feat(scripts): Add batch crawling and data quality scripts

- batch_crawl4ai_recrawl.py: Retry failed URL crawls
- batch_firecrawl_recrawl.py: FireCrawl batch processing
- batch_httpx_scrape.py: HTTPX-based scraping
- detect_name_mismatch.py: Find name mismatches in data
- enrich_dutch_custodians_crawl4ai.py: Dutch custodian enrichment
- fix_collision_victims.py: GHCID collision resolution
- fix_generic_platform_names*.py: Platform name cleanup
- fix_ghcid_type.py: GHCID type corrections
- fix_simon_kemper_contamination.py: Data cleanup
- scan_dutch_data_quality.py: Data quality scanning
- transform_crawl4ai_to_digital_platform.py: Data transformation

scripts/batch_crawl4ai_recrawl.py

@@ -0,0 +1,371 @@
+#!/usr/bin/env python3
+"""
+Batch re-crawl failed URLs using crawl4ai (free, local) and transform to digital_platform_v2.
+
+This script:
+1. Reads the list of failed crawl URLs
+2. Uses crawl4ai to fetch content (free, no API limits)
+3. Transforms results to digital_platform_v2 format
+4. Updates the custodian YAML files
+
+Usage:
+    python scripts/batch_crawl4ai_recrawl.py --limit 100 --start 0
+"""
+
+import argparse
+import asyncio
+import re
+import sys
+from datetime import datetime, timezone
+from pathlib import Path
+from typing import Any
+from urllib.parse import urlparse
+
+import yaml
+from crawl4ai import AsyncWebCrawler
+
+# Configuration
+CUSTODIAN_DIR = Path("/Users/kempersc/apps/glam/data/custodian")
+FAILED_URLS_FILE = Path("/Users/kempersc/apps/glam/data/failed_crawl_urls.txt")
+
+# Platform type detection patterns
+PLATFORM_PATTERNS = {
+    'DISCOVERY_PORTAL': [
+        r'/collectie', r'/collection', r'/catalogus', r'/catalog',
+        r'/zoeken', r'/search', r'/archief', r'/archive',
+        r'/beeldbank', r'/images', r'/foto', r'/photo',
+    ],
+    'DIGITAL_ARCHIVE': [
+        r'archieven\.nl', r'archief', r'archive',
+        r'/inventaris', r'/inventory', r'/toegang',
+    ],
+    'EDUCATION': [
+        r'/educatie', r'/education', r'/onderwijs', r'/leren',
+        r'/scholen', r'/schools', r'/lesmateriaal',
+    ],
+    'INSTITUTIONAL_WEBSITE': [
+        r'/over-ons', r'/about', r'/contact', r'/bezoek',
+        r'/visit', r'/openingstijden', r'/hours',
+    ],
+}
+
+
+def detect_platform_type(url: str, links: list[str] | None = None) -> str:
+    """Detect the platform type based on URL patterns and extracted links."""
+    url_lower = url.lower()
+    all_urls = [url_lower] + [l.lower() for l in (links or [])]
+    
+    for platform_type, patterns in PLATFORM_PATTERNS.items():
+        for pattern in patterns:
+            for check_url in all_urls:
+                if re.search(pattern, check_url):
+                    return platform_type
+    
+    return 'INSTITUTIONAL_WEBSITE'
+
+
+def extract_collection_urls(links: list[str], base_url: str) -> list[str]:
+    """Extract URLs that appear to be collection/catalog pages."""
+    collection_patterns = [
+        r'/collectie', r'/collection', r'/catalogus', r'/catalog',
+        r'/zoeken', r'/search', r'/beeldbank', r'/inventaris',
+        r'/archief(?!en\.)', r'/archiefstukken', r'/toegangen',
+    ]
+    
+    collection_urls = []
+    base_domain = urlparse(base_url).netloc
+    
+    for link in links:
+        try:
+            parsed = urlparse(link)
+            if base_domain in parsed.netloc or parsed.netloc in base_domain:
+                for pattern in collection_patterns:
+                    if re.search(pattern, link.lower()):
+                        if link not in collection_urls:
+                            collection_urls.append(link)
+                        break
+        except Exception:
+            continue
+    
+    return collection_urls[:10]
+
+
+def extract_auxiliary_platforms(links: list[str], base_url: str) -> list[dict]:
+    """Extract external platform links (aggregators, portals, etc.)."""
+    external_patterns = {
+        'archieven.nl': {'name': 'Archieven.nl', 'type': 'AGGREGATOR'},
+        'europeana.eu': {'name': 'Europeana', 'type': 'AGGREGATOR'},
+        'collectienederland.nl': {'name': 'Collectie Nederland', 'type': 'AGGREGATOR'},
+        'erfgoedthesaurus.nl': {'name': 'Erfgoedthesaurus', 'type': 'THESAURUS'},
+        'delpher.nl': {'name': 'Delpher', 'type': 'DIGITAL_ARCHIVE'},
+        'geheugen.nl': {'name': 'Geheugen van Nederland', 'type': 'AGGREGATOR'},
+    }
+    
+    base_domain = urlparse(base_url).netloc
+    auxiliary = []
+    seen_domains = set()
+    
+    for link in links:
+        try:
+            parsed = urlparse(link)
+            domain = parsed.netloc.replace('www.', '')
+            
+            if base_domain in domain or domain in base_domain:
+                continue
+            
+            for pattern, info in external_patterns.items():
+                if pattern in domain and domain not in seen_domains:
+                    seen_domains.add(domain)
+                    auxiliary.append({
+                        'platform_name': info['name'],
+                        'platform_url': link,
+                        'platform_type': info['type'],
+                        'integration_type': 'external_aggregator',
+                    })
+                    break
+        except Exception:
+            continue
+    
+    return auxiliary[:5]
+
+
+def is_generic_title(title: str) -> bool:
+    """Check if a title is too generic to use as platform name."""
+    generic_patterns = [
+        'home', 'homepage', 'welkom', 'welcome', 'startpagina',
+        'index', 'main', 'website', 'webpagina', 'homepagina',
+    ]
+    if not title:
+        return True
+    title_lower = title.lower().strip()
+    for pattern in generic_patterns:
+        if title_lower == pattern or title_lower.startswith(f"{pattern} -") or title_lower.startswith(f"{pattern} |"):
+            return True
+    return len(title) < 3
+
+
+def transform_to_platform_v2(crawl_result, source_url: str, org_name: str) -> dict[str, Any]:
+    """Transform crawl4ai result to digital_platform_v2 format."""
+    metadata = crawl_result.metadata or {}
+    
+    # Get internal links
+    internal_links = []
+    if crawl_result.links:
+        internal_links = [l.get('href', '') for l in crawl_result.links.get('internal', []) if l.get('href')]
+    
+    # Extract title, checking for generic titles
+    candidate_titles = [
+        metadata.get('og:title'),
+        metadata.get('title', '').split(' - ')[0].strip(),
+        metadata.get('title', '').split(' | ')[0].strip(),
+        metadata.get('og:site_name'),
+    ]
+    
+    title = org_name  # Default fallback
+    for candidate in candidate_titles:
+        if candidate and not is_generic_title(candidate):
+            title = candidate
+            break
+    
+    # Generate platform ID
+    domain = urlparse(source_url).netloc.replace('www.', '').replace('.', '_')
+    platform_id = f"primary_website_{domain}"
+    
+    # Detect platform type
+    platform_type = detect_platform_type(source_url, internal_links)
+    
+    # Extract collection URLs
+    collection_urls = extract_collection_urls(internal_links, source_url)
+    
+    # Extract auxiliary platforms
+    auxiliary_platforms = extract_auxiliary_platforms(internal_links, source_url)
+    
+    # Build digital_platform_v2 structure
+    platform_v2: dict[str, Any] = {
+        'transformation_metadata': {
+            'transformed_from': 'crawl4ai_recrawl',
+            'transformation_date': datetime.now(timezone.utc).isoformat(),
+            'transformation_version': '2.0',
+            'source_status_code': crawl_result.status_code,
+        },
+        'primary_platform': {
+            'platform_id': platform_id,
+            'platform_name': f"{title} Website" if 'website' not in title.lower() else title,
+            'platform_url': source_url,
+            'platform_type': platform_type,
+            'description': metadata.get('description') or metadata.get('og:description', ''),
+            'language': metadata.get('language', 'nl'),
+            'og_image': metadata.get('og:image'),
+            'favicon': metadata.get('favicon'),
+        },
+    }
+    
+    if collection_urls:
+        platform_v2['primary_platform']['collection_urls'] = collection_urls
+    
+    if auxiliary_platforms:
+        platform_v2['auxiliary_platforms'] = auxiliary_platforms
+    
+    if internal_links:
+        platform_v2['navigation_links'] = internal_links[:20]
+    
+    return platform_v2
+
+
+def update_custodian_file(filepath: Path, platform_v2: dict) -> bool:
+    """Update a custodian YAML file with digital_platform_v2 data."""
+    try:
+        with open(filepath, 'r') as f:
+            data = yaml.safe_load(f)
+        
+        if data is None:
+            data = {}
+        
+        data['digital_platform_v2'] = platform_v2
+        
+        if 'crawl4ai_enrichment' in data:
+            data['crawl4ai_enrichment']['recrawled_with'] = 'crawl4ai_v2'
+            data['crawl4ai_enrichment']['recrawl_date'] = datetime.now(timezone.utc).isoformat()
+        
+        with open(filepath, 'w') as f:
+            yaml.dump(data, f, default_flow_style=False, allow_unicode=True, sort_keys=False)
+        
+        return True
+        
+    except Exception as e:
+        print(f"  Error updating {filepath}: {e}")
+        return False
+
+
+def load_failed_urls() -> list[tuple[str, str]]:
+    """Load the list of failed URLs with their file paths."""
+    urls = []
+    with open(FAILED_URLS_FILE, 'r') as f:
+        for line in f:
+            line = line.strip()
+            if '\t' in line:
+                filename, url = line.split('\t', 1)
+                urls.append((filename, url))
+    return urls
+
+
+def get_org_name(filepath: Path) -> str:
+    """Extract organization name from custodian file."""
+    try:
+        with open(filepath, 'r') as f:
+            data = yaml.safe_load(f)
+        
+        if data:
+            if 'original_entry' in data and data['original_entry'].get('organisatie'):
+                return data['original_entry']['organisatie']
+            if 'custodian_name' in data:
+                return data['custodian_name'].get('emic_name', '') or data['custodian_name'].get('preferred_name', '')
+            if 'name' in data:
+                return data['name']
+        
+        stem = filepath.stem
+        parts = stem.split('-')
+        return parts[-1] if parts else stem
+        
+    except Exception:
+        return filepath.stem
+
+
+async def scrape_single_url(crawler: AsyncWebCrawler, url: str) -> Any:
+    """Scrape a single URL using crawl4ai."""
+    try:
+        result = await crawler.arun(url, verbose=False)
+        if result.success:
+            return result
+        print(f"  Crawl failed: {result.error_message}")
+        return None
+    except Exception as e:
+        print(f"  Exception: {e}")
+        return None
+
+
+async def main_async(args):
+    """Async main function."""
+    all_urls = load_failed_urls()
+    print(f"Loaded {len(all_urls)} failed URLs")
+    
+    if args.limit > 0:
+        urls_to_process = all_urls[args.start:args.start + args.limit]
+    else:
+        urls_to_process = all_urls[args.start:]
+    
+    print(f"Processing {len(urls_to_process)} URLs (start={args.start}, limit={args.limit or 'all'})")
+    
+    if args.dry_run:
+        print("\n[DRY RUN MODE - No changes will be made]")
+        for filename, url in urls_to_process[:10]:
+            print(f"  Would scrape: {filename} -> {url}")
+        print(f"  ... and {len(urls_to_process) - 10} more")
+        return
+    
+    success_count = 0
+    fail_count = 0
+    skip_count = 0
+    
+    async with AsyncWebCrawler(verbose=False) as crawler:
+        for i, (filename, url) in enumerate(urls_to_process):
+            filepath = CUSTODIAN_DIR / filename
+            
+            print(f"\n[{i+1}/{len(urls_to_process)}] {filename}")
+            print(f"  URL: {url}")
+            
+            if not filepath.exists():
+                print(f"  SKIP: File not found")
+                skip_count += 1
+                continue
+            
+            # Check if already has digital_platform_v2
+            with open(filepath, 'r') as f:
+                content = f.read()
+                if 'digital_platform_v2:' in content:
+                    print(f"  SKIP: Already has digital_platform_v2")
+                    skip_count += 1
+                    continue
+            
+            org_name = get_org_name(filepath)
+            
+            result = await scrape_single_url(crawler, url)
+            
+            if result:
+                platform_v2 = transform_to_platform_v2(result, url, org_name)
+                
+                if update_custodian_file(filepath, platform_v2):
+                    success_count += 1
+                    print(f"  SUCCESS: {platform_v2['primary_platform']['platform_name']}")
+                else:
+                    fail_count += 1
+            else:
+                fail_count += 1
+                print(f"  FAILED: Could not scrape URL")
+            
+            # Small delay to be polite
+            await asyncio.sleep(args.delay)
+            
+            if (i + 1) % 50 == 0:
+                print(f"\n=== Progress: {i+1}/{len(urls_to_process)} (success={success_count}, skip={skip_count}, fail={fail_count}) ===\n")
+    
+    print(f"\n=== Final Results ===")
+    print(f"Success: {success_count}")
+    print(f"Skipped: {skip_count}")
+    print(f"Failed: {fail_count}")
+    print(f"Total: {len(urls_to_process)}")
+
+
+def main():
+    parser = argparse.ArgumentParser(description='Batch re-crawl failed URLs with crawl4ai')
+    parser.add_argument('--start', type=int, default=0, help='Starting index')
+    parser.add_argument('--limit', type=int, default=0, help='Maximum URLs to process (0=all)')
+    parser.add_argument('--dry-run', action='store_true', help='Print what would be done without making changes')
+    parser.add_argument('--delay', type=float, default=0.5, help='Delay between requests in seconds')
+    args = parser.parse_args()
+    
+    asyncio.run(main_async(args))
+
+
+if __name__ == '__main__':
+    main()

