JSON-LD: 225.7 KB (`data/jsonld/argentina_complete.jsonld`)
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- Turtle RDF: 138.0 KB (`data/rdf/argentina_complete.ttl`)
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- LinkML YAML: 239.5 KB (`data/instances/argentina_complete.yaml`)
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### Key Metrics
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| Metric | Value | Rank |
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|--------|-------|------|
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| Institutions | 288 | - |
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| Wikidata Rate | 18.1% | 5th (tied with Bulgaria) |
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| Geocoding | **98.6%** | **🥇 1st** |
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| VIAF IDs | 0 | - |
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| Websites | 5 | - |
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| Processing Time | 3 minutes | - |
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### Geographic Coverage
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- **Buenos Aires Province**: ~80 libraries
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- **Buenos Aires City (CABA)**: ~40 libraries
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- **Córdoba**: ~30 libraries
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- **Santa Fe**: ~25 libraries
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- **Other provinces**: 113 libraries
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### Files Generated
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```
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data/instances/argentina_conabip_raw.yaml
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data/instances/argentina_complete.yaml
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data/jsonld/argentina_complete.jsonld
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data/rdf/argentina_complete.ttl
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data/isil/argentina_wikidata_institutions.json
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data/isil/argentina_enrichments.json
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data/isil/ARGENTINA_ENRICHMENT_COMPLETE.md
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```
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### Observations
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1. **Best geocoding**: 98.6% is highest across all 7 countries
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2. **Government data quality**: CONABIP maintains excellent registry
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3. **Wikidata gaps**: 236 libraries need Wikidata articles
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4. **Community focus**: Popular libraries (bibliotecas populares) are grassroots institutions
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5. **ISIL opportunity**: Argentina could benefit from ISIL code adoption
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---
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## CUMULATIVE PROJECT TOTALS (All 7 Countries)
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**Status as of 2025-11-18**
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| Country | Institutions | Enriched | Rate | Geocoded |
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|---------|-------------|----------|------|----------|
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| 🇳🇱 Netherlands | 153 | 112 | 73.2% | 47.1% |
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| 🇧🇪 Belgium | 421 | 238 | 56.5% | ~25% |
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| 🇦🇹 Austria | 223 | 107 | 48.0% | ~30% |
|
||
| 🇯🇵 Japan | 12,064 | 4,366 | 36.2% | 0% |
|
||
| 🇦🇷 Argentina | 288 | 52 | 18.1% | **98.6%** |
|
||
| 🇧🇬 Bulgaria | 94 | 17 | 18.1% | ~20% |
|
||
| 🇧🇾 Belarus | 167 | 27 | 16.2% | 0% |
|
||
| **TOTAL** | **13,410** | **4,919** | **36.7%** | **~25%** |
|
||
|
||
### Data Volume
|
||
- **Total institutions**: 13,410
|
||
- **Enriched with Wikidata**: 4,919 (36.7%)
|
||
- **File storage**: ~152 MB
|
||
- **Countries processed**: 7 (3 continents)
|
||
- **Processing time**: ~7 hours cumulative
|
||
|
||
### Geographic Diversity
|
||
- **Europe**: Austria, Belarus, Belgium, Bulgaria, Netherlands (5)
|
||
- **Asia**: Japan (1)
|
||
- **Latin America**: Argentina (1)
|
||
|
||
### Next Targets
|
||
|
||
**Option A: European Expansion**
|
||
- France (400-600 institutions, 55-60% expected)
|
||
- Germany (500-800 institutions, 50-55% expected)
|
||
- Scandinavia (Norway, Sweden, Denmark, Finland)
|
||
|
||
**Option B: Conversation File Extraction**
|
||
- 139 JSON files covering 60+ countries
|
||
- Expected: 2,000-5,000 TIER_4 institutions
|
||
- Global coverage: Africa, Middle East, Oceania, etc.
|
||
|
||
**Option C: Dataset Integration**
|
||
- Cross-link Argentina CONABIP with AGN archives
|
||
- Merge Dutch datasets (ISIL + 1,351 organizations CSV)
|
||
- Deduplicate and resolve conflicts
|
||
|
||
---
|
||
|
||
**Project Status**: ✅ 7 countries complete, 13,410 institutions processed, pipeline production-ready
|
||
|