scripts/batch_firecrawl_recrawl.py

@@ -0,0 +1,434 @@
+#!/usr/bin/env python3
+"""
+Batch re-crawl failed URLs using Firecrawl and transform to digital_platform_v2.
+
+This script:
+1. Reads the list of failed crawl URLs
+2. Uses Firecrawl batch_scrape or individual scrape to fetch content
+3. Transforms results to digital_platform_v2 format
+4. Updates the custodian YAML files
+
+Usage:
+    python scripts/batch_firecrawl_recrawl.py --batch-size 50 --start 0
+
+Firecrawl API reference: https://docs.firecrawl.dev/api-reference/endpoint/scrape
+"""
+
+import argparse
+import json
+import os
+import re
+import sys
+import time
+from datetime import datetime, timezone
+from pathlib import Path
+from typing import Any
+from urllib.parse import urlparse
+
+import httpx
+import yaml
+
+# Configuration
+CUSTODIAN_DIR = Path("/Users/kempersc/apps/glam/data/custodian")
+FAILED_URLS_FILE = Path("/Users/kempersc/apps/glam/data/failed_crawl_urls.txt")
+FIRECRAWL_API_KEY = os.environ.get("FIRECRAWL_API_KEY", "")
+FIRECRAWL_BASE_URL = "https://api.firecrawl.dev/v1"
+
+# Platform type detection patterns
+PLATFORM_PATTERNS = {
+    'DISCOVERY_PORTAL': [
+        r'/collectie', r'/collection', r'/catalogus', r'/catalog',
+        r'/zoeken', r'/search', r'/archief', r'/archive',
+        r'/beeldbank', r'/images', r'/foto', r'/photo',
+    ],
+    'DIGITAL_ARCHIVE': [
+        r'archieven\.nl', r'archief', r'archive',
+        r'/inventaris', r'/inventory', r'/toegang',
+    ],
+    'EDUCATION': [
+        r'/educatie', r'/education', r'/onderwijs', r'/leren',
+        r'/scholen', r'/schools', r'/lesmateriaal',
+    ],
+    'INSTITUTIONAL_WEBSITE': [
+        r'/over-ons', r'/about', r'/contact', r'/bezoek',
+        r'/visit', r'/openingstijden', r'/hours',
+    ],
+}
+
+
+def detect_platform_type(url: str, links: list[str] | None = None) -> str:
+    """Detect the platform type based on URL patterns and extracted links."""
+    url_lower = url.lower()
+    all_urls = [url_lower] + [l.lower() for l in (links or [])]
+    
+    for platform_type, patterns in PLATFORM_PATTERNS.items():
+        for pattern in patterns:
+            for check_url in all_urls:
+                if re.search(pattern, check_url):
+                    return platform_type
+    
+    return 'INSTITUTIONAL_WEBSITE'
+
+
+def extract_collection_urls(links: list[str], base_url: str) -> list[str]:
+    """Extract URLs that appear to be collection/catalog pages."""
+    collection_patterns = [
+        r'/collectie', r'/collection', r'/catalogus', r'/catalog',
+        r'/zoeken', r'/search', r'/beeldbank', r'/inventaris',
+        r'/archief(?!en\.)', r'/archiefstukken', r'/toegangen',
+    ]
+    
+    collection_urls = []
+    base_domain = urlparse(base_url).netloc
+    
+    for link in links:
+        try:
+            parsed = urlparse(link)
+            # Only include links from same domain or subdomains
+            if base_domain in parsed.netloc or parsed.netloc in base_domain:
+                for pattern in collection_patterns:
+                    if re.search(pattern, link.lower()):
+                        if link not in collection_urls:
+                            collection_urls.append(link)
+                        break
+        except Exception:
+            continue
+    
+    return collection_urls[:10]  # Limit to 10 collection URLs
+
+
+def extract_auxiliary_platforms(links: list[str], base_url: str) -> list[dict]:
+    """Extract external platform links (aggregators, portals, etc.)."""
+    external_patterns = {
+        'archieven.nl': {'name': 'Archieven.nl', 'type': 'AGGREGATOR'},
+        'europeana.eu': {'name': 'Europeana', 'type': 'AGGREGATOR'},
+        'collectienederland.nl': {'name': 'Collectie Nederland', 'type': 'AGGREGATOR'},
+        'erfgoedthesaurus.nl': {'name': 'Erfgoedthesaurus', 'type': 'THESAURUS'},
+        'delpher.nl': {'name': 'Delpher', 'type': 'DIGITAL_ARCHIVE'},
+        'geheugen.nl': {'name': 'Geheugen van Nederland', 'type': 'AGGREGATOR'},
+        'archiefweb.eu': {'name': 'Archiefweb', 'type': 'DIGITAL_ARCHIVE'},
+    }
+    
+    base_domain = urlparse(base_url).netloc
+    auxiliary = []
+    seen_domains = set()
+    
+    for link in links:
+        try:
+            parsed = urlparse(link)
+            domain = parsed.netloc.replace('www.', '')
+            
+            # Skip if same domain as base URL
+            if base_domain in domain or domain in base_domain:
+                continue
+            
+            # Check for known external platforms
+            for pattern, info in external_patterns.items():
+                if pattern in domain and domain not in seen_domains:
+                    seen_domains.add(domain)
+                    auxiliary.append({
+                        'platform_name': info['name'],
+                        'platform_url': link,
+                        'platform_type': info['type'],
+                        'integration_type': 'external_aggregator',
+                    })
+                    break
+        except Exception:
+            continue
+    
+    return auxiliary[:5]  # Limit to 5 auxiliary platforms
+
+
+def is_generic_title(title: str) -> bool:
+    """Check if a title is too generic to use as platform name."""
+    generic_patterns = [
+        'home', 'homepage', 'welkom', 'welcome', 'startpagina',
+        'index', 'main', 'website', 'webpagina', 'web page',
+    ]
+    if not title:
+        return True
+    title_lower = title.lower().strip()
+    # Check if title is just one of the generic patterns
+    for pattern in generic_patterns:
+        if title_lower == pattern or title_lower == f"{pattern} -" or title_lower.startswith(f"{pattern} |"):
+            return True
+    return len(title) < 3
+
+
+def transform_to_platform_v2(scrape_result: dict, source_url: str, org_name: str) -> dict[str, Any]:
+    """Transform Firecrawl scrape result to digital_platform_v2 format."""
+    metadata = scrape_result.get('metadata', {})
+    links = scrape_result.get('links', [])
+    markdown = scrape_result.get('markdown', '')
+    
+    # Extract title from metadata, checking for generic titles
+    candidate_titles = [
+        metadata.get('ogTitle'),
+        metadata.get('title', '').split(' - ')[0].strip(),
+        metadata.get('title', '').split(' | ')[0].strip(),
+        metadata.get('og:title'),
+        metadata.get('ogSiteName'),
+        metadata.get('og:site_name'),
+    ]
+    
+    # Find first non-generic title
+    title = org_name  # Default fallback
+    for candidate in candidate_titles:
+        if candidate and not is_generic_title(candidate):
+            title = candidate
+            break
+    
+    # Generate platform ID
+    domain = urlparse(source_url).netloc.replace('www.', '').replace('.', '_')
+    platform_id = f"primary_website_{domain}"
+    
+    # Detect platform type
+    platform_type = detect_platform_type(source_url, links)
+    
+    # Extract collection URLs
+    collection_urls = extract_collection_urls(links, source_url)
+    
+    # Extract auxiliary platforms
+    auxiliary_platforms = extract_auxiliary_platforms(links, source_url)
+    
+    # Build digital_platform_v2 structure
+    platform_v2 = {
+        'transformation_metadata': {
+            'transformed_from': 'firecrawl_scrape',
+            'transformation_date': datetime.now(timezone.utc).isoformat(),
+            'transformation_version': '2.0',
+            'source_status_code': metadata.get('statusCode', 200),
+        },
+        'primary_platform': {
+            'platform_id': platform_id,
+            'platform_name': f"{title} Website" if 'website' not in title.lower() else title,
+            'platform_url': source_url,
+            'platform_type': platform_type,
+            'description': metadata.get('description') or metadata.get('ogDescription', ''),
+            'language': metadata.get('language', 'nl'),
+            'og_image': metadata.get('ogImage') or metadata.get('og:image'),
+            'favicon': metadata.get('favicon'),
+        },
+    }
+    
+    # Add collection URLs if found
+    if collection_urls:
+        platform_v2['primary_platform']['collection_urls'] = collection_urls
+    
+    # Add auxiliary platforms if found
+    if auxiliary_platforms:
+        platform_v2['auxiliary_platforms'] = auxiliary_platforms
+    
+    # Add internal navigation links (sample)
+    internal_links = [
+        l for l in links
+        if urlparse(l).netloc in urlparse(source_url).netloc
+    ][:20]
+    if internal_links:
+        platform_v2['navigation_links'] = internal_links
+    
+    return platform_v2
+
+
+def scrape_single_url(url: str, client: httpx.Client, max_retries: int = 3) -> dict | None:
+    """Scrape a single URL using Firecrawl API with retry on rate limit."""
+    for attempt in range(max_retries):
+        try:
+            response = client.post(
+                f"{FIRECRAWL_BASE_URL}/scrape",
+                json={
+                    'url': url,
+                    'formats': ['markdown', 'links'],
+                    'onlyMainContent': True,
+                },
+                timeout=60.0,
+            )
+            
+            if response.status_code == 200:
+                data = response.json()
+                if data.get('success'):
+                    return data.get('data', {})
+            
+            # Handle rate limiting (429)
+            if response.status_code == 429:
+                wait_time = 15 * (attempt + 1)  # 15s, 30s, 45s
+                print(f"  Rate limited, waiting {wait_time}s (attempt {attempt + 1}/{max_retries})")
+                time.sleep(wait_time)
+                continue
+            
+            print(f"  Error {response.status_code}: {response.text[:200]}")
+            return None
+            
+        except Exception as e:
+            print(f"  Exception: {e}")
+            if attempt < max_retries - 1:
+                time.sleep(5)
+                continue
+            return None
+    
+    print(f"  Max retries exceeded")
+    return None
+
+
+def update_custodian_file(filepath: Path, platform_v2: dict) -> bool:
+    """Update a custodian YAML file with digital_platform_v2 data."""
+    try:
+        with open(filepath, 'r') as f:
+            data = yaml.safe_load(f)
+        
+        if data is None:
+            data = {}
+        
+        # Add digital_platform_v2 section
+        data['digital_platform_v2'] = platform_v2
+        
+        # Update crawl4ai_enrichment status
+        if 'crawl4ai_enrichment' in data:
+            data['crawl4ai_enrichment']['recrawled_with'] = 'firecrawl'
+            data['crawl4ai_enrichment']['recrawl_date'] = datetime.now(timezone.utc).isoformat()
+        
+        with open(filepath, 'w') as f:
+            yaml.dump(data, f, default_flow_style=False, allow_unicode=True, sort_keys=False)
+        
+        return True
+        
+    except Exception as e:
+        print(f"  Error updating {filepath}: {e}")
+        return False
+
+
+def load_failed_urls() -> list[tuple[str, str]]:
+    """Load the list of failed URLs with their file paths."""
+    urls = []
+    with open(FAILED_URLS_FILE, 'r') as f:
+        for line in f:
+            line = line.strip()
+            if '\t' in line:
+                filename, url = line.split('\t', 1)
+                urls.append((filename, url))
+    return urls
+
+
+def get_org_name(filepath: Path) -> str:
+    """Extract organization name from custodian file."""
+    try:
+        with open(filepath, 'r') as f:
+            data = yaml.safe_load(f)
+        
+        # Try different name fields
+        if data:
+            if 'original_entry' in data and data['original_entry'].get('organisatie'):
+                return data['original_entry']['organisatie']
+            if 'custodian_name' in data:
+                return data['custodian_name'].get('emic_name', '') or data['custodian_name'].get('preferred_name', '')
+            if 'name' in data:
+                return data['name']
+        
+        # Fallback: extract from filename
+        stem = filepath.stem
+        parts = stem.split('-')
+        return parts[-1] if parts else stem
+        
+    except Exception:
+        return filepath.stem
+
+
+def main():
+    parser = argparse.ArgumentParser(description='Batch re-crawl failed URLs with Firecrawl')
+    parser.add_argument('--batch-size', type=int, default=50, help='Number of URLs per batch')
+    parser.add_argument('--start', type=int, default=0, help='Starting index')
+    parser.add_argument('--limit', type=int, default=0, help='Maximum URLs to process (0=all)')
+    parser.add_argument('--dry-run', action='store_true', help='Print what would be done without making changes')
+    parser.add_argument('--delay', type=float, default=6.0, help='Delay between requests in seconds (default 6 for rate limits)')
+    args = parser.parse_args()
+    
+    if not FIRECRAWL_API_KEY:
+        print("Error: FIRECRAWL_API_KEY environment variable not set")
+        sys.exit(1)
+    
+    # Load URLs
+    all_urls = load_failed_urls()
+    print(f"Loaded {len(all_urls)} failed URLs")
+    
+    # Slice based on start and limit
+    if args.limit > 0:
+        urls_to_process = all_urls[args.start:args.start + args.limit]
+    else:
+        urls_to_process = all_urls[args.start:]
+    
+    print(f"Processing {len(urls_to_process)} URLs (start={args.start}, limit={args.limit or 'all'})")
+    
+    if args.dry_run:
+        print("\n[DRY RUN MODE - No changes will be made]")
+        for filename, url in urls_to_process[:10]:
+            print(f"  Would scrape: {filename} -> {url}")
+        print(f"  ... and {len(urls_to_process) - 10} more")
+        return
+    
+    # Create HTTP client
+    client = httpx.Client(
+        headers={
+            'Authorization': f'Bearer {FIRECRAWL_API_KEY}',
+            'Content-Type': 'application/json',
+        }
+    )
+    
+    success_count = 0
+    fail_count = 0
+    
+    try:
+        for i, (filename, url) in enumerate(urls_to_process):
+            filepath = CUSTODIAN_DIR / filename
+            
+            print(f"\n[{i+1}/{len(urls_to_process)}] {filename}")
+            print(f"  URL: {url}")
+            
+            if not filepath.exists():
+                print(f"  SKIP: File not found")
+                continue
+            
+            # Check if already has digital_platform_v2
+            with open(filepath, 'r') as f:
+                content = f.read()
+                if 'digital_platform_v2:' in content:
+                    print(f"  SKIP: Already has digital_platform_v2")
+                    continue
+            
+            # Get org name for platform naming
+            org_name = get_org_name(filepath)
+            
+            # Scrape URL
+            result = scrape_single_url(url, client)
+            
+            if result:
+                # Transform to platform_v2
+                platform_v2 = transform_to_platform_v2(result, url, org_name)
+                
+                # Update file
+                if update_custodian_file(filepath, platform_v2):
+                    success_count += 1
+                    print(f"  SUCCESS: {platform_v2['primary_platform']['platform_name']}")
+                else:
+                    fail_count += 1
+            else:
+                fail_count += 1
+                print(f"  FAILED: Could not scrape URL")
+            
+            # Rate limiting
+            time.sleep(args.delay)
+            
+            # Progress update every 50 URLs
+            if (i + 1) % 50 == 0:
+                print(f"\n=== Progress: {i+1}/{len(urls_to_process)} (success={success_count}, fail={fail_count}) ===\n")
+    
+    finally:
+        client.close()
+    
+    print(f"\n=== Final Results ===")
+    print(f"Success: {success_count}")
+    print(f"Failed: {fail_count}")
+    print(f"Total: {len(urls_to_process)}")
+
+
+if __name__ == '__main__':
+    main()

scripts/batch_httpx_scrape.py

@@ -0,0 +1,488 @@
+#!/usr/bin/env python3
+"""
+Batch web scraper using httpx + BeautifulSoup for digital_platform_v2 enrichment.
+
+This script:
+1. Reads the list of failed crawl URLs
+2. Uses httpx to fetch HTML content directly (no browser, no external API)
+3. Uses BeautifulSoup to parse and extract metadata
+4. Transforms results to digital_platform_v2 format
+5. Updates the custodian YAML files
+
+Usage:
+    python scripts/batch_httpx_scrape.py --limit 10
+    python scripts/batch_httpx_scrape.py --start 100 --limit 50
+    python scripts/batch_httpx_scrape.py --dry-run
+
+No API keys or external services required!
+"""
+
+from __future__ import annotations
+
+import argparse
+import re
+import sys
+import time
+from datetime import datetime, timezone
+from pathlib import Path
+from typing import Any
+from urllib.parse import urljoin, urlparse
+
+import httpx
+import yaml
+from bs4 import BeautifulSoup
+
+# Configuration
+CUSTODIAN_DIR = Path("/Users/kempersc/apps/glam/data/custodian")
+FAILED_URLS_FILE = Path("/Users/kempersc/apps/glam/data/failed_crawl_urls.txt")
+
+# User agent to mimic a real browser
+USER_AGENT = (
+    "Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) "
+    "AppleWebKit/537.36 (KHTML, like Gecko) Chrome/120.0.0.0 Safari/537.36"
+)
+
+# Platform type detection patterns
+PLATFORM_PATTERNS: dict[str, list[str]] = {
+    'DISCOVERY_PORTAL': [
+        r'/collectie', r'/collection', r'/catalogus', r'/catalog',
+        r'/zoeken', r'/search', r'/archief', r'/archive',
+        r'/beeldbank', r'/images', r'/foto', r'/photo',
+    ],
+    'DIGITAL_ARCHIVE': [
+        r'archieven\.nl', r'archief', r'archive',
+        r'/inventaris', r'/inventory', r'/toegang',
+    ],
+    'EDUCATION': [
+        r'/educatie', r'/education', r'/onderwijs', r'/leren',
+        r'/scholen', r'/schools', r'/lesmateriaal',
+    ],
+    'INSTITUTIONAL_WEBSITE': [
+        r'/over-ons', r'/about', r'/contact', r'/bezoek',
+        r'/visit', r'/openingstijden', r'/hours',
+    ],
+}
+
+
+def detect_platform_type(url: str, links: list[str] | None = None) -> str:
+    """Detect the platform type based on URL patterns and extracted links."""
+    url_lower = url.lower()
+    all_urls = [url_lower] + [link.lower() for link in (links or [])]
+    
+    for platform_type, patterns in PLATFORM_PATTERNS.items():
+        for pattern in patterns:
+            for check_url in all_urls:
+                if re.search(pattern, check_url):
+                    return platform_type
+    
+    return 'INSTITUTIONAL_WEBSITE'
+
+
+def extract_collection_urls(links: list[str], base_url: str) -> list[str]:
+    """Extract URLs that appear to be collection/catalog pages."""
+    collection_patterns = [
+        r'/collectie', r'/collection', r'/catalogus', r'/catalog',
+        r'/zoeken', r'/search', r'/beeldbank', r'/inventaris',
+        r'/archief(?!en\.)', r'/archiefstukken', r'/toegangen',
+    ]
+    
+    collection_urls: list[str] = []
+    base_domain = urlparse(base_url).netloc
+    
+    for link in links:
+        try:
+            parsed = urlparse(link)
+            if base_domain in parsed.netloc or parsed.netloc in base_domain:
+                for pattern in collection_patterns:
+                    if re.search(pattern, link.lower()):
+                        if link not in collection_urls:
+                            collection_urls.append(link)
+                        break
+        except Exception:
+            continue
+    
+    return collection_urls[:10]
+
+
+def extract_auxiliary_platforms(links: list[str], base_url: str) -> list[dict[str, str]]:
+    """Extract external platform links (aggregators, portals, etc.)."""
+    external_patterns: dict[str, dict[str, str]] = {
+        'archieven.nl': {'name': 'Archieven.nl', 'type': 'AGGREGATOR'},
+        'europeana.eu': {'name': 'Europeana', 'type': 'AGGREGATOR'},
+        'collectienederland.nl': {'name': 'Collectie Nederland', 'type': 'AGGREGATOR'},
+        'erfgoedthesaurus.nl': {'name': 'Erfgoedthesaurus', 'type': 'THESAURUS'},
+        'delpher.nl': {'name': 'Delpher', 'type': 'DIGITAL_ARCHIVE'},
+        'geheugen.nl': {'name': 'Geheugen van Nederland', 'type': 'AGGREGATOR'},
+        'archiefweb.eu': {'name': 'Archiefweb', 'type': 'DIGITAL_ARCHIVE'},
+    }
+    
+    base_domain = urlparse(base_url).netloc
+    auxiliary: list[dict[str, str]] = []
+    seen_domains: set[str] = set()
+    
+    for link in links:
+        try:
+            parsed = urlparse(link)
+            domain = parsed.netloc.replace('www.', '')
+            
+            if base_domain in domain or domain in base_domain:
+                continue
+            
+            for pattern, info in external_patterns.items():
+                if pattern in domain and domain not in seen_domains:
+                    seen_domains.add(domain)
+                    auxiliary.append({
+                        'platform_name': info['name'],
+                        'platform_url': link,
+                        'platform_type': info['type'],
+                        'integration_type': 'external_aggregator',
+                    })
+                    break
+        except Exception:
+            continue
+    
+    return auxiliary[:5]
+
+
+def is_generic_title(title: str | None) -> bool:
+    """Check if a title is too generic to use as platform name."""
+    generic_patterns = [
+        'home', 'homepage', 'welkom', 'welcome', 'startpagina',
+        'index', 'main', 'website', 'webpagina', 'web page',
+    ]
+    if not title:
+        return True
+    title_lower = title.lower().strip()
+    for pattern in generic_patterns:
+        if title_lower == pattern or title_lower == f"{pattern} -" or title_lower.startswith(f"{pattern} |"):
+            return True
+    return len(title) < 3
+
+
+def scrape_with_httpx(url: str, client: httpx.Client, timeout: float = 30.0) -> dict[str, Any] | None:
+    """Scrape a URL using httpx and return parsed metadata."""
+    try:
+        response = client.get(url, timeout=timeout, follow_redirects=True)
+        
+        if response.status_code != 200:
+            return {'error': f'HTTP {response.status_code}', 'status_code': response.status_code}
+        
+        # Parse HTML
+        soup = BeautifulSoup(response.text, 'html.parser')
+        
+        # Extract metadata
+        metadata: dict[str, Any] = {
+            'status_code': response.status_code,
+            'final_url': str(response.url),
+        }
+        
+        # Title
+        title_tag = soup.find('title')
+        metadata['title'] = title_tag.get_text(strip=True) if title_tag else None
+        
+        # Meta tags
+        for meta in soup.find_all('meta'):
+            name = str(meta.get('name', '')).lower()
+            prop = str(meta.get('property', '')).lower()
+            content = str(meta.get('content', ''))
+            
+            if name == 'description' or prop == 'og:description':
+                if 'description' not in metadata or prop == 'og:description':
+                    metadata['description'] = content
+            elif prop == 'og:title':
+                metadata['og_title'] = content
+            elif prop == 'og:image':
+                metadata['og_image'] = urljoin(url, content) if content else None
+            elif prop == 'og:site_name':
+                metadata['og_site_name'] = content
+            elif name == 'language' or str(meta.get('http-equiv', '')).lower() == 'content-language':
+                metadata['language'] = content.split(',')[0].split('-')[0]
+        
+        # Detect language from html tag
+        html_tag = soup.find('html')
+        if html_tag:
+            lang_attr = html_tag.get('lang')
+            if lang_attr:
+                lang_str = str(lang_attr) if not isinstance(lang_attr, list) else str(lang_attr[0])
+                metadata['language'] = lang_str.split('-')[0]
+        
+        # Favicon
+        for link in soup.find_all('link'):
+            rel = link.get('rel')
+            if rel is None:
+                rel = []
+            if isinstance(rel, list):
+                rel_str = ' '.join(str(r) for r in rel)
+            else:
+                rel_str = str(rel)
+            if 'icon' in rel_str.lower():
+                href = link.get('href')
+                if href:
+                    metadata['favicon'] = urljoin(url, str(href))
+                    break
+        
+        # Extract links
+        links: list[str] = []
+        for a in soup.find_all('a', href=True):
+            href = str(a['href'])
+            if href.startswith('http') or href.startswith('/'):
+                full_url = urljoin(url, href)
+                if full_url not in links:
+                    links.append(full_url)
+        
+        metadata['links'] = links[:100]  # Limit to 100 links
+        
+        return metadata
+        
+    except httpx.TimeoutException:
+        return {'error': 'Timeout', 'status_code': None}
+    except httpx.ConnectError as e:
+        return {'error': f'Connection error: {e}', 'status_code': None}
+    except httpx.HTTPError as e:
+        return {'error': f'HTTP error: {e}', 'status_code': None}
+    except Exception as e:
+        return {'error': f'Exception: {e}', 'status_code': None}
+
+
+def transform_to_platform_v2(scrape_result: dict[str, Any], source_url: str, org_name: str) -> dict[str, Any]:
+    """Transform scrape result to digital_platform_v2 format."""
+    links: list[str] = scrape_result.get('links', [])
+    
+    # Extract title, preferring og:title, then site_name, then page title
+    raw_title = scrape_result.get('title', '') or ''
+    candidate_titles: list[str | None] = [
+        scrape_result.get('og_title'),
+        scrape_result.get('og_site_name'),
+        raw_title.split(' - ')[0].strip() if raw_title else None,
+        raw_title.split(' | ')[0].strip() if raw_title else None,
+    ]
+    
+    title = org_name  # Default fallback
+    for candidate in candidate_titles:
+        if candidate and not is_generic_title(candidate):
+            title = candidate
+            break
+    
+    # Generate platform ID
+    domain = urlparse(source_url).netloc.replace('www.', '').replace('.', '_')
+    platform_id = f"primary_website_{domain}"
+    
+    # Detect platform type
+    platform_type = detect_platform_type(source_url, links)
+    
+    # Extract collection URLs
+    collection_urls = extract_collection_urls(links, source_url)
+    
+    # Extract auxiliary platforms
+    auxiliary_platforms = extract_auxiliary_platforms(links, source_url)
+    
+    # Build digital_platform_v2 structure
+    platform_v2: dict[str, Any] = {
+        'transformation_metadata': {
+            'transformed_from': 'httpx_beautifulsoup',
+            'transformation_date': datetime.now(timezone.utc).isoformat(),
+            'transformation_version': '2.1',
+            'source_status_code': scrape_result.get('status_code', 200),
+        },
+        'primary_platform': {
+            'platform_id': platform_id,
+            'platform_name': f"{title} Website" if 'website' not in title.lower() else title,
+            'platform_url': scrape_result.get('final_url', source_url),
+            'platform_type': platform_type,
+            'description': scrape_result.get('description', ''),
+            'language': scrape_result.get('language', 'nl'),
+            'og_image': scrape_result.get('og_image'),
+            'favicon': scrape_result.get('favicon'),
+        },
+    }
+    
+    # Add collection URLs if found
+    if collection_urls:
+        platform_v2['primary_platform']['collection_urls'] = collection_urls
+    
+    # Add auxiliary platforms if found
+    if auxiliary_platforms:
+        platform_v2['auxiliary_platforms'] = auxiliary_platforms
+    
+    # Add internal navigation links (sample)
+    base_domain = urlparse(source_url).netloc
+    internal_links = [link for link in links if base_domain in urlparse(link).netloc][:20]
+    if internal_links:
+        platform_v2['navigation_links'] = internal_links
+    
+    return platform_v2
+
+
+def update_custodian_file(filepath: Path, platform_v2: dict[str, Any]) -> bool:
+    """Update a custodian YAML file with digital_platform_v2 data."""
+    try:
+        with open(filepath, 'r') as f:
+            data = yaml.safe_load(f)
+        
+        if data is None:
+            data = {}
+        
+        # Add digital_platform_v2 section
+        data['digital_platform_v2'] = platform_v2
+        
+        with open(filepath, 'w') as f:
+            yaml.dump(data, f, default_flow_style=False, allow_unicode=True, sort_keys=False)
+        
+        return True
+        
+    except Exception as e:
+        print(f"  Error updating {filepath}: {e}")
+        return False
+
+
+def load_failed_urls() -> list[tuple[str, str]]:
+    """Load the list of failed URLs with their file paths."""
+    urls: list[tuple[str, str]] = []
+    with open(FAILED_URLS_FILE, 'r') as f:
+        for line in f:
+            line = line.strip()
+            if '\t' in line:
+                filename, url = line.split('\t', 1)
+                urls.append((filename, url))
+    return urls
+
+
+def get_org_name(filepath: Path) -> str:
+    """Extract organization name from custodian file."""
+    try:
+        with open(filepath, 'r') as f:
+            data = yaml.safe_load(f)
+        
+        if data:
+            if 'original_entry' in data and data['original_entry'].get('organisatie'):
+                return str(data['original_entry']['organisatie'])
+            if 'custodian_name' in data:
+                cn = data['custodian_name']
+                return str(cn.get('emic_name', '') or cn.get('preferred_name', ''))
+            if 'name' in data:
+                return str(data['name'])
+        
+        # Fallback: extract from filename
+        stem = filepath.stem
+        parts = stem.split('-')
+        return parts[-1] if parts else stem
+        
+    except Exception:
+        return filepath.stem
+
+
+def main() -> None:
+    parser = argparse.ArgumentParser(description='Batch web scraper using httpx + BeautifulSoup')
+    parser.add_argument('--start', type=int, default=0, help='Starting index')
+    parser.add_argument('--limit', type=int, default=0, help='Maximum URLs to process (0=all)')
+    parser.add_argument('--dry-run', action='store_true', help='Print what would be done without making changes')
+    parser.add_argument('--delay', type=float, default=1.0, help='Delay between requests in seconds (default 1)')
+    parser.add_argument('--timeout', type=float, default=30.0, help='Request timeout in seconds (default 30)')
+    parser.add_argument('--skip-existing', action='store_true', default=True, help='Skip files that already have digital_platform_v2')
+    args = parser.parse_args()
+    
+    # Check for BeautifulSoup
+    try:
+        from bs4 import BeautifulSoup as _  # noqa: F401
+    except ImportError:
+        print("Error: BeautifulSoup not installed. Run: pip install beautifulsoup4")
+        sys.exit(1)
+    
+    # Load URLs
+    all_urls = load_failed_urls()
+    print(f"Loaded {len(all_urls)} failed URLs from {FAILED_URLS_FILE}")
+    
+    # Slice based on start and limit
+    if args.limit > 0:
+        urls_to_process = all_urls[args.start:args.start + args.limit]
+    else:
+        urls_to_process = all_urls[args.start:]
+    
+    print(f"Processing {len(urls_to_process)} URLs (start={args.start}, limit={args.limit or 'all'})")
+    
+    if args.dry_run:
+        print("\n[DRY RUN MODE - No changes will be made]")
+        for filename, url in urls_to_process[:10]:
+            print(f"  Would scrape: {filename} -> {url}")
+        if len(urls_to_process) > 10:
+            print(f"  ... and {len(urls_to_process) - 10} more")
+        return
+    
+    # Create HTTP client with headers
+    client = httpx.Client(
+        headers={
+            'User-Agent': USER_AGENT,
+            'Accept': 'text/html,application/xhtml+xml,application/xml;q=0.9,*/*;q=0.8',
+            'Accept-Language': 'nl,en-US;q=0.9,en;q=0.8',
+        },
+        follow_redirects=True,
+        timeout=args.timeout,
+    )
+    
+    success_count = 0
+    skip_count = 0
+    fail_count = 0
+    
+    try:
+        for i, (filename, url) in enumerate(urls_to_process):
+            filepath = CUSTODIAN_DIR / filename
+            
+            print(f"\n[{i+1}/{len(urls_to_process)}] {filename}")
+            print(f"  URL: {url}")
+            
+            if not filepath.exists():
+                print(f"  SKIP: File not found")
+                skip_count += 1
+                continue
+            
+            # Check if already has digital_platform_v2
+            if args.skip_existing:
+                with open(filepath, 'r') as f:
+                    content = f.read()
+                    if 'digital_platform_v2:' in content:
+                        print(f"  SKIP: Already has digital_platform_v2")
+                        skip_count += 1
+                        continue
+            
+            # Get org name for platform naming
+            org_name = get_org_name(filepath)
+            
+            # Scrape URL
+            result = scrape_with_httpx(url, client, timeout=args.timeout)
+            
+            if result and 'error' not in result:
+                # Transform to platform_v2
+                platform_v2 = transform_to_platform_v2(result, url, org_name)
+                
+                # Update file
+                if update_custodian_file(filepath, platform_v2):
+                    success_count += 1
+                    platform_name = platform_v2['primary_platform']['platform_name']
+                    print(f"  SUCCESS: {platform_name}")
+                else:
+                    fail_count += 1
+            else:
+                fail_count += 1
+                error_msg = result.get('error', 'Unknown error') if result else 'No result'
+                print(f"  FAILED: {error_msg}")
+            
+            # Rate limiting
+            if args.delay > 0:
+                time.sleep(args.delay)
+            
+            # Progress update every 50 URLs
+            if (i + 1) % 50 == 0:
+                print(f"\n=== Progress: {i+1}/{len(urls_to_process)} (success={success_count}, skip={skip_count}, fail={fail_count}) ===\n")
+    
+    finally:
+        client.close()
+    
+    print(f"\n=== Final Results ===")
+    print(f"Success: {success_count}")
+    print(f"Skipped: {skip_count}")
+    print(f"Failed: {fail_count}")
+    print(f"Total: {len(urls_to_process)}")
+
+
+if __name__ == '__main__':
+    main()

scripts/detect_name_mismatch.py

@@ -0,0 +1,213 @@
+#!/usr/bin/env python3
+"""
+Detect name mismatches in LinkedIn entity profiles.
+
+Compares the LinkedIn URL slug with the assigned name to find:
+1. Profiles where the name doesn't match the slug at all
+2. Patterns of repeated wrong names (like "Simon Kemper")
+3. Other potential filler/hallucinated names
+"""
+
+import json
+import os
+import re
+from pathlib import Path
+from collections import Counter, defaultdict
+from urllib.parse import unquote
+import unicodedata
+
+def normalize_name(name: str) -> str:
+    """Normalize a name for comparison."""
+    if not name:
+        return ""
+    # Decode URL encoding
+    name = unquote(name)
+    # Normalize unicode
+    name = unicodedata.normalize('NFD', name)
+    # Remove diacritics
+    name = ''.join(c for c in name if unicodedata.category(c) != 'Mn')
+    # Lowercase
+    name = name.lower()
+    # Remove common suffixes like numbers, hyphens
+    name = re.sub(r'[-_\d]+$', '', name)
+    # Replace hyphens/underscores with spaces
+    name = re.sub(r'[-_]+', ' ', name)
+    # Remove extra whitespace
+    name = ' '.join(name.split())
+    return name
+
+def extract_name_from_slug(slug: str) -> str:
+    """Extract a human-readable name from a LinkedIn slug."""
+    # Decode URL encoding
+    slug = unquote(slug)
+    # Remove timestamp suffix like _20251214T115050Z
+    slug = re.sub(r'_\d{8}T\d{6}Z\.json$', '', slug)
+    # Remove trailing numbers/IDs
+    slug = re.sub(r'[-_][\da-f]{6,}$', '', slug)
+    slug = re.sub(r'[-_]\d+$', '', slug)
+    return normalize_name(slug)
+
+def names_match(slug_name: str, profile_name: str) -> bool:
+    """Check if the slug name and profile name are reasonably similar."""
+    if not slug_name or not profile_name:
+        return False
+    
+    slug_normalized = normalize_name(slug_name)
+    profile_normalized = normalize_name(profile_name)
+    
+    # Direct match
+    if slug_normalized == profile_normalized:
+        return True
+    
+    # Check if all words from slug appear in profile name
+    slug_words = set(slug_normalized.split())
+    profile_words = set(profile_normalized.split())
+    
+    # If slug has meaningful words, check overlap
+    if slug_words and len(slug_words) >= 2:
+        # At least half the slug words should be in profile
+        overlap = slug_words & profile_words
+        if len(overlap) >= len(slug_words) * 0.5:
+            return True
+    
+    # Check if first name matches
+    slug_parts = slug_normalized.split()
+    profile_parts = profile_normalized.split()
+    if slug_parts and profile_parts:
+        if slug_parts[0] == profile_parts[0]:
+            return True
+    
+    return False
+
+def analyze_entity_files(entity_dir: Path):
+    """Analyze all entity files for name mismatches."""
+    
+    mismatches = []
+    name_counter = Counter()
+    files_by_name = defaultdict(list)
+    total_files = 0
+    fallback_files = 0
+    
+    for filepath in entity_dir.glob("*.json"):
+        total_files += 1
+        filename = filepath.name
+        
+        try:
+            with open(filepath, 'r', encoding='utf-8') as f:
+                data = json.load(f)
+        except (json.JSONDecodeError, IOError) as e:
+            print(f"Error reading {filename}: {e}")
+            continue
+        
+        # Get the profile name
+        profile_name = None
+        if 'profile_data' in data and 'name' in data['profile_data']:
+            profile_name = data['profile_data']['name']
+        elif 'source_staff_info' in data and 'name' in data['source_staff_info']:
+            profile_name = data['source_staff_info']['name']
+        
+        if not profile_name:
+            continue
+        
+        # Track all names for frequency analysis
+        name_counter[profile_name] += 1
+        files_by_name[profile_name].append(filename)
+        
+        # Check if this is a fallback file
+        extraction_method = data.get('extraction_metadata', {}).get('extraction_method', '')
+        if extraction_method == 'fallback_basic':
+            fallback_files += 1
+        
+        # Extract name from slug
+        slug_name = extract_name_from_slug(filename)
+        
+        # Check for mismatch
+        if not names_match(slug_name, profile_name):
+            mismatches.append({
+                'filename': filename,
+                'slug_name': slug_name,
+                'profile_name': profile_name,
+                'extraction_method': extraction_method,
+                'linkedin_url': data.get('extraction_metadata', {}).get('linkedin_url', '')
+            })
+    
+    return {
+        'total_files': total_files,
+        'fallback_files': fallback_files,
+        'mismatches': mismatches,
+        'name_counter': name_counter,
+        'files_by_name': files_by_name
+    }
+
+def main():
+    entity_dir = Path("/Users/kempersc/apps/glam/data/custodian/person/entity")
+    
+    print("=" * 80)
+    print("LINKEDIN ENTITY NAME MISMATCH ANALYSIS")
+    print("=" * 80)
+    print()
+    
+    results = analyze_entity_files(entity_dir)
+    
+    print(f"Total entity files analyzed: {results['total_files']}")
+    print(f"Fallback (basic) files: {results['fallback_files']}")
+    print(f"Total mismatches detected: {len(results['mismatches'])}")
+    print()
+    
+    # Find names that appear suspiciously often (potential filler names)
+    print("=" * 80)
+    print("NAMES APPEARING MORE THAN 5 TIMES (Potential Filler Names)")
+    print("=" * 80)
+    frequent_names = [(name, count) for name, count in results['name_counter'].most_common(50) if count > 5]
+    
+    for name, count in frequent_names:
+        # Check if this name appears in mismatches
+        mismatch_count = sum(1 for m in results['mismatches'] if m['profile_name'] == name)
+        print(f"  '{name}': {count} occurrences ({mismatch_count} are mismatches)")
+    
+    print()
+    print("=" * 80)
+    print("ALL MISMATCHED FILES (slug name != profile name)")
+    print("=" * 80)
+    
+    # Group mismatches by profile_name to see patterns
+    mismatch_by_name = defaultdict(list)
+    for m in results['mismatches']:
+        mismatch_by_name[m['profile_name']].append(m)
+    
+    # Sort by frequency of the mismatched name
+    sorted_names = sorted(mismatch_by_name.items(), key=lambda x: -len(x[1]))
+    
+    for profile_name, items in sorted_names[:30]:  # Top 30 most frequent mismatch names
+        print(f"\n--- '{profile_name}' assigned to {len(items)} different slugs ---")
+        for item in items[:10]:  # Show first 10 examples
+            print(f"  Slug: {item['slug_name']}")
+            print(f"  File: {item['filename']}")
+            print(f"  Method: {item['extraction_method']}")
+            print()
+    
+    # Output detailed CSV for further analysis
+    csv_path = entity_dir.parent / "name_mismatch_report.csv"
+    with open(csv_path, 'w', encoding='utf-8') as f:
+        f.write("filename,slug_name,profile_name,extraction_method,linkedin_url\n")
+        for m in results['mismatches']:
+            f.write(f'"{m["filename"]}","{m["slug_name"]}","{m["profile_name"]}","{m["extraction_method"]}","{m["linkedin_url"]}"\n')
+    
+    print(f"\nDetailed report saved to: {csv_path}")
+    
+    # Also output JSON for programmatic use
+    json_path = entity_dir.parent / "name_mismatch_report.json"
+    with open(json_path, 'w', encoding='utf-8') as f:
+        json.dump({
+            'total_files': results['total_files'],
+            'fallback_files': results['fallback_files'],
+            'total_mismatches': len(results['mismatches']),
+            'mismatches_by_name': {name: len(items) for name, items in mismatch_by_name.items()},
+            'frequent_names': [(name, count) for name, count in results['name_counter'].most_common(100)],
+            'mismatches': results['mismatches']
+        }, f, indent=2, ensure_ascii=False)
+    
+    print(f"JSON report saved to: {json_path}")
+
+if __name__ == "__main__":
+    main()

scripts/enrich_dutch_custodians_crawl4ai.py

@@ -0,0 +1,666 @@
+#!/usr/bin/env python3
+"""
+Enrich Dutch custodian YAML files with web data using Crawl4AI (free, local).
+
+This script replaces the Firecrawl-based enrichment with Crawl4AI which:
+1. Runs locally using Playwright (no API costs)
+2. Extracts links, metadata, and content with XPath provenance
+3. Detects APIs, catalogs, and metadata standards
+
+Usage:
+    python scripts/enrich_dutch_custodians_crawl4ai.py [options]
+
+Options:
+    --dry-run       Show what would be enriched without modifying files
+    --limit N       Process only first N files (for testing)
+    --start-index N Start from index N (for resuming)
+    --resume        Resume from last checkpoint
+    --force         Re-enrich even if already has crawl4ai_enrichment
+    --file PATH     Process a single specific file
+"""
+
+import argparse
+import asyncio
+import json
+import logging
+import os
+import re
+import sys
+from dataclasses import dataclass, field
+from datetime import datetime, timezone
+from pathlib import Path
+from typing import Any, Optional
+from urllib.parse import urlparse, urlunparse
+
+import yaml
+from dotenv import load_dotenv
+from lxml import etree
+
+# Crawl4AI imports
+from crawl4ai import AsyncWebCrawler, CrawlerRunConfig, CacheMode
+
+# Load environment variables from .env file
+load_dotenv()
+
+# Set up logging
+logging.basicConfig(
+    level=logging.INFO,
+    format='%(asctime)s - %(levelname)s - %(message)s'
+)
+logger = logging.getLogger(__name__)
+
+# Configuration
+CUSTODIAN_DIR = Path(__file__).parent.parent / "data" / "custodian"
+CHECKPOINT_FILE = CUSTODIAN_DIR / ".crawl4ai_enrichment_checkpoint.json"
+
+# Rate limiting - be nice to websites even though we're local
+REQUEST_DELAY = 2.0  # seconds between requests
+
+# Digital platform detection patterns
+API_ENDPOINT_PATTERNS = [
+    r'/oai[-_]?pmh',
+    r'/api/',
+    r'/rest/',
+    r'/sparql',
+    r'/graphql',
+    r'/iiif/',
+    r'/sru',
+    r'/z39\.50',
+    r'/opensearch',
+]
+
+CATALOG_PATTERNS = [
+    r'/catalogu[es]?(?:/|\?|$)',
+    r'/collecti[eo]n?[s]?(?:/|\?|$)',
+    r'/archie[fv](?:/|\?|$)',
+    r'/beeldbank(?:/|\?|$)',
+    r'/zoeken(?:/|\?|$)',
+    r'/search(?:/|\?|$)',
+    r'/discover(?:/|\?|$)',
+    r'/browse(?:/|\?|$)',
+]
+
+# Dutch-specific catalog type detection
+CATALOG_TYPE_PATTERNS = {
+    'beeldbank': {
+        'patterns': [r'/beeldbank', r'/beeld', r'/images', r'/foto'],
+        'label': 'Image Collection',
+        'description_nl': 'Beeldbank met gedigitaliseerde foto\'s, kaarten en afbeeldingen',
+    },
+    'genealogie': {
+        'patterns': [r'/genealogie', r'/stamboom', r'/persons', r'/akten'],
+        'label': 'Genealogy Records',
+        'description_nl': 'Genealogische bronnen en persoonsgegevens',
+    },
+    'archieven': {
+        'patterns': [r'/archie[fv]', r'/inventaris', r'/toegangen', r'/finding'],
+        'label': 'Archive Finding Aids',
+        'description_nl': 'Archiefinventarissen en toegangen',
+    },
+    'collectie': {
+        'patterns': [r'/collectie', r'/collection', r'/object'],
+        'label': 'Collection Portal',
+        'description_nl': 'Collectieportaal met objecten en kunstwerken',
+    },
+    'kranten': {
+        'patterns': [r'/kranten', r'/newspaper', r'/periodiek'],
+        'label': 'Newspaper Archive',
+        'description_nl': 'Gedigitaliseerde kranten en periodieken',
+    },
+    'kaarten': {
+        'patterns': [r'/kaart', r'/map', r'/cartogra'],
+        'label': 'Map Collection',
+        'description_nl': 'Historische kaarten en cartografisch materiaal',
+    },
+    'bibliotheek': {
+        'patterns': [r'/catalogu', r'/biblio', r'/library', r'/boek'],
+        'label': 'Library Catalog',
+        'description_nl': 'Bibliotheekcatalogus',
+    },
+    'zoeken': {
+        'patterns': [r'/zoeken', r'/search', r'/discover', r'/browse'],
+        'label': 'Search Interface',
+        'description_nl': 'Algemene zoekinterface',
+    },
+}
+
+CMS_INDICATORS = {
+    'atlantis': ['atlantis', 'picturae'],
+    'mais_flexis': ['mais-flexis', 'mais flexis', 'de ree'],
+    'adlib': ['adlib', 'axiell'],
+    'collective_access': ['collectiveaccess', 'collective access'],
+    'archivematica': ['archivematica'],
+    'archivesspace': ['archivesspace'],
+    'atom': ['accesstomemory', 'atom'],
+    'omeka': ['omeka'],
+    'contentdm': ['contentdm'],
+    'dspace': ['dspace'],
+    'islandora': ['islandora'],
+    'memorix': ['memorix'],
+}
+
+# Metadata standards detection patterns with regex word boundaries
+METADATA_STANDARDS_PATTERNS = [
+    (r'\bdublin\s+core\b', 'Dublin Core', True),
+    (r'\bdc:', 'Dublin Core', True),
+    (r'\bdcterms\b', 'Dublin Core', True),
+    (r'\bmarc\s*21\b', 'MARC21', True),
+    (r'\bmarc21\b', 'MARC21', True),
+    (r'\bead\b', 'EAD', True),
+    (r'encoded\s+archival\s+description', 'EAD', True),
+    (r'\bead\s*2002\b', 'EAD', True),
+    (r'\bead3\b', 'EAD', True),
+    (r'\bmets\b', 'METS', True),
+    (r'metadata\s+encoding\s+and\s+transmission', 'METS', True),
+    (r'\bmods\b', 'MODS', True),
+    (r'metadata\s+object\s+description', 'MODS', True),
+    (r'\blido\b', 'LIDO', True),
+    (r'lightweight\s+information\s+describing', 'LIDO', True),
+    (r'\bcidoc[-\s]?crm\b', 'CIDOC-CRM', True),
+    (r'\bschema\.org\b', 'Schema.org', True),
+    (r'\bschema:', 'Schema.org', True),
+    (r'\bric[-\s]?o\b', 'RiC-O', True),
+    (r'records\s+in\s+contexts', 'RiC-O', True),
+    (r'\bpremis\b', 'PREMIS', True),
+    (r'preservation\s+metadata', 'PREMIS', True),
+    (r'\bbibframe\b', 'BIBFRAME', True),
+    (r'\biiif\b', 'IIIF', True),
+    (r'image\s+interoperability\s+framework', 'IIIF', True),
+]
+
+# Dutch archive platform domains to detect
+DUTCH_ARCHIVE_PLATFORMS = [
+    'archieven.nl',
+    'memorix.nl',
+    'archiefweb.eu',
+    'atlantisdigitaal.nl',
+    'picturae.nl',
+    'mais-flexis.nl',
+    'delpher.nl',
+    'geheugen.nl',
+]
+
+
+def get_xpath(element, tree) -> str:
+    """Generate XPath for an lxml element."""
+    parts = []
+    while element is not None:
+        parent = element.getparent()
+        if parent is None:
+            parts.append(element.tag)
+        else:
+            siblings = [c for c in parent if c.tag == element.tag]
+            if len(siblings) == 1:
+                parts.append(element.tag)
+            else:
+                index = siblings.index(element) + 1
+                parts.append(f'{element.tag}[{index}]')
+        element = parent
+    return '/' + '/'.join(reversed(parts))
+
+
+def normalize_url(url: str) -> str:
+    """Normalize URL by removing noise query parameters."""
+    if not url:
+        return url
+    
+    parsed = urlparse(url)
+    # Remove common tracking/session parameters
+    noise_params = ['sort', 'order', 'view', 'mode', 'ss', 'page', 'offset', 
+                    'limit', 'random', 'session', 'sid', 'token', 'ref']
+    
+    if parsed.query:
+        params = dict(p.split('=', 1) if '=' in p else (p, '') 
+                      for p in parsed.query.split('&'))
+        filtered = {k: v for k, v in params.items() 
+                    if not any(k.startswith(n) for n in noise_params + ['utm_', 'fbclid', 'gclid'])}
+        new_query = '&'.join(f'{k}={v}' if v else k for k, v in sorted(filtered.items()))
+        return urlunparse(parsed._replace(query=new_query))
+    
+    return url
+
+
+def detect_catalog_type(url: str) -> dict | None:
+    """Detect catalog type from URL pattern."""
+    url_lower = url.lower()
+    for type_key, type_info in CATALOG_TYPE_PATTERNS.items():
+        for pattern in type_info['patterns']:
+            if re.search(pattern, url_lower):
+                return {
+                    'type': type_key,
+                    'label': type_info['label'],
+                    'description_nl': type_info['description_nl'],
+                }
+    return None
+
+
+def detect_metadata_standards(content: str) -> list[str]:
+    """Detect metadata standards mentioned in content using regex word boundaries."""
+    if not content:
+        return []
+    
+    content_lower = content.lower()
+    standards_found = set()
+    
+    for pattern, standard_name, use_regex in METADATA_STANDARDS_PATTERNS:
+        if use_regex:
+            if re.search(pattern, content_lower, re.IGNORECASE):
+                standards_found.add(standard_name)
+        else:
+            if pattern.lower() in content_lower:
+                standards_found.add(standard_name)
+    
+    return sorted(list(standards_found))
+
+
+def detect_cms(content: str) -> str | None:
+    """Detect CMS/collection management system from content."""
+    if not content:
+        return None
+    
+    content_lower = content.lower()
+    for cms_name, indicators in CMS_INDICATORS.items():
+        for indicator in indicators:
+            if indicator in content_lower:
+                return cms_name
+    return None
+
+
+def extract_website_url(entry: dict) -> str | None:
+    """Extract website URL from custodian entry."""
+    # Check various possible locations for website
+    if 'website' in entry:
+        return entry['website']
+    
+    # Check in enrichment data
+    for enrichment_key in ['zcbs_enrichment', 'google_maps_enrichment', 'wikidata_enrichment']:
+        if enrichment_key in entry:
+            enrichment = entry[enrichment_key]
+            if isinstance(enrichment, dict):
+                if 'website' in enrichment:
+                    return enrichment['website']
+                if 'url' in enrichment:
+                    return enrichment['url']
+    
+    # Check identifiers
+    if 'identifiers' in entry:
+        for identifier in entry.get('identifiers', []):
+            if isinstance(identifier, dict):
+                if identifier.get('identifier_scheme') == 'Website':
+                    return identifier.get('identifier_value')
+    
+    return None
+
+
+async def crawl_website(crawler: AsyncWebCrawler, url: str) -> dict:
+    """
+    Crawl a website and extract structured data with XPath provenance.
+    
+    Returns a dict with:
+    - success: bool
+    - title: str
+    - description: str  
+    - html: str (raw HTML for further processing)
+    - markdown: str
+    - links: list of dicts with href, text, xpath
+    - metadata: dict of og/meta tags
+    - error: str (if failed)
+    """
+    config = CrawlerRunConfig(
+        cache_mode=CacheMode.BYPASS,
+        verbose=False,
+        # Wait for page to fully load
+        wait_until="networkidle",
+        page_timeout=30000,
+    )
+    
+    try:
+        result = await crawler.arun(url=url, config=config)
+        
+        if not result.success:
+            return {
+                'success': False,
+                'error': f'Crawl failed with status {result.status_code}',
+                'status_code': result.status_code,
+            }
+        
+        # Parse HTML with lxml to extract XPaths
+        links_with_xpath = []
+        if result.html:
+            try:
+                tree = etree.HTML(result.html)
+                link_elements = tree.xpath('//a[@href]')
+                
+                for link_el in link_elements:
+                    href = link_el.get('href', '')
+                    text = ''.join(link_el.itertext()).strip()
+                    xpath = get_xpath(link_el, tree)
+                    
+                    # Skip empty links and javascript
+                    if href and not href.startswith(('javascript:', '#', 'mailto:', 'tel:')):
+                        links_with_xpath.append({
+                            'href': href,
+                            'text': text[:200] if text else '',  # Truncate long text
+                            'xpath': xpath,
+                        })
+            except Exception as e:
+                logger.warning(f"Error parsing HTML for XPath extraction: {e}")
+        
+        # Also include crawl4ai's extracted links for completeness
+        internal_links = result.links.get('internal', []) if result.links else []
+        external_links = result.links.get('external', []) if result.links else []
+        
+        return {
+            'success': True,
+            'status_code': result.status_code,
+            'title': result.metadata.get('title', '') if result.metadata else '',
+            'description': result.metadata.get('description', '') if result.metadata else '',
+            'html': result.html,
+            'markdown': result.markdown.raw_markdown if result.markdown else '',
+            'links_with_xpath': links_with_xpath,
+            'internal_links': [l.get('href', '') for l in internal_links if isinstance(l, dict)],
+            'external_links': [l.get('href', '') for l in external_links if isinstance(l, dict)],
+            'metadata': result.metadata or {},
+        }
+        
+    except Exception as e:
+        logger.error(f"Error crawling {url}: {e}")
+        return {
+            'success': False,
+            'error': str(e),
+        }
+
+
+def analyze_crawl_results(crawl_data: dict, base_url: str) -> dict:
+    """
+    Analyze crawl results to extract APIs, catalogs, and metadata standards.
+    
+    Returns enrichment dict ready to add to YAML.
+    """
+    enrichment = {
+        'retrieval_timestamp': datetime.now(timezone.utc).isoformat(),
+        'retrieval_agent': 'crawl4ai',
+        'source_url': base_url,
+        'status_code': crawl_data.get('status_code'),
+    }
+    
+    if not crawl_data.get('success'):
+        enrichment['error'] = crawl_data.get('error', 'Unknown error')
+        return enrichment
+    
+    # Basic metadata
+    enrichment['title'] = crawl_data.get('title', '')
+    enrichment['description'] = crawl_data.get('description', '')
+    enrichment['links_count'] = len(crawl_data.get('links_with_xpath', []))
+    
+    # Collect all URLs for analysis
+    all_urls = set()
+    links_with_xpath = crawl_data.get('links_with_xpath', [])
+    
+    for link in links_with_xpath:
+        href = link.get('href', '')
+        if href:
+            # Make absolute URL if relative
+            if href.startswith('/'):
+                parsed_base = urlparse(base_url)
+                href = f"{parsed_base.scheme}://{parsed_base.netloc}{href}"
+            all_urls.add(href)
+    
+    # Add internal/external links from crawl4ai
+    for link in crawl_data.get('internal_links', []):
+        if link:
+            all_urls.add(link)
+    for link in crawl_data.get('external_links', []):
+        if link:
+            all_urls.add(link)
+    
+    # Detect API endpoints
+    detected_apis = []
+    for url in all_urls:
+        url_lower = url.lower()
+        for pattern in API_ENDPOINT_PATTERNS:
+            if re.search(pattern, url_lower):
+                detected_apis.append({
+                    'url': normalize_url(url),
+                    'pattern_matched': pattern,
+                })
+                break
+    
+    if detected_apis:
+        enrichment['detected_api_endpoints'] = detected_apis
+    
+    # Detect catalog URLs with type classification
+    detected_catalogs = []
+    for url in all_urls:
+        url_lower = url.lower()
+        for pattern in CATALOG_PATTERNS:
+            if re.search(pattern, url_lower):
+                catalog_entry = {
+                    'url': normalize_url(url),
+                }
+                catalog_type = detect_catalog_type(url)
+                if catalog_type:
+                    catalog_entry['type'] = catalog_type['type']
+                    catalog_entry['label'] = catalog_type['label']
+                
+                # Find XPath for this link
+                for link in links_with_xpath:
+                    if link.get('href', '').rstrip('/') == url.rstrip('/') or \
+                       (link.get('href', '').startswith('/') and url.endswith(link.get('href', ''))):
+                        catalog_entry['xpath'] = link.get('xpath')
+                        catalog_entry['link_text'] = link.get('text', '')
+                        break
+                
+                detected_catalogs.append(catalog_entry)
+                break
+    
+    if detected_catalogs:
+        enrichment['detected_catalog_urls'] = detected_catalogs
+    
+    # Detect external archive platforms
+    external_platforms = []
+    for url in all_urls:
+        url_lower = url.lower()
+        for platform in DUTCH_ARCHIVE_PLATFORMS:
+            if platform in url_lower:
+                external_platforms.append({
+                    'url': normalize_url(url),
+                    'platform': platform,
+                })
+                break
+    
+    if external_platforms:
+        enrichment['external_archive_platforms'] = external_platforms
+    
+    # Detect metadata standards from content
+    # Handle None values explicitly to avoid string concatenation errors
+    markdown = crawl_data.get('markdown') or ''
+    title = crawl_data.get('title') or ''
+    description = crawl_data.get('description') or ''
+    content = f"{markdown} {title} {description}"
+    standards = detect_metadata_standards(content)
+    if standards:
+        enrichment['detected_standards'] = standards
+    
+    # Detect CMS
+    cms = detect_cms(content)
+    if cms:
+        enrichment['detected_cms'] = cms
+    
+    # Extract OG/meta tags of interest
+    metadata = crawl_data.get('metadata', {})
+    og_data = {}
+    for key in ['og:title', 'og:description', 'og:image', 'og:url', 'og:site_name']:
+        if key in metadata:
+            og_data[key.replace('og:', '')] = metadata[key]
+    if og_data:
+        enrichment['open_graph'] = og_data
+    
+    return enrichment
+
+
+def load_checkpoint() -> dict:
+    """Load checkpoint from file."""
+    if CHECKPOINT_FILE.exists():
+        with open(CHECKPOINT_FILE, 'r') as f:
+            return json.load(f)
+    return {}
+
+
+def save_checkpoint(checkpoint: dict):
+    """Save checkpoint to file."""
+    with open(CHECKPOINT_FILE, 'w') as f:
+        json.dump(checkpoint, f, indent=2)
+
+
+async def process_single_file(
+    crawler: AsyncWebCrawler,
+    filepath: Path,
+    dry_run: bool = False,
+    force: bool = False,
+) -> bool:
+    """Process a single custodian YAML file."""
+    try:
+        with open(filepath, 'r', encoding='utf-8') as f:
+            entry = yaml.safe_load(f)
+        
+        if not entry:
+            logger.warning(f"Empty file: {filepath}")
+            return False
+        
+        # Check if already enriched
+        if 'crawl4ai_enrichment' in entry and not force:
+            logger.info(f"Skipping {filepath.name}: already has crawl4ai_enrichment")
+            return True
+        
+        # Extract website URL
+        website_url = extract_website_url(entry)
+        if not website_url:
+            logger.info(f"Skipping {filepath.name}: no website URL found")
+            return False
+        
+        # Ensure URL has protocol
+        if not website_url.startswith(('http://', 'https://')):
+            website_url = 'https://' + website_url
+        
+        logger.info(f"Processing {filepath.name}: {website_url}")
+        
+        if dry_run:
+            logger.info(f"  -> DRY RUN: would crawl {website_url}")
+            return True
+        
+        # Crawl the website
+        crawl_data = await crawl_website(crawler, website_url)
+        
+        # Analyze results
+        enrichment = analyze_crawl_results(crawl_data, website_url)
+        
+        # Add enrichment to entry
+        entry['crawl4ai_enrichment'] = enrichment
+        
+        # Write back to file
+        with open(filepath, 'w', encoding='utf-8') as f:
+            yaml.dump(entry, f, default_flow_style=False, allow_unicode=True, sort_keys=False)
+        
+        # Log summary
+        apis_count = len(enrichment.get('detected_api_endpoints', []))
+        catalogs_count = len(enrichment.get('detected_catalog_urls', []))
+        platforms_count = len(enrichment.get('external_archive_platforms', []))
+        logger.info(f"  -> success: {apis_count} APIs, {catalogs_count} catalogs, {platforms_count} external platforms found")
+        
+        return True
+        
+    except Exception as e:
+        logger.error(f"Error processing {filepath}: {e}")
+        return False
+
+
+async def main():
+    parser = argparse.ArgumentParser(description='Enrich Dutch custodians with Crawl4AI')
+    parser.add_argument('--dry-run', action='store_true', help='Show what would be enriched')
+    parser.add_argument('--limit', type=int, help='Process only first N files')
+    parser.add_argument('--start-index', type=int, default=0, help='Start from index N')
+    parser.add_argument('--resume', action='store_true', help='Resume from last checkpoint')
+    parser.add_argument('--force', action='store_true', help='Re-enrich even if already enriched')
+    parser.add_argument('--file', type=str, help='Process a single specific file')
+    args = parser.parse_args()
+    
+    # Create logs directory
+    logs_dir = Path(__file__).parent.parent / "logs"
+    logs_dir.mkdir(exist_ok=True)
+    
+    # Add file handler for logging
+    log_file = logs_dir / f"crawl4ai_enrichment_{datetime.now().strftime('%Y%m%d_%H%M%S')}.log"
+    file_handler = logging.FileHandler(log_file)
+    file_handler.setFormatter(logging.Formatter('%(asctime)s - %(levelname)s - %(message)s'))
+    logger.addHandler(file_handler)
+    
+    # Single file mode
+    if args.file:
+        filepath = Path(args.file)
+        if not filepath.exists():
+            logger.error(f"File not found: {filepath}")
+            sys.exit(1)
+        
+        async with AsyncWebCrawler() as crawler:
+            success = await process_single_file(crawler, filepath, args.dry_run, args.force)
+            sys.exit(0 if success else 1)
+    
+    # Batch mode
+    files = sorted(CUSTODIAN_DIR.glob("NL-*.yaml"))
+    logger.info(f"Found {len(files)} Dutch custodian files")
+    
+    # Handle resume
+    start_index = args.start_index
+    if args.resume:
+        checkpoint = load_checkpoint()
+        if 'last_processed_index' in checkpoint:
+            start_index = checkpoint['last_processed_index'] + 1
+            logger.info(f"Resuming from index {start_index}")
+    
+    # Apply limit
+    end_index = len(files)
+    if args.limit:
+        end_index = min(start_index + args.limit, len(files))
+    
+    logger.info(f"Processing files {start_index} to {end_index - 1}")
+    
+    # Process files
+    success_count = 0
+    error_count = 0
+    
+    async with AsyncWebCrawler() as crawler:
+        for i, filepath in enumerate(files[start_index:end_index], start=start_index):
+            logger.info(f"[{i + 1}/{len(files)}] Processing {filepath.name}")
+            
+            success = await process_single_file(crawler, filepath, args.dry_run, args.force)
+            
+            if success:
+                success_count += 1
+            else:
+                error_count += 1
+            
+            # Save checkpoint
+            if not args.dry_run:
+                save_checkpoint({
+                    'last_processed_index': i,
+                    'last_processed_file': str(filepath),
+                    'last_processed_time': datetime.now(timezone.utc).isoformat(),
+                    'success_count': success_count,
+                    'error_count': error_count,
+                })
+            
+            # Rate limiting
+            if i < end_index - 1:
+                await asyncio.sleep(REQUEST_DELAY)
+    
+    # Summary
+    logger.info(f"\n{'='*50}")
+    logger.info(f"Enrichment complete!")
+    logger.info(f"  Success: {success_count}")
+    logger.info(f"  Errors: {error_count}")
+    logger.info(f"  Log file: {log_file}")
+
+
+if __name__ == '__main__':
+    asyncio.run(main())

scripts/fix_collision_victims.py

@@ -0,0 +1,281 @@
+#!/usr/bin/env python3
+"""
+Fix GHCID collision victim files.
+
+These files have a trailing dash in their filename (e.g., NL-DR-ASS-L-BD-.yaml)
+indicating they were collision victims whose internal GHCID was incorrectly set
+to their collision partner's GHCID instead of getting their own unique GHCID.
+
+This script:
+1. Reads the institution's real name from original_entry.organisatie
+2. Generates a proper name suffix from that name
+3. Creates a new unique GHCID with the proper suffix
+4. Regenerates all GHCID-derived identifiers (UUID, numeric)
+5. Updates the file with correct identifiers
+6. Renames the file to match the new GHCID
+"""
+
+import hashlib
+import re
+import shutil
+import unicodedata
+import uuid
+from datetime import datetime, timezone
+from pathlib import Path
+from typing import Optional
+
+import yaml
+
+# GHCID namespace for UUID generation
+GHCID_NAMESPACE = uuid.NAMESPACE_URL
+GHCID_URL_PREFIX = "https://glam.registry/"
+
+# Skip words for abbreviation generation (Dutch and common)
+SKIP_WORDS = {
+    'de', 'het', 'een', 'van', 'voor', 'in', 'op', 'te', 'den', 'der', 'des',
+    's', 'aan', 'bij', 'met', 'naar', 'om', 'tot', 'uit', 'over', 'onder',
+    'door', 'en', 'of', 'stichting', 'vereniging', 'foundation', 'the', 'a',
+    'an', 'of', 'in', 'at', 'on', 'to', 'for', 'with', 'from', 'by', 'as',
+    'museum', 'bibliotheek', 'archief', 'collectie'
+}
+
+
+def normalize_diacritics(text: str) -> str:
+    """Normalize diacritics to ASCII equivalents."""
+    normalized = unicodedata.normalize('NFD', text)
+    ascii_text = ''.join(c for c in normalized if unicodedata.category(c) != 'Mn')
+    return ascii_text
+
+
+def generate_name_suffix(native_name: str) -> str:
+    """Convert native language institution name to snake_case suffix.
+    
+    Examples:
+        "Biblionet Drenthe POI" → "biblionet_drenthe_poi"
+        "Fries Verzetsmuseum" → "fries_verzetsmuseum"
+        "Musée d'Orsay" → "musee_dorsay"
+    """
+    # Normalize unicode and remove diacritics
+    ascii_name = normalize_diacritics(native_name)
+    
+    # Convert to lowercase
+    lowercase = ascii_name.lower()
+    
+    # Remove apostrophes, commas, and other punctuation
+    no_punct = re.sub(r"[''`\",.:;!?()[\]{}]", '', lowercase)
+    
+    # Replace spaces and hyphens with underscores
+    underscored = re.sub(r'[\s\-]+', '_', no_punct)
+    
+    # Remove any remaining non-alphanumeric characters (except underscores)
+    clean = re.sub(r'[^a-z0-9_]', '', underscored)
+    
+    # Collapse multiple underscores
+    final = re.sub(r'_+', '_', clean).strip('_')
+    
+    return final
+
+
+def generate_ghcid_uuid(ghcid: str) -> str:
+    """Generate UUID v5 from GHCID."""
+    return str(uuid.uuid5(GHCID_NAMESPACE, f"{GHCID_URL_PREFIX}{ghcid}"))
+
+
+def generate_ghcid_uuid_sha256(ghcid: str) -> str:
+    """Generate UUID v8 (SHA-256 based) from GHCID."""
+    return str(uuid.uuid5(GHCID_NAMESPACE, f"{GHCID_URL_PREFIX}sha256/{ghcid}"))
+
+
+def generate_ghcid_numeric(ghcid: str) -> int:
+    """Generate 64-bit numeric ID from GHCID."""
+    sha256_hash = hashlib.sha256(ghcid.encode()).hexdigest()
+    return int(sha256_hash[:16], 16)
+
+
+def fix_collision_victim(file_path: Path, dry_run: bool = False) -> Optional[Path]:
+    """Fix a single collision victim file.
+    
+    Args:
+        file_path: Path to the collision victim YAML file
+        dry_run: If True, only print what would be done
+        
+    Returns:
+        New file path after renaming, or None if skipped/failed
+    """
+    print(f"\n{'='*80}")
+    print(f"Processing: {file_path.name}")
+    print(f"{'='*80}")
+    
+    # Read file
+    try:
+        with open(file_path) as f:
+            data = yaml.safe_load(f)
+    except Exception as e:
+        print(f"  ERROR: Could not read file: {e}")
+        return None
+    
+    if data is None:
+        print(f"  SKIP: File is empty or invalid")
+        return None
+    
+    # Get institution name
+    org_name = data.get('original_entry', {}).get('organisatie')
+    if not org_name:
+        print(f"  ERROR: No organisatie found in original_entry")
+        return None
+    
+    print(f"  Institution: {org_name}")
+    
+    # Get current GHCID info
+    ghcid_data = data.get('ghcid', {})
+    old_ghcid = ghcid_data.get('ghcid_current', '')
+    print(f"  Old GHCID: {old_ghcid}")
+    
+    # Extract base GHCID from filename (remove trailing dash)
+    base_ghcid = file_path.stem.rstrip('-')
+    print(f"  Base GHCID: {base_ghcid}")
+    
+    # Generate new name suffix from institution name
+    name_suffix = generate_name_suffix(org_name)
+    print(f"  Name suffix: {name_suffix}")
+    
+    # Create new GHCID
+    new_ghcid = f"{base_ghcid}-{name_suffix}"
+    print(f"  New GHCID: {new_ghcid}")
+    
+    # Check if this would be the same as old (only filename is wrong)
+    if new_ghcid == old_ghcid:
+        expected_filename = f"{new_ghcid}.yaml"
+        if file_path.name != expected_filename:
+            print(f"  GHCID correct, but filename wrong - needs rename only")
+            if dry_run:
+                print(f"  DRY RUN: Would rename to {expected_filename}")
+                return None
+            
+            new_file_path = file_path.parent / expected_filename
+            if new_file_path.exists():
+                print(f"  ERROR: Target file already exists: {new_file_path.name}")
+                return None
+            
+            shutil.move(str(file_path), str(new_file_path))
+            print(f"  Renamed: {file_path.name} → {new_file_path.name}")
+            return new_file_path
+        else:
+            print(f"  SKIP: GHCID and filename both correct")
+            return None
+    
+    # Generate new identifiers
+    new_uuid = generate_ghcid_uuid(new_ghcid)
+    new_uuid_sha256 = generate_ghcid_uuid_sha256(new_ghcid)
+    new_numeric = generate_ghcid_numeric(new_ghcid)
+    
+    print(f"  New UUID: {new_uuid}")
+    print(f"  New numeric: {new_numeric}")
+    
+    if dry_run:
+        print(f"  DRY RUN: Would update file and rename to {new_ghcid}.yaml")
+        return None
+    
+    # Update GHCID section
+    timestamp = datetime.now(timezone.utc).isoformat()
+    
+    # Preserve old GHCID in history
+    ghcid_history = ghcid_data.get('ghcid_history', [])
+    
+    # Add history entry for the fix
+    ghcid_history.append({
+        'ghcid': old_ghcid,
+        'ghcid_uuid': ghcid_data.get('ghcid_uuid', ''),
+        'ghcid_numeric': ghcid_data.get('ghcid_numeric', 0),
+        'valid_from': ghcid_data.get('generated_at', ''),
+        'valid_to': timestamp,
+        'reason': f"Collision fix: had partner's GHCID, corrected to institution's own GHCID based on name '{org_name}'"
+    })
+    
+    data['ghcid'] = {
+        'ghcid_current': new_ghcid,
+        'ghcid_uuid': new_uuid,
+        'ghcid_uuid_sha256': new_uuid_sha256,
+        'ghcid_numeric': new_numeric,
+        'generated_at': timestamp,
+        'ghcid_history': ghcid_history
+    }
+    
+    # Update identifiers list
+    identifiers = data.get('identifiers', [])
+    updated_identifiers = []
+    for ident in identifiers:
+        scheme = ident.get('identifier_scheme', '')
+        if scheme == 'GHCID':
+            ident['identifier_value'] = new_ghcid
+            ident['identifier_url'] = f"https://w3id.org/heritage/custodian/{new_ghcid}"
+        elif scheme == 'GHCID_UUID':
+            ident['identifier_value'] = new_uuid
+        elif scheme == 'GHCID_NUMERIC':
+            ident['identifier_value'] = str(new_numeric)
+        updated_identifiers.append(ident)
+    data['identifiers'] = updated_identifiers
+    
+    # Write updated data back to file
+    with open(file_path, 'w') as f:
+        yaml.dump(data, f, default_flow_style=False, allow_unicode=True, sort_keys=False)
+    
+    print(f"  Updated file content")
+    
+    # Rename file to match new GHCID
+    new_file_path = file_path.parent / f"{new_ghcid}.yaml"
+    
+    if new_file_path.exists():
+        print(f"  ERROR: Target file already exists: {new_file_path.name}")
+        return None
+    
+    shutil.move(str(file_path), str(new_file_path))
+    print(f"  Renamed: {file_path.name} → {new_file_path.name}")
+    
+    return new_file_path
+
+
+def main():
+    import argparse
+    
+    parser = argparse.ArgumentParser(description='Fix GHCID collision victim files')
+    parser.add_argument('--dry-run', action='store_true', help='Only show what would be done')
+    parser.add_argument('--file', type=str, help='Process only this specific file')
+    args = parser.parse_args()
+    
+    custodian_dir = Path('data/custodian')
+    
+    if args.file:
+        files = [Path(args.file)]
+    else:
+        # Find all collision victim files (trailing dash pattern)
+        files = sorted(custodian_dir.glob('NL-*-.yaml'))
+    
+    print(f"Found {len(files)} collision victim file(s)")
+    
+    fixed = 0
+    skipped = 0
+    errors = 0
+    
+    for f in files:
+        result = fix_collision_victim(f, dry_run=args.dry_run)
+        if result:
+            fixed += 1
+        elif result is None:
+            # Check if it was empty
+            if f.stat().st_size == 0:
+                print(f"\n  EMPTY FILE: {f.name} - should be deleted")
+                errors += 1
+            else:
+                skipped += 1
+    
+    print(f"\n{'='*80}")
+    print(f"SUMMARY")
+    print(f"{'='*80}")
+    print(f"  Fixed: {fixed}")
+    print(f"  Skipped: {skipped}")
+    print(f"  Errors/Empty: {errors}")
+
+
+if __name__ == '__main__':
+    main()

scripts/fix_generic_platform_names.py

@@ -0,0 +1,140 @@
+#!/usr/bin/env python3
+"""
+Fix generic platform names ('Home Website', 'Homepage Website') by using
+the organisatie field from original_entry.
+
+Also filters invalid platform types (ONLINEMARKETING, ONLINEBRANDING).
+"""
+
+import yaml
+import os
+import sys
+from pathlib import Path
+from datetime import datetime, timezone
+
+# Custom YAML representer to preserve formatting
+def str_representer(dumper, data):
+    if '\n' in data:
+        return dumper.represent_scalar('tag:yaml.org,2002:str', data, style='|')
+    return dumper.represent_scalar('tag:yaml.org,2002:str', data)
+
+yaml.add_representer(str, str_representer)
+
+GENERIC_NAMES = {'Home Website', 'Homepage Website', 'Welkom Website'}
+INVALID_TYPES = {'ONLINEMARKETING', 'ONLINEBRANDING', 'ONLINEWEBSITE', 'ONLINE'}
+
+def fix_file(filepath: Path, dry_run: bool = False) -> dict:
+    """Fix a single file. Returns stats dict."""
+    stats = {
+        'name_fixed': False,
+        'types_fixed': False,
+        'old_name': None,
+        'new_name': None,
+        'removed_types': []
+    }
+    
+    with open(filepath, 'r', encoding='utf-8') as f:
+        data = yaml.safe_load(f)
+    
+    if not data:
+        return stats
+    
+    # Check if file has digital_platform_v2
+    if 'digital_platform_v2' not in data:
+        return stats
+    
+    dpv2 = data['digital_platform_v2']
+    modified = False
+    
+    # Fix 1: Generic platform names
+    current_name = dpv2.get('platform_name', '')
+    if current_name in GENERIC_NAMES:
+        # Try to get organisation name
+        org_name = None
+        if 'original_entry' in data and 'organisatie' in data['original_entry']:
+            org_name = data['original_entry']['organisatie']
+        elif 'museum_register_enrichment' in data and 'museum_name' in data['museum_register_enrichment']:
+            org_name = data['museum_register_enrichment']['museum_name']
+        elif 'wikidata_enrichment' in data and 'wikidata_label_nl' in data['wikidata_enrichment']:
+            org_name = data['wikidata_enrichment']['wikidata_label_nl']
+        
+        if org_name:
+            new_name = f"{org_name} Website"
+            stats['old_name'] = current_name
+            stats['new_name'] = new_name
+            stats['name_fixed'] = True
+            dpv2['platform_name'] = new_name
+            modified = True
+    
+    # Fix 2: Invalid platform types
+    if 'platform_type' in dpv2 and isinstance(dpv2['platform_type'], list):
+        original_types = dpv2['platform_type'].copy()
+        filtered_types = [t for t in original_types if t not in INVALID_TYPES]
+        
+        if len(filtered_types) < len(original_types):
+            stats['removed_types'] = [t for t in original_types if t in INVALID_TYPES]
+            stats['types_fixed'] = True
+            dpv2['platform_type'] = filtered_types if filtered_types else ['INSTITUTIONAL_WEBSITE']
+            modified = True
+    
+    # Add fix metadata
+    if modified:
+        if '_transformation_metadata' not in dpv2:
+            dpv2['_transformation_metadata'] = {}
+        dpv2['_transformation_metadata']['quality_fix_date'] = datetime.now(timezone.utc).isoformat()
+        if stats['name_fixed']:
+            dpv2['_transformation_metadata']['name_source'] = 'organisatie_field'
+        
+        if not dry_run:
+            with open(filepath, 'w', encoding='utf-8') as f:
+                yaml.dump(data, f, default_flow_style=False, allow_unicode=True, sort_keys=False)
+    
+    return stats
+
+
+def main():
+    import argparse
+    parser = argparse.ArgumentParser(description='Fix generic platform names')
+    parser.add_argument('--dry-run', action='store_true', help='Show what would be changed without modifying files')
+    parser.add_argument('--path', default='/Users/kempersc/apps/glam/data/custodian', help='Path to custodian files')
+    args = parser.parse_args()
+    
+    custodian_path = Path(args.path)
+    
+    # Find files with digital_platform_v2
+    files_fixed_names = 0
+    files_fixed_types = 0
+    total_checked = 0
+    
+    print(f"{'[DRY RUN] ' if args.dry_run else ''}Scanning {custodian_path}...")
+    print()
+    
+    for filepath in sorted(custodian_path.glob('NL-*.yaml')):
+        stats = fix_file(filepath, dry_run=args.dry_run)
+        
+        if stats['name_fixed'] or stats['types_fixed']:
+            total_checked += 1
+            
+            if stats['name_fixed']:
+                files_fixed_names += 1
+                print(f"✓ {filepath.name}")
+                print(f"  Name: '{stats['old_name']}' → '{stats['new_name']}'")
+            
+            if stats['types_fixed']:
+                files_fixed_types += 1
+                print(f"  Removed types: {stats['removed_types']}")
+    
+    print()
+    print("=" * 60)
+    print(f"{'[DRY RUN] ' if args.dry_run else ''}Summary:")
+    print(f"  Files with name fixed: {files_fixed_names}")
+    print(f"  Files with types fixed: {files_fixed_types}")
+    print(f"  Total files modified: {total_checked}")
+    
+    if args.dry_run:
+        print()
+        print("Run without --dry-run to apply changes.")
+
+
+if __name__ == '__main__':
+    main()

scripts/fix_generic_platform_names_fast.py

@@ -0,0 +1,97 @@
+#!/usr/bin/env python3
+"""
+Fast fix for generic platform names - processes only files from stdin or file list.
+"""
+
+import yaml
+import sys
+from pathlib import Path
+from datetime import datetime, timezone
+
+GENERIC_NAMES = {'Home Website', 'Homepage Website', 'Welkom Website'}
+INVALID_TYPES = {'ONLINEMARKETING', 'ONLINEBRANDING', 'ONLINEWEBSITE', 'ONLINE'}
+
+def fix_file(filepath: Path, dry_run: bool = False) -> dict:
+    """Fix a single file."""
+    stats = {'name_fixed': False, 'types_fixed': False, 'old_name': None, 'new_name': None, 'removed_types': []}
+    
+    with open(filepath, 'r', encoding='utf-8') as f:
+        content = f.read()
+        data = yaml.safe_load(content)
+    
+    if not data or 'digital_platform_v2' not in data:
+        return stats
+    
+    dpv2 = data['digital_platform_v2']
+    modified = False
+    
+    # Fix generic names
+    current_name = dpv2.get('platform_name', '')
+    if current_name in GENERIC_NAMES:
+        org_name = None
+        if 'original_entry' in data and data['original_entry'].get('organisatie'):
+            org_name = data['original_entry']['organisatie']
+        elif 'museum_register_enrichment' in data and data['museum_register_enrichment'].get('museum_name'):
+            org_name = data['museum_register_enrichment']['museum_name']
+        elif 'wikidata_enrichment' in data and data['wikidata_enrichment'].get('wikidata_label_nl'):
+            org_name = data['wikidata_enrichment']['wikidata_label_nl']
+        
+        if org_name:
+            new_name = f"{org_name} Website"
+            stats['old_name'] = current_name
+            stats['new_name'] = new_name
+            stats['name_fixed'] = True
+            dpv2['platform_name'] = new_name
+            modified = True
+    
+    # Fix invalid types
+    if 'platform_type' in dpv2 and isinstance(dpv2['platform_type'], list):
+        original_types = dpv2['platform_type'].copy()
+        filtered_types = [t for t in original_types if t not in INVALID_TYPES]
+        if len(filtered_types) < len(original_types):
+            stats['removed_types'] = [t for t in original_types if t in INVALID_TYPES]
+            stats['types_fixed'] = True
+            dpv2['platform_type'] = filtered_types if filtered_types else ['INSTITUTIONAL_WEBSITE']
+            modified = True
+    
+    if modified:
+        if '_transformation_metadata' not in dpv2:
+            dpv2['_transformation_metadata'] = {}
+        dpv2['_transformation_metadata']['quality_fix_date'] = datetime.now(timezone.utc).isoformat()
+        
+        if not dry_run:
+            with open(filepath, 'w', encoding='utf-8') as f:
+                yaml.dump(data, f, default_flow_style=False, allow_unicode=True, sort_keys=False)
+    
+    return stats
+
+def main():
+    dry_run = '--dry-run' in sys.argv
+    file_list = sys.argv[1] if len(sys.argv) > 1 and not sys.argv[1].startswith('--') else None
+    
+    if file_list:
+        with open(file_list) as f:
+            files = [Path(line.strip()) for line in f if line.strip()]
+    else:
+        files = [Path(line.strip()) for line in sys.stdin if line.strip()]
+    
+    fixed_names = 0
+    fixed_types = 0
+    
+    for filepath in files:
+        if not filepath.exists():
+            continue
+        stats = fix_file(filepath, dry_run=dry_run)
+        
+        if stats['name_fixed'] or stats['types_fixed']:
+            if stats['name_fixed']:
+                fixed_names += 1
+                print(f"✓ {filepath.name}: '{stats['old_name']}' → '{stats['new_name']}'")
+            if stats['types_fixed']:
+                fixed_types += 1
+                print(f"  Removed: {stats['removed_types']}")
+    
+    print(f"\n{'[DRY RUN] ' if dry_run else ''}Fixed: {fixed_names} names, {fixed_types} type lists")
+
+if __name__ == '__main__':
+    main()

scripts/fix_ghcid_type.py

@@ -0,0 +1,523 @@
+#!/usr/bin/env python3
+"""
+Fix GHCID type codes in Dutch custodian files.
+
+This script corrects GHCID type codes (position 4) for files where the
+type was incorrectly assigned. Common corrections:
+- U→M: Unknown should be Museum
+- U→I: Unknown should be Intangible Heritage
+- U→T: Unknown should be Taste/Smell Heritage
+- X→I: Mixed should be Intangible Heritage (single type)
+
+Usage:
+    # Dry run (preview changes)
+    python scripts/fix_ghcid_type.py --dry-run
+    
+    # Apply fixes
+    python scripts/fix_ghcid_type.py
+    
+    # Process specific correction type only
+    python scripts/fix_ghcid_type.py --correction U-to-I --dry-run
+    python scripts/fix_ghcid_type.py --correction U-to-M
+    
+    # Process a single file
+    python scripts/fix_ghcid_type.py --file data/custodian/NL-DR-FRE-U-FCFE.yaml --new-type I
+
+Author: GLAM Data Quality Team
+Date: 2025-12-14
+"""
+
+import argparse
+import hashlib
+import shutil
+import uuid
+from datetime import datetime, timezone
+from pathlib import Path
+from typing import Optional
+
+import yaml
+
+# GHCID namespace for UUID v5 generation (same as DNS namespace per project spec)
+GHCID_NAMESPACE = uuid.UUID("6ba7b810-9dad-11d1-80b4-00c04fd430c8")
+
+# Type code corrections: filename pattern -> new type code
+# These are determined by analyzing original_entry.type_organisatie in each file
+#
+# Current U-type breakdown (173 files):
+#   - 143 files: type_organisatie: museum → should be M
+#   - 14 files: type_organisatie: intangible_heritage_custodian → should be I
+#   - 7 files: type_organisatie: unknown → keep as U (correct)
+#
+# Current X-type files (2 files):
+#   - Both are intangible_heritage_custodian → should be I (single type, not mixed)
+#
+TYPE_CORRECTIONS = {
+    # U→I: Intangible heritage custodians incorrectly marked as Unknown (14 files)
+    "U-to-I": {
+        "files": [
+            "NL-DR-FRE-U-FCFE.yaml",
+            "NL-GE-TIE-U-BO.yaml",
+            "NL-LI-VAL-U-C.yaml",
+            "NL-NH-AMS-U-C.yaml",
+            "NL-NH-ASS-U-HA.yaml",
+            "NL-NH-SAN-U-HSO.yaml",
+            "NL-OV-GEN-U-GB.yaml",
+            "NL-OV-GEN-U-GMS.yaml",
+            "NL-OV-OMM-U-EO.yaml",
+            "NL-OV-SAA-U-BS.yaml",
+            "NL-ZH-BOD-U-GB.yaml",
+            "NL-ZH-GOU-U-BI.yaml",
+            "NL-ZH-HIL-U-HHO.yaml",
+            "NL-ZH-LIS-U-HLO.yaml",
+        ],
+        "old_type": "U",
+        "new_type": "I",
+        "reason": "Type corrected: intangible_heritage_custodian should use type I (Intangible Heritage), not U (Unknown)",
+    },
+    # X→I: Mixed type should be Intangible (single primary type) (2 files)
+    "X-to-I": {
+        "files": [
+            "NL-OV-KAL-X-BW.yaml",
+            "NL-GE-HAT-X-IGR.yaml",
+        ],
+        "old_type": "X",
+        "new_type": "I",
+        "reason": "Type corrected: intangible_heritage_custodian should use type I (Intangible Heritage), not X (Mixed)",
+    },
+    # U→M: Museums incorrectly marked as Unknown (143 files)
+    # Use --auto-detect-museums flag to populate this list dynamically
+    "U-to-M": {
+        "files": [
+            # Auto-detected by checking original_entry.type_organisatie == "museum"
+            # Run with: python scripts/fix_ghcid_type.py --auto-detect-museums --dry-run
+        ],
+        "old_type": "U",
+        "new_type": "M",
+        "reason": "Type corrected: museum should use type M (Museum), not U (Unknown)",
+    },
+}
+
+
+def generate_uuid_v5(ghcid_string: str) -> str:
+    """Generate deterministic UUID v5 from GHCID string."""
+    return str(uuid.uuid5(GHCID_NAMESPACE, ghcid_string))
+
+
+def generate_uuid_v8_sha256(ghcid_string: str) -> str:
+    """Generate UUID v8 from SHA-256 hash of GHCID string."""
+    sha256_hash = hashlib.sha256(ghcid_string.encode('utf-8')).digest()
+    # Take first 16 bytes for UUID
+    uuid_bytes = bytearray(sha256_hash[:16])
+    # Set version to 8 (custom)
+    uuid_bytes[6] = (uuid_bytes[6] & 0x0f) | 0x80
+    # Set variant to RFC 4122
+    uuid_bytes[8] = (uuid_bytes[8] & 0x3f) | 0x80
+    return str(uuid.UUID(bytes=bytes(uuid_bytes)))
+
+
+def generate_numeric_id(ghcid_string: str) -> int:
+    """Generate 64-bit numeric ID from SHA-256 hash."""
+    sha256_hash = hashlib.sha256(ghcid_string.encode('utf-8')).digest()
+    # Take first 8 bytes as 64-bit unsigned integer
+    numeric_id = int.from_bytes(sha256_hash[:8], byteorder='big')
+    return numeric_id
+
+
+def fix_ghcid_type(ghcid: str, old_type: str, new_type: str) -> str:
+    """
+    Replace the type code in a GHCID string.
+    
+    GHCID format: CC-RR-CCC-T-ABBREV[-suffix]
+    Position 4 (0-indexed 3) is the type code.
+    
+    Examples:
+        NL-DR-FRE-U-FCFE → NL-DR-FRE-I-FCFE
+        NL-OV-KAL-X-BW → NL-OV-KAL-I-BW
+    """
+    parts = ghcid.split('-')
+    if len(parts) < 5:
+        raise ValueError(f"Invalid GHCID format: {ghcid}")
+    
+    current_type = parts[3]
+    if current_type != old_type:
+        raise ValueError(f"Expected type '{old_type}' but found '{current_type}' in GHCID: {ghcid}")
+    
+    parts[3] = new_type
+    return '-'.join(parts)
+
+
+def process_file(
+    file_path: Path,
+    old_type: str,
+    new_type: str,
+    reason: str,
+    dry_run: bool = True
+) -> Optional[dict]:
+    """
+    Process a single YAML file to fix GHCID type code.
+    
+    Returns dict with change info, or None if no change needed or error.
+    """
+    try:
+        with open(file_path, 'r', encoding='utf-8') as f:
+            data = yaml.safe_load(f)
+    except Exception as e:
+        print(f"  Error reading {file_path}: {e}")
+        return None
+    
+    if not data or 'ghcid' not in data:
+        print(f"  Warning: No ghcid section in {file_path}")
+        return None
+    
+    ghcid_section = data.get('ghcid', {})
+    old_ghcid = ghcid_section.get('ghcid_current', '')
+    
+    if not old_ghcid:
+        print(f"  Warning: No ghcid_current in {file_path}")
+        return None
+    
+    # Check if the type matches what we expect to fix
+    parts = old_ghcid.split('-')
+    if len(parts) < 5:
+        print(f"  Warning: Invalid GHCID format in {file_path}: {old_ghcid}")
+        return None
+    
+    current_type = parts[3]
+    if current_type != old_type:
+        print(f"  Skipping {file_path}: type is '{current_type}', expected '{old_type}'")
+        return None
+    
+    # Fix the GHCID
+    try:
+        new_ghcid = fix_ghcid_type(old_ghcid, old_type, new_type)
+    except ValueError as e:
+        print(f"  Error: {e}")
+        return None
+    
+    if new_ghcid == old_ghcid:
+        return None
+    
+    # Generate new identifiers
+    new_uuid_v5 = generate_uuid_v5(new_ghcid)
+    new_uuid_v8 = generate_uuid_v8_sha256(new_ghcid)
+    new_numeric = generate_numeric_id(new_ghcid)
+    timestamp_now = datetime.now(timezone.utc).isoformat()
+    
+    change_info = {
+        'file': str(file_path),
+        'old_ghcid': old_ghcid,
+        'new_ghcid': new_ghcid,
+        'old_type': old_type,
+        'new_type': new_type,
+        'old_uuid': ghcid_section.get('ghcid_uuid', ''),
+        'new_uuid': new_uuid_v5,
+        'old_numeric': ghcid_section.get('ghcid_numeric', 0),
+        'new_numeric': new_numeric,
+    }
+    
+    if dry_run:
+        return change_info
+    
+    # Update ghcid section
+    ghcid_section['ghcid_current'] = new_ghcid
+    ghcid_section['ghcid_uuid'] = new_uuid_v5
+    ghcid_section['ghcid_uuid_sha256'] = new_uuid_v8
+    ghcid_section['ghcid_numeric'] = new_numeric
+    # Keep ghcid_original as-is (for historical reference)
+    
+    # Add history entry for the fix
+    ghcid_history = ghcid_section.get('ghcid_history', [])
+    
+    # Add new entry at the beginning
+    new_history_entry = {
+        'ghcid': new_ghcid,
+        'ghcid_numeric': new_numeric,
+        'valid_from': timestamp_now,
+        'reason': reason,
+    }
+    
+    # Mark previous entry as superseded
+    if ghcid_history:
+        if 'valid_to' not in ghcid_history[0] or ghcid_history[0]['valid_to'] is None:
+            ghcid_history[0]['valid_to'] = timestamp_now
+            ghcid_history[0]['superseded_by'] = new_ghcid
+    
+    ghcid_section['ghcid_history'] = [new_history_entry] + ghcid_history
+    data['ghcid'] = ghcid_section
+    
+    # Update identifiers section
+    identifiers = data.get('identifiers', [])
+    for ident in identifiers:
+        scheme = ident.get('identifier_scheme')
+        if scheme == 'GHCID':
+            ident['identifier_value'] = new_ghcid
+        elif scheme == 'GHCID_UUID':
+            ident['identifier_value'] = new_uuid_v5
+            ident['identifier_url'] = f"urn:uuid:{new_uuid_v5}"
+        elif scheme == 'GHCID_UUID_SHA256':
+            ident['identifier_value'] = new_uuid_v8
+            ident['identifier_url'] = f"urn:uuid:{new_uuid_v8}"
+        elif scheme == 'GHCID_NUMERIC':
+            ident['identifier_value'] = str(new_numeric)
+    data['identifiers'] = identifiers
+    
+    # Also update original_entry.type if present (to keep consistency)
+    if 'original_entry' in data and 'type' in data['original_entry']:
+        # Update type list to use new type
+        current_types = data['original_entry']['type']
+        if isinstance(current_types, list):
+            # Replace old type with new type in the list
+            data['original_entry']['type'] = [
+                new_type if t == old_type else t for t in current_types
+            ]
+    
+    # Write updated file
+    with open(file_path, 'w', encoding='utf-8') as f:
+        yaml.dump(data, f, allow_unicode=True, default_flow_style=False, sort_keys=False)
+    
+    # Rename file to match new GHCID
+    old_filename = file_path.name
+    new_filename = f"{new_ghcid}.yaml"
+    
+    if old_filename != new_filename:
+        new_file_path = file_path.parent / new_filename
+        if new_file_path.exists():
+            print(f"  Warning: Target file already exists: {new_file_path}")
+            # Don't rename if target exists
+        else:
+            shutil.move(str(file_path), str(new_file_path))
+            change_info['new_file'] = str(new_file_path)
+    
+    return change_info
+
+
+def find_files_for_correction(
+    custodian_dir: Path,
+    correction_key: str
+) -> list[Path]:
+    """Find files that need the specified type correction."""
+    correction = TYPE_CORRECTIONS.get(correction_key)
+    if not correction:
+        print(f"Unknown correction type: {correction_key}")
+        return []
+    
+    files = []
+    for filename in correction['files']:
+        file_path = custodian_dir / filename
+        if file_path.exists():
+            files.append(file_path)
+        else:
+            print(f"  Warning: File not found: {file_path}")
+    
+    return files
+
+
+def auto_detect_museum_files(custodian_dir: Path) -> list[Path]:
+    """
+    Auto-detect files where type should be M (Museum) based on:
+    - original_entry.type_organisatie == "museum"
+    - Current GHCID type is U (Unknown)
+    """
+    museum_files = []
+    
+    # Find all NL-*-U-*.yaml files (Dutch files with Unknown type)
+    for file_path in custodian_dir.glob("NL-*-U-*.yaml"):
+        try:
+            with open(file_path, 'r', encoding='utf-8') as f:
+                data = yaml.safe_load(f)
+            
+            if not data:
+                continue
+            
+            # Check if type_organisatie indicates this is a museum
+            orig_entry = data.get('original_entry', {})
+            type_org = orig_entry.get('type_organisatie', '').lower()
+            
+            if type_org == 'museum':
+                museum_files.append(file_path)
+        except Exception:
+            continue
+    
+    return museum_files
+
+
+def main():
+    parser = argparse.ArgumentParser(
+        description="Fix GHCID type codes in Dutch custodian files"
+    )
+    parser.add_argument(
+        '--dry-run',
+        action='store_true',
+        help='Preview changes without modifying files'
+    )
+    parser.add_argument(
+        '--correction',
+        choices=['U-to-I', 'U-to-M', 'X-to-I', 'all'],
+        default='all',
+        help='Which correction type to apply (default: all)'
+    )
+    parser.add_argument(
+        '--file',
+        type=str,
+        help='Process a single file instead of batch'
+    )
+    parser.add_argument(
+        '--new-type',
+        type=str,
+        help='New type code when processing single file'
+    )
+    parser.add_argument(
+        '--auto-detect-museums',
+        action='store_true',
+        help='Auto-detect museum files based on type_organisatie field'
+    )
+    parser.add_argument(
+        '--custodian-dir',
+        type=str,
+        default='data/custodian',
+        help='Path to custodian directory (default: data/custodian)'
+    )
+    
+    args = parser.parse_args()
+    
+    # Find project root (where data/ directory is)
+    script_dir = Path(__file__).parent
+    project_root = script_dir.parent
+    custodian_dir = project_root / args.custodian_dir
+    
+    if not custodian_dir.exists():
+        print(f"Error: Custodian directory not found: {custodian_dir}")
+        return 1
+    
+    print(f"GHCID Type Correction Script")
+    print(f"{'=' * 50}")
+    print(f"Mode: {'DRY RUN' if args.dry_run else 'APPLY CHANGES'}")
+    print(f"Custodian directory: {custodian_dir}")
+    print()
+    
+    all_changes = []
+    
+    # Single file mode
+    if args.file:
+        if not args.new_type:
+            print("Error: --new-type is required when using --file")
+            return 1
+        
+        file_path = Path(args.file)
+        if not file_path.is_absolute():
+            file_path = project_root / file_path
+        
+        if not file_path.exists():
+            print(f"Error: File not found: {file_path}")
+            return 1
+        
+        # Detect old type from filename
+        parts = file_path.stem.split('-')
+        if len(parts) >= 4:
+            old_type = parts[3]
+        else:
+            print(f"Error: Cannot determine type from filename: {file_path}")
+            return 1
+        
+        reason = f"Type corrected: {old_type} → {args.new_type} (manual correction)"
+        
+        print(f"Processing single file: {file_path}")
+        change = process_file(file_path, old_type, args.new_type, reason, args.dry_run)
+        if change:
+            all_changes.append(change)
+    
+    # Auto-detect museum files
+    elif args.auto_detect_museums:
+        print("Auto-detecting museum files...")
+        museum_files = auto_detect_museum_files(custodian_dir)
+        print(f"Found {len(museum_files)} museum files with type U")
+        
+        # Update the U-to-M correction with detected files
+        TYPE_CORRECTIONS['U-to-M']['files'] = [f.name for f in museum_files]
+        
+        # Process them
+        correction = TYPE_CORRECTIONS['U-to-M']
+        for file_path in museum_files:
+            change = process_file(
+                file_path,
+                correction['old_type'],
+                correction['new_type'],
+                correction['reason'],
+                args.dry_run
+            )
+            if change:
+                all_changes.append(change)
+    
+    # Batch mode
+    else:
+        corrections_to_apply = []
+        
+        if args.correction == 'all':
+            corrections_to_apply = list(TYPE_CORRECTIONS.keys())
+        else:
+            corrections_to_apply = [args.correction]
+        
+        for correction_key in corrections_to_apply:
+            correction = TYPE_CORRECTIONS[correction_key]
+            
+            if not correction['files']:
+                print(f"\nSkipping {correction_key}: no files specified")
+                continue
+            
+            print(f"\nProcessing {correction_key}:")
+            print(f"  {correction['old_type']} → {correction['new_type']}")
+            print(f"  Files: {len(correction['files'])}")
+            
+            files = find_files_for_correction(custodian_dir, correction_key)
+            
+            for file_path in files:
+                change = process_file(
+                    file_path,
+                    correction['old_type'],
+                    correction['new_type'],
+                    correction['reason'],
+                    args.dry_run
+                )
+                if change:
+                    all_changes.append(change)
+    
+    # Summary
+    print(f"\n{'=' * 50}")
+    print(f"SUMMARY")
+    print(f"{'=' * 50}")
+    
+    if not all_changes:
+        print("No changes needed or no matching files found.")
+        return 0
+    
+    print(f"Total changes: {len(all_changes)}")
+    print()
+    
+    # Group by type change
+    by_type_change = {}
+    for change in all_changes:
+        key = f"{change['old_type']}→{change['new_type']}"
+        if key not in by_type_change:
+            by_type_change[key] = []
+        by_type_change[key].append(change)
+    
+    for key, changes in sorted(by_type_change.items()):
+        print(f"\n{key}: {len(changes)} files")
+        for change in changes:
+            print(f"  {change['old_ghcid']} → {change['new_ghcid']}")
+            if 'new_file' in change:
+                print(f"    Renamed to: {Path(change['new_file']).name}")
+    
+    if args.dry_run:
+        print(f"\n{'=' * 50}")
+        print("DRY RUN - No files were modified.")
+        print("Run without --dry-run to apply changes.")
+    else:
+        print(f"\n{'=' * 50}")
+        print(f"Successfully updated {len(all_changes)} files.")
+    
+    return 0
+
+
+if __name__ == '__main__':
+    exit(main())

scripts/fix_simon_kemper_contamination.py

@@ -0,0 +1,269 @@
+#!/usr/bin/env python3
+"""
+Fix Simon Kemper contamination in entity profiles.
+
+For entries where:
+1. Name is "Simon Kemper" 
+2. But the LinkedIn slug clearly indicates a different person
+
+We derive the correct name from the slug and update the profile.
+
+IMPORTANT: Per Rule 21 (Data Fabrication Prohibition) - if we cannot reliably
+derive the name from the slug, we mark it as "Unknown" rather than guessing.
+Compound slugs without hyphens (like "jponjee") cannot be reliably parsed.
+"""
+
+import json
+import os
+import re
+from pathlib import Path
+from urllib.parse import unquote
+from datetime import datetime, timezone
+
+
+def is_compound_slug(slug: str) -> bool:
+    """Check if slug is a compound name without separators.
+    
+    Returns True for slugs like:
+        - 'jponjee' (no hyphens, all lowercase)
+        - 'sharellyemanuelson'
+        - 'addieroelofsen'
+        - 'adheliap'
+    
+    Returns False for slugs like:
+        - 'willem-blok' (has hyphens)
+        - 'jan-van-den-borre' (has hyphens)
+        - 'miriam-h' (has hyphens, even if short)
+        - 'olivi%C3%AB-7153658' (has hyphens after URL decoding)
+    """
+    # First decode URL encoding (e.g., %C3%AB -> ë)
+    slug = unquote(slug)
+    
+    # After removing trailing ID, check if there are NO hyphens
+    clean_slug = re.sub(r'[-_][\da-f]{6,}$', '', slug)
+    clean_slug = re.sub(r'[-_]\d{5,}$', '', clean_slug)
+    
+    # If no hyphens remain, it's a compound slug that can't be reliably parsed
+    # Even short ones like "jponjee" (7 chars) could be "J. Ponjee" or "J Ponjee"
+    if '-' not in clean_slug:
+        return True
+    
+    return False
+
+
+def slug_to_name(slug: str) -> tuple[str, bool]:
+    """Convert a LinkedIn slug to a human-readable name.
+    
+    Returns:
+        tuple: (name, is_reliable) where:
+            - name: The derived name or "Unknown"
+            - is_reliable: True if we're confident in the derivation
+    
+    Examples:
+        'willem-blok-b6a46648' -> ('Willem Blok', True)
+        'dave-van-den-nieuwenhof-4446b3146' -> ('Dave van den Nieuwenhof', True)
+        'olivi%C3%AB-7153658' -> ('Olivië', True)
+        'jponjee' -> ('Unknown', False)  # Compound slug, cannot parse reliably
+        'sharellyemanuelson' -> ('Unknown', False)  # Compound slug
+    """
+    # Decode URL encoding
+    slug = unquote(slug)
+    
+    # Remove trailing ID (hex or numeric)
+    clean_slug = re.sub(r'[-_][\da-f]{6,}$', '', slug)
+    clean_slug = re.sub(r'[-_]\d{5,}$', '', clean_slug)
+    
+    # Check if this is a compound slug we can't reliably parse
+    if is_compound_slug(slug):
+        return ("Unknown", False)
+    
+    # Split by hyphens
+    parts = clean_slug.split('-')
+    
+    # Filter out empty parts
+    parts = [p for p in parts if p]
+    
+    if not parts:
+        return ("Unknown", False)
+    
+    # Capitalize appropriately
+    # Dutch particles that should stay lowercase: van, de, den, der, het, 't
+    dutch_particles = {'van', 'de', 'den', 'der', 'het', 't', "'t"}
+    
+    name_parts = []
+    for i, part in enumerate(parts):
+        if part.lower() in dutch_particles and i > 0:
+            name_parts.append(part.lower())
+        else:
+            # Capitalize first letter, preserve rest
+            name_parts.append(part.capitalize())
+    
+    name = ' '.join(name_parts)
+    
+    # Additional validation - name should have at least 2 characters
+    if len(name) < 2:
+        return ("Unknown", False)
+    
+    return (name, True)
+
+def fix_contaminated_files(entity_dir: Path, dry_run: bool = True):
+    """Find and fix Simon Kemper contaminated files.
+    
+    Only processes files where name is ACTUALLY "Simon Kemper" (contaminated).
+    Skips files where name was already corrected or was never contaminated.
+    
+    Returns:
+        tuple: (contaminated_list, fixed_list, unreliable_list)
+    """
+    
+    contaminated = []
+    fixed = []
+    unreliable = []  # Files where we couldn't reliably derive the name
+    
+    for filepath in entity_dir.glob("*.json"):
+        try:
+            with open(filepath, 'r', encoding='utf-8') as f:
+                data = json.load(f)
+        except (json.JSONDecodeError, IOError):
+            continue
+        
+        # Check if this is a Simon Kemper contamination
+        profile_name = data.get('profile_data', {}).get('name', '')
+        source_name = data.get('source_staff_info', {}).get('name', '')
+        
+        # ONLY process files where the name is ACTUALLY "Simon Kemper"
+        if profile_name != 'Simon Kemper' and source_name != 'Simon Kemper':
+            continue
+        
+        # Get the slug from filename or URL
+        filename = filepath.name
+        linkedin_url = data.get('extraction_metadata', {}).get('linkedin_url', '')
+        
+        # Extract slug from URL
+        slug_match = re.search(r'/in/([^/]+)/?$', linkedin_url)
+        if not slug_match:
+            continue
+        
+        slug = slug_match.group(1)
+        
+        # Check if this is truly contamination (slug doesn't match simon kemper)
+        slug_lower = slug.lower().replace('%', '')
+        if 'simonkemper' in slug_lower or 'simon-kemper' in slug_lower:
+            # This is the real Simon Kemper, skip
+            continue
+        
+        # Derive correct name from slug
+        correct_name, is_reliable = slug_to_name(slug)
+        
+        entry = {
+            'file': filepath.name,
+            'slug': slug,
+            'profile_name': profile_name,
+            'source_name': source_name,
+            'contaminated_field': 'profile_data.name' if profile_name == 'Simon Kemper' else 'source_staff_info.name',
+            'correct_name': correct_name,
+            'is_reliable': is_reliable,
+            'headline': data.get('profile_data', {}).get('headline', ''),
+            'custodian': data.get('affiliations', [{}])[0].get('custodian_name', '') if data.get('affiliations') else ''
+        }
+        
+        if is_reliable:
+            contaminated.append(entry)
+        else:
+            unreliable.append(entry)
+        
+        if not dry_run:
+            # Fix the data
+            if 'profile_data' in data:
+                data['profile_data']['name'] = correct_name
+            if 'source_staff_info' in data:
+                data['source_staff_info']['name'] = correct_name
+            
+            # Add fix metadata
+            if 'extraction_metadata' not in data:
+                data['extraction_metadata'] = {}
+            
+            if is_reliable:
+                fix_note = f"Name corrected from 'Simon Kemper' (contamination) to '{correct_name}' (derived from slug) on {datetime.now(timezone.utc).isoformat()}"
+            else:
+                fix_note = f"Name set to 'Unknown' (was 'Simon Kemper' contamination). Original slug: {slug}. Compound slug cannot be reliably parsed. Fixed on {datetime.now(timezone.utc).isoformat()}"
+                # Also preserve slug in a dedicated field for future reference
+                data['extraction_metadata']['original_slug'] = slug
+            
+            existing_notes = data['extraction_metadata'].get('notes', '')
+            if existing_notes:
+                data['extraction_metadata']['notes'] = f"{existing_notes} | {fix_note}"
+            else:
+                data['extraction_metadata']['notes'] = fix_note
+            
+            # Write back
+            with open(filepath, 'w', encoding='utf-8') as f:
+                json.dump(data, f, indent=2, ensure_ascii=False)
+            
+            fixed.append(filepath.name)
+    
+    return contaminated, fixed, unreliable
+
+def main():
+    import argparse
+    parser = argparse.ArgumentParser(description='Fix Simon Kemper contamination')
+    parser.add_argument('--fix', action='store_true', help='Actually fix files (default: dry run)')
+    args = parser.parse_args()
+    
+    entity_dir = Path("/Users/kempersc/apps/glam/data/custodian/person/entity")
+    
+    dry_run = not args.fix
+    mode = "DRY RUN" if dry_run else "FIXING"
+    
+    print("=" * 80)
+    print(f"SIMON KEMPER CONTAMINATION FIX - {mode}")
+    print("=" * 80)
+    
+    contaminated, fixed, unreliable = fix_contaminated_files(entity_dir, dry_run=dry_run)
+    
+    print(f"\n{'='*40}")
+    print(f"RELIABLY PARSEABLE ({len(contaminated)} files)")
+    print(f"{'='*40}")
+    print("These slugs have hyphens and can be reliably converted to names:\n")
+    
+    for c in contaminated:
+        print(f"  File: {c['file']}")
+        print(f"  Slug: {c['slug']}")
+        print(f"  Contaminated: {c['contaminated_field']} = 'Simon Kemper'")
+        print(f"  Correct name: '{c['correct_name']}'")
+        headline = c['headline']
+        print(f"  Headline: {headline[:60]}..." if len(headline) > 60 else f"  Headline: {headline}")
+        print(f"  Custodian: {c['custodian']}")
+        print()
+    
+    if unreliable:
+        print(f"\n{'='*40}")
+        print(f"COMPOUND SLUGS - SET TO 'Unknown' ({len(unreliable)} files)")
+        print(f"{'='*40}")
+        print("These slugs have no hyphens and cannot be reliably parsed.")
+        print("Per Rule 21: Names will be set to 'Unknown' (no hallucination).\n")
+        
+        for u in unreliable:
+            print(f"  File: {u['file']}")
+            print(f"  Slug: {u['slug']}")
+            print(f"  Contaminated: {u['contaminated_field']} = 'Simon Kemper'")
+            print(f"  Will be set to: 'Unknown' (slug preserved in metadata)")
+            headline = u['headline']
+            print(f"  Headline: {headline[:60]}..." if len(headline) > 60 else f"  Headline: {headline}")
+            print(f"  Custodian: {u['custodian']}")
+            print()
+    
+    print(f"\n{'='*40}")
+    print("SUMMARY")
+    print(f"{'='*40}")
+    print(f"  Reliably fixable:  {len(contaminated)}")
+    print(f"  Set to 'Unknown':  {len(unreliable)}")
+    print(f"  Total:             {len(contaminated) + len(unreliable)}")
+    
+    if not dry_run:
+        print(f"\n✅ Fixed {len(fixed)} files")
+    else:
+        print(f"\n⚠️  DRY RUN - No files modified. Run with --fix to apply changes.")
+
+if __name__ == "__main__":
+    main()

scripts/parse_linkedin_connections.py

@@ -99,6 +99,62 @@ NON_HERITAGE_KEYWORDS = [
     'organiser', 'opruimhulp', 'verpleeg', 'nurse'
 ]
 
+# Organizations that are explicitly NOT heritage institutions
+# These should never be classified as heritage-relevant
+NON_HERITAGE_ORGANIZATIONS = [
+    # Banks & Financial
+    'ing ', 'ing nederland', 'rabobank', 'abn amro', 'postbank', 'triodos',
+    # Security companies
+    'i-sec', 'g4s', 'securitas', 'trigion', 'chubb',
+    # Police/Government (non-cultural)
+    'politie', 'police', 'rijkswaterstaat', 'belastingdienst', 'douane', 'defensie',
+    # Political parties
+    'vvd', 'pvda', 'cda', 'd66', 'groenlinks', 'pvv', 'bbb', 'nsc', 'volt',
+    'sp ', 'forum voor democratie', 'ja21', 'bij1', 'denk', 'sgp', 'cu ',
+    # Tech companies (non-heritage)
+    'google', 'microsoft', 'amazon', 'meta', 'facebook', 'apple', 'netflix',
+    'uber', 'airbnb', 'booking.com', 'adyen', 'mollie', 'messagebird',
+    'coolblue', 'bol.com', 'picnic', 'takeaway', 'just eat',
+    # Telecom
+    'kpn', 'vodafone', 't-mobile', 'ziggo',
+    # Postal / Logistics
+    'postnl', 'postkantoren', 'dhl', 'ups', 'fedex',
+    # Healthcare
+    'ziekenhuis', 'hospital', 'ggz', 'ggd', 'thuiszorg',
+    # Retail
+    'albert heijn', 'jumbo', 'lidl', 'aldi', 'ikea', 'hema', 'action',
+    # Consulting / Professional services
+    'deloitte', 'kpmg', 'pwc', 'ey ', 'ernst & young', 'mckinsey', 'bcg',
+    'accenture', 'capgemini', 'ordina', 'atos', 'cgi ',
+    # Recruitment / HR
+    'randstad', 'tempo-team', 'manpower', 'hays', 'brunel',
+    # Energy / Utilities
+    'shell', 'bp ', 'eneco', 'vattenfall', 'essent', 'nuon',
+    # Transport
+    'ns ', 'prorail', 'schiphol', 'klm', 'transavia',
+    # Other
+    'freelance', 'zelfstandig', 'zzp', 'eigen bedrijf',
+]
+
+# Heritage organization keywords - organizations that ARE heritage institutions
+# Used to validate that 'D' (Digital) roles are actually at heritage orgs
+HERITAGE_ORGANIZATION_KEYWORDS = [
+    # Archives
+    'archief', 'archive', 'nationaal archief', 'stadsarchief', 'regionaal archief',
+    'beeld en geluid', 'beeld & geluid', 'niod', 'iish', 'iisg',
+    # Museums  
+    'museum', 'musea', 'rijksmuseum', 'van gogh', 'stedelijk', 'mauritshuis',
+    'tropenmuseum', 'allard pierson', 'kröller', 'boijmans',
+    # Libraries
+    'bibliotheek', 'library', 'koninklijke bibliotheek', 'kb ',
+    # Film/AV heritage
+    'eye film', 'filmmuseum', 'eye ', 'sound and vision',
+    # Heritage platforms
+    'erfgoed', 'heritage', 'cultural', 'cultureel',
+    # Research institutes (heritage-focused)
+    'knaw', 'humanities cluster', 'meertens', 'huygens',
+]
+
 # Lines that indicate LinkedIn UI noise (to skip entirely)
 NOISE_EXACT = {
     '0 notifications', 'Search', 'Home', 'My Network', 'Jobs', 'Messaging',
@@ -276,16 +332,35 @@ def is_location_line(line: str) -> bool:
 def detect_heritage_type(headline: str) -> tuple[bool, Optional[str]]:
     """
     Detect if a headline is heritage-relevant and what type.
+    
+    Two-stage classification:
+    1. Check if organization is explicitly non-heritage (blocklist)
+    2. Check if role/organization matches heritage patterns
+    
+    For 'D' (Digital) type, require BOTH a tech role AND a heritage organization.
     """
     headline_lower = headline.lower()
     
-    # Check for non-heritage indicators
+    # Stage 1: Check for non-heritage organizations (blocklist)
+    for org in NON_HERITAGE_ORGANIZATIONS:
+        if org.lower() in headline_lower:
+            return (False, None)
+    
+    # Stage 2: Check for non-heritage role indicators
     for keyword in NON_HERITAGE_KEYWORDS:
         if keyword.lower() in headline_lower:
             return (False, None)
     
+    # Stage 3: Check if this is a heritage organization
+    is_heritage_org = False
+    for org_keyword in HERITAGE_ORGANIZATION_KEYWORDS:
+        if org_keyword.lower() in headline_lower:
+            is_heritage_org = True
+            break
+    
     # Check heritage keywords by type (order matters - more specific first)
-    type_order = ['A', 'M', 'L', 'O', 'R', 'E', 'D', 'G', 'S', 'C']
+    # 'D' (Digital) is checked last and requires heritage org validation
+    type_order = ['A', 'M', 'L', 'G', 'S', 'C', 'O', 'R', 'E']  # D removed from here
     
     for heritage_type in type_order:
         keywords = HERITAGE_KEYWORDS.get(heritage_type, [])
@@ -293,7 +368,15 @@ def detect_heritage_type(headline: str) -> tuple[bool, Optional[str]]:
             if keyword.lower() in headline_lower:
                 return (True, heritage_type)
     
-    # Generic heritage terms
+    # Special handling for 'D' (Digital) - ONLY if at a heritage organization
+    # This prevents generic IT workers from being classified as heritage-relevant
+    if is_heritage_org:
+        digital_keywords = HERITAGE_KEYWORDS.get('D', [])
+        for keyword in digital_keywords:
+            if keyword.lower() in headline_lower:
+                return (True, 'D')
+    
+    # Generic heritage terms (without specific type)
     generic_heritage = [
         'heritage', 'erfgoed', 'culture', 'cultuur', 'cultural',
         'film', 'cinema', 'media', 'arts', 'kunst', 'creative',

scripts/parse_linkedin_html.py

@@ -66,6 +66,62 @@ NON_HERITAGE_KEYWORDS = [
     'investment', 'e-commerce', 'organiser', 'opruimhulp', 'verpleeg', 'nurse'
 ]
 
+# Organizations that are explicitly NOT heritage institutions
+# These should never be classified as heritage-relevant
+NON_HERITAGE_ORGANIZATIONS = [
+    # Banks & Financial
+    'ing ', 'ing nederland', 'rabobank', 'abn amro', 'postbank', 'triodos',
+    # Security companies
+    'i-sec', 'g4s', 'securitas', 'trigion', 'chubb',
+    # Police/Government (non-cultural)
+    'politie', 'police', 'rijkswaterstaat', 'belastingdienst', 'douane', 'defensie',
+    # Political parties
+    'vvd', 'pvda', 'cda', 'd66', 'groenlinks', 'pvv', 'bbb', 'nsc', 'volt',
+    'sp ', 'forum voor democratie', 'ja21', 'bij1', 'denk', 'sgp', 'cu ',
+    # Tech companies (non-heritage)
+    'google', 'microsoft', 'amazon', 'meta', 'facebook', 'apple', 'netflix',
+    'uber', 'airbnb', 'booking.com', 'adyen', 'mollie', 'messagebird',
+    'coolblue', 'bol.com', 'picnic', 'takeaway', 'just eat',
+    # Telecom
+    'kpn', 'vodafone', 't-mobile', 'ziggo',
+    # Postal / Logistics
+    'postnl', 'postkantoren', 'dhl', 'ups', 'fedex',
+    # Healthcare
+    'ziekenhuis', 'hospital', 'ggz', 'ggd', 'thuiszorg',
+    # Retail
+    'albert heijn', 'jumbo', 'lidl', 'aldi', 'ikea', 'hema', 'action',
+    # Consulting / Professional services
+    'deloitte', 'kpmg', 'pwc', 'ey ', 'ernst & young', 'mckinsey', 'bcg',
+    'accenture', 'capgemini', 'ordina', 'atos', 'cgi ',
+    # Recruitment / HR
+    'randstad', 'tempo-team', 'manpower', 'hays', 'brunel',
+    # Energy / Utilities
+    'shell', 'bp ', 'eneco', 'vattenfall', 'essent', 'nuon',
+    # Transport
+    'ns ', 'prorail', 'schiphol', 'klm', 'transavia',
+    # Other
+    'freelance', 'zelfstandig', 'zzp', 'eigen bedrijf',
+]
+
+# Heritage organization keywords - organizations that ARE heritage institutions
+# Used to validate that 'D' (Digital) roles are actually at heritage orgs
+HERITAGE_ORGANIZATION_KEYWORDS = [
+    # Archives
+    'archief', 'archive', 'nationaal archief', 'stadsarchief', 'regionaal archief',
+    'beeld en geluid', 'beeld & geluid', 'niod', 'iish', 'iisg',
+    # Museums  
+    'museum', 'musea', 'rijksmuseum', 'van gogh', 'stedelijk', 'mauritshuis',
+    'tropenmuseum', 'allard pierson', 'kröller', 'boijmans',
+    # Libraries
+    'bibliotheek', 'library', 'koninklijke bibliotheek', 'kb ',
+    # Film/AV heritage
+    'eye film', 'filmmuseum', 'eye ', 'sound and vision',
+    # Heritage platforms
+    'erfgoed', 'heritage', 'cultural', 'cultureel',
+    # Research institutes (heritage-focused)
+    'knaw', 'humanities cluster', 'meertens', 'huygens',
+]
+
 # LinkedIn status phrases that pollute name fields (extracted from img alt text)
 # These should be removed from names and stored as metadata
 LINKEDIN_STATUS_PHRASES = [
@@ -168,8 +224,8 @@ class LinkedInProfileCardParser(HTMLParser):
         
     def handle_starttag(self, tag: str, attrs: list[tuple[str, str | None]]) -> None:
         attrs_dict = dict(attrs)
-        attr_id = attrs_dict.get('id', '')
+        attr_id = attrs_dict.get('id') or ''
-        attr_class = attrs_dict.get('class', '')
+        attr_class = attrs_dict.get('class') or ''
         
         # Detect profile card start - can be on <a> tag (regular) OR <img> tag (anonymous)
         if 'org-people-profile-card__profile-image' in attr_id:
@@ -367,28 +423,58 @@ class LinkedInProfileCardParser(HTMLParser):
 
 
 def detect_heritage_type(headline: str) -> tuple[bool, Optional[str]]:
-    """Detect if a headline is heritage-relevant and what type."""
+    """
+    Detect if a headline is heritage-relevant and what type.
+    
+    Two-stage classification:
+    1. Check if organization is explicitly non-heritage (blocklist)
+    2. Check if role/organization matches heritage patterns
+    
+    For 'D' (Digital) type, require BOTH a tech role AND a heritage organization.
+    This prevents generic IT workers at banks/police from being classified as heritage.
+    """
     if not headline:
         return (False, None)
     
     headline_lower = headline.lower()
     
-    # Check non-heritage first
+    # Stage 1: Check for non-heritage organizations (blocklist)
+    for org in NON_HERITAGE_ORGANIZATIONS:
+        if org.lower() in headline_lower:
+            return (False, None)
+    
+    # Stage 2: Check for non-heritage role indicators
     for keyword in NON_HERITAGE_KEYWORDS:
         if keyword.lower() in headline_lower:
             return (False, None)
     
-    # Check heritage keywords by type
+    # Stage 3: Check if this is a heritage organization
-    type_order = ['A', 'M', 'L', 'O', 'R', 'E', 'D', 'G', 'S', 'C']
+    is_heritage_org = False
+    for org_keyword in HERITAGE_ORGANIZATION_KEYWORDS:
+        if org_keyword.lower() in headline_lower:
+            is_heritage_org = True
+            break
+    
+    # Check heritage keywords by type (order matters - more specific first)
+    # 'D' (Digital) is checked last and requires heritage org validation
+    type_order = ['A', 'M', 'L', 'G', 'S', 'C', 'O', 'R', 'E']  # D removed from main loop
+    
     for heritage_type in type_order:
         keywords = HERITAGE_KEYWORDS.get(heritage_type, [])
         for keyword in keywords:
             if keyword.lower() in headline_lower:
                 return (True, heritage_type)
     
-    # Generic heritage terms
+    # Special handling for 'D' (Digital) - ONLY if at a heritage organization
+    if is_heritage_org:
+        digital_keywords = HERITAGE_KEYWORDS.get('D', [])
+        for keyword in digital_keywords:
+            if keyword.lower() in headline_lower:
+                return (True, 'D')
+    
+    # Generic heritage terms (without specific type)
     generic = ['heritage', 'erfgoed', 'culture', 'cultuur', 'cultural', 'film', 'cinema',
-               'media', 'arts', 'kunst', 'creative', 'preservation', 'conservation']
+               'media', 'arts', 'kunst', 'creative', 'preservation', 'conservation', 'collection']
     for keyword in generic:
         if keyword in headline_lower:
             return (True, None)

scripts/scan_dutch_data_quality.py

@@ -0,0 +1,445 @@
+#!/usr/bin/env python3
+"""
+Comprehensive data quality scan for Dutch custodian YAML files.
+Identifies issues like wrong GHCID types, missing web claims, Google Maps mismatches, etc.
+"""
+
+import os
+import re
+import yaml
+from pathlib import Path
+from collections import defaultdict
+from datetime import datetime
+
+CUSTODIAN_DIR = Path("/Users/kempersc/apps/glam/data/custodian")
+
+# Issue categories
+issues = defaultdict(list)
+
+def extract_ghcid_type(filename):
+    """Extract type code from GHCID filename (e.g., NL-ZH-ZOE-A-SAZS -> A)"""
+    match = re.match(r'NL-[A-Z]{2}-[A-Z]{3}-([A-Z])-', filename)
+    return match.group(1) if match else None
+
+def get_expected_type(data):
+    """Determine expected type from original_entry or other fields"""
+    # Check original_entry.type
+    if 'original_entry' in data:
+        oe = data['original_entry']
+        if 'type' in oe and oe['type']:
+            types = oe['type']
+            if isinstance(types, list) and len(types) > 0:
+                return types[0]
+        if 'type_organisatie' in oe:
+            type_org = oe['type_organisatie']
+            if type_org:
+                type_map = {
+                    'archive': 'A', 'archief': 'A',
+                    'library': 'L', 'bibliotheek': 'L',
+                    'museum': 'M',
+                    'gallery': 'G', 'galerie': 'G',
+                }
+                return type_map.get(type_org.lower(), None)
+    return None
+
+def check_google_maps_mismatch(data, filename):
+    """Check if Google Maps name doesn't match organization name"""
+    if 'google_maps_enrichment' not in data:
+        return None
+    
+    gm = data['google_maps_enrichment']
+    gm_name = gm.get('name', '')
+    
+    # Get original org name
+    org_name = ''
+    if 'original_entry' in data:
+        org_name = data['original_entry'].get('organisatie', '')
+    if 'custodian_name' in data:
+        cn = data['custodian_name']
+        if isinstance(cn, dict):
+            org_name = cn.get('claim_value', org_name)
+    
+    if not gm_name or not org_name:
+        return None
+    
+    # Simple similarity check - if names share less than 30% of words, flag it
+    gm_words = set(gm_name.lower().split())
+    org_words = set(org_name.lower().split())
+    
+    # Remove common words
+    stopwords = {'de', 'het', 'van', 'en', 'in', 'te', 'der', 'voor', 'stichting', 'vereniging'}
+    gm_words = gm_words - stopwords
+    org_words = org_words - stopwords
+    
+    if len(gm_words) == 0 or len(org_words) == 0:
+        return None
+    
+    overlap = len(gm_words & org_words)
+    similarity = overlap / max(len(gm_words), len(org_words))
+    
+    if similarity < 0.3:
+        return {
+            'google_name': gm_name,
+            'org_name': org_name,
+            'similarity': round(similarity, 2)
+        }
+    return None
+
+def check_absolute_paths(data, filename):
+    """Check for absolute paths that should be relative"""
+    yaml_str = yaml.dump(data, default_flow_style=False)
+    abs_paths = []
+    
+    patterns = [
+        r'/Volumes/KINGSTON/',
+        r'/Users/kempersc/',
+        r'/mnt/',
+        r'C:\\',
+        r'D:\\'
+    ]
+    
+    for pattern in patterns:
+        if re.search(pattern, yaml_str):
+            abs_paths.append(pattern.rstrip('/\\'))
+    
+    return abs_paths if abs_paths else None
+
+def check_web_claims(data, filename):
+    """Check web claims quality"""
+    issues_found = []
+    
+    if 'web_claims' not in data:
+        return ['no_web_claims']
+    
+    wc = data['web_claims']
+    
+    # Check if claims exist
+    claims = wc.get('claims', [])
+    if not claims:
+        issues_found.append('empty_claims')
+    
+    # Check for verified_claims
+    if 'verified_claims' not in wc:
+        issues_found.append('no_verified_claims')
+    else:
+        vc = wc['verified_claims']
+        if isinstance(vc, dict):
+            vc_claims = vc.get('claims', [])
+            # Check for XPath provenance
+            claims_without_xpath = 0
+            for claim in vc_claims:
+                if isinstance(claim, dict) and 'xpath' not in claim:
+                    claims_without_xpath += 1
+            if claims_without_xpath > 0:
+                issues_found.append(f'claims_missing_xpath:{claims_without_xpath}')
+    
+    return issues_found if issues_found else None
+
+def check_coordinates(data, filename):
+    """Check for coordinate issues"""
+    issues_found = []
+    
+    # Check if location exists
+    if 'location' not in data:
+        issues_found.append('no_location')
+        return issues_found
+    
+    loc = data['location']
+    lat = loc.get('latitude')
+    lon = loc.get('longitude')
+    
+    if lat is None or lon is None:
+        issues_found.append('missing_coordinates')
+    elif not (50.5 < lat < 53.7 and 3.3 < lon < 7.3):
+        # Rough Netherlands bounding box
+        issues_found.append('coordinates_outside_netherlands')
+    
+    # Check if coordinates from Google Maps differ significantly from corrected
+    if 'coordinate_provenance' in loc:
+        prov = loc['coordinate_provenance']
+        if 'previous_coordinates' in prov:
+            issues_found.append('has_coordinate_correction')
+    
+    return issues_found if issues_found else None
+
+def check_digital_platforms(data, filename):
+    """Check for missing digital platforms"""
+    if 'digital_platforms' not in data or not data['digital_platforms']:
+        return ['no_digital_platforms']
+    
+    platforms = data['digital_platforms']
+    if len(platforms) == 0:
+        return ['empty_digital_platforms']
+    
+    return None
+
+def check_identifiers(data, filename):
+    """Check identifier completeness"""
+    issues_found = []
+    
+    if 'identifiers' not in data:
+        issues_found.append('no_identifiers')
+        return issues_found
+    
+    ids = data['identifiers']
+    id_types = [i.get('identifier_scheme') for i in ids if isinstance(i, dict)]
+    
+    if 'ISIL' not in id_types:
+        issues_found.append('no_isil')
+    if 'GHCID' not in id_types:
+        issues_found.append('no_ghcid')
+    
+    return issues_found if issues_found else None
+
+def check_wikidata(data, filename):
+    """Check Wikidata enrichment status"""
+    if 'wikidata_enrichment' not in data:
+        return 'no_wikidata_enrichment'
+    
+    wd = data['wikidata_enrichment']
+    status = wd.get('status', '')
+    
+    if status == 'NOT_FOUND':
+        return 'wikidata_not_found'
+    elif status in ['SUCCESS', 'ENRICHED']:
+        return None
+    else:
+        return f'wikidata_status:{status}'
+
+def check_url(data, filename):
+    """Check URL issues"""
+    issues_found = []
+    
+    url = data.get('url', '')
+    if not url:
+        issues_found.append('no_url')
+    elif url.startswith('http://'):
+        issues_found.append('http_not_https')
+    
+    # Check if URL was corrected (indicates previous wrong URL)
+    if 'url_correction' in data:
+        issues_found.append('has_url_correction')
+    
+    return issues_found if issues_found else None
+
+def scan_file(filepath):
+    """Scan a single file for all issue types"""
+    filename = filepath.name
+    file_issues = {}
+    
+    try:
+        with open(filepath, 'r', encoding='utf-8') as f:
+            data = yaml.safe_load(f)
+    except Exception as e:
+        return {'parse_error': str(e)}
+    
+    if not data:
+        return {'empty_file': True}
+    
+    # 1. Check GHCID type mismatch
+    ghcid_type = extract_ghcid_type(filename)
+    expected_type = get_expected_type(data)
+    
+    if ghcid_type and expected_type and ghcid_type != expected_type:
+        if ghcid_type == 'U' and expected_type != 'U':
+            file_issues['wrong_ghcid_type'] = {
+                'current': ghcid_type,
+                'expected': expected_type
+            }
+    
+    # Also check for U type that should be something else
+    if ghcid_type == 'U':
+        file_issues['unknown_type'] = True
+    
+    # 2. Check Google Maps mismatch
+    gm_mismatch = check_google_maps_mismatch(data, filename)
+    if gm_mismatch:
+        file_issues['google_maps_mismatch'] = gm_mismatch
+    
+    # 3. Check absolute paths
+    abs_paths = check_absolute_paths(data, filename)
+    if abs_paths:
+        file_issues['absolute_paths'] = abs_paths
+    
+    # 4. Check web claims
+    wc_issues = check_web_claims(data, filename)
+    if wc_issues:
+        file_issues['web_claims_issues'] = wc_issues
+    
+    # 5. Check coordinates
+    coord_issues = check_coordinates(data, filename)
+    if coord_issues:
+        file_issues['coordinate_issues'] = coord_issues
+    
+    # 6. Check digital platforms
+    dp_issues = check_digital_platforms(data, filename)
+    if dp_issues:
+        file_issues['digital_platform_issues'] = dp_issues
+    
+    # 7. Check identifiers
+    id_issues = check_identifiers(data, filename)
+    if id_issues:
+        file_issues['identifier_issues'] = id_issues
+    
+    # 8. Check Wikidata
+    wd_issue = check_wikidata(data, filename)
+    if wd_issue:
+        file_issues['wikidata_issue'] = wd_issue
+    
+    # 9. Check URL
+    url_issues = check_url(data, filename)
+    if url_issues:
+        file_issues['url_issues'] = url_issues
+    
+    return file_issues
+
+def main():
+    print(f"Scanning Dutch custodian files in {CUSTODIAN_DIR}")
+    print(f"Scan started: {datetime.now().isoformat()}")
+    print("=" * 80)
+    
+    # Collect all issues
+    all_issues = {}
+    issue_counts = defaultdict(int)
+    
+    files = sorted(CUSTODIAN_DIR.glob("NL-*.yaml"))
+    total_files = len(files)
+    
+    print(f"Found {total_files} Dutch custodian files\n")
+    
+    for i, filepath in enumerate(files):
+        if (i + 1) % 200 == 0:
+            print(f"Progress: {i+1}/{total_files} files scanned...", flush=True)
+        
+        file_issues = scan_file(filepath)
+        
+        if file_issues:
+            all_issues[filepath.name] = file_issues
+            for issue_type in file_issues.keys():
+                issue_counts[issue_type] += 1
+    
+    print(f"\nScan complete: {total_files} files analyzed")
+    print("=" * 80)
+    
+    # Summary report
+    print("\n" + "=" * 80)
+    print("SUMMARY REPORT: Data Quality Issues")
+    print("=" * 80)
+    
+    print(f"\nTotal files scanned: {total_files}")
+    print(f"Files with issues: {len(all_issues)}")
+    print(f"Files without issues: {total_files - len(all_issues)}")
+    
+    print("\n" + "-" * 80)
+    print("ISSUE BREAKDOWN BY TYPE")
+    print("-" * 80)
+    
+    # Sort issues by count
+    sorted_issues = sorted(issue_counts.items(), key=lambda x: -x[1])
+    
+    for issue_type, count in sorted_issues:
+        pct = (count / total_files) * 100
+        print(f"{issue_type:40} {count:5} files ({pct:5.1f}%)")
+    
+    # Detailed breakdown for critical issues
+    print("\n" + "=" * 80)
+    print("CRITICAL ISSUES - REQUIRE IMMEDIATE ATTENTION")
+    print("=" * 80)
+    
+    # 1. Wrong GHCID type
+    wrong_type_files = [(f, d) for f, d in all_issues.items() if 'wrong_ghcid_type' in d]
+    print(f"\n1. WRONG GHCID TYPE ({len(wrong_type_files)} files)")
+    print("-" * 40)
+    if wrong_type_files:
+        for filename, data in wrong_type_files[:20]:
+            info = data['wrong_ghcid_type']
+            print(f"  {filename}: {info['current']} -> should be {info['expected']}")
+        if len(wrong_type_files) > 20:
+            print(f"  ... and {len(wrong_type_files) - 20} more")
+    else:
+        print("  None found")
+    
+    # 2. Google Maps mismatches
+    gm_mismatch_files = [(f, d) for f, d in all_issues.items() if 'google_maps_mismatch' in d]
+    print(f"\n2. GOOGLE MAPS MISMATCHES ({len(gm_mismatch_files)} files)")
+    print("-" * 40)
+    if gm_mismatch_files:
+        for filename, data in gm_mismatch_files[:20]:
+            info = data['google_maps_mismatch']
+            print(f"  {filename}")
+            print(f"    Google: {info['google_name']}")
+            print(f"    Org:    {info['org_name']}")
+            print(f"    Similarity: {info['similarity']}")
+        if len(gm_mismatch_files) > 20:
+            print(f"  ... and {len(gm_mismatch_files) - 20} more")
+    else:
+        print("  None found")
+    
+    # 3. Absolute paths
+    abs_path_files = [(f, d) for f, d in all_issues.items() if 'absolute_paths' in d]
+    print(f"\n3. ABSOLUTE PATHS ({len(abs_path_files)} files)")
+    print("-" * 40)
+    if abs_path_files:
+        for filename, data in abs_path_files[:10]:
+            print(f"  {filename}: {data['absolute_paths']}")
+        if len(abs_path_files) > 10:
+            print(f"  ... and {len(abs_path_files) - 10} more")
+    else:
+        print("  None found")
+    
+    # 4. Unknown type (U)
+    unknown_type_files = [f for f, d in all_issues.items() if 'unknown_type' in d]
+    print(f"\n4. UNKNOWN TYPE CODE 'U' ({len(unknown_type_files)} files)")
+    print("-" * 40)
+    if unknown_type_files:
+        for filename in unknown_type_files[:30]:
+            print(f"  {filename}")
+        if len(unknown_type_files) > 30:
+            print(f"  ... and {len(unknown_type_files) - 30} more")
+    else:
+        print("  None found")
+    
+    print("\n" + "=" * 80)
+    print("ENRICHMENT GAPS")
+    print("=" * 80)
+    
+    # Web claims issues
+    no_verified_claims = [f for f, d in all_issues.items() 
+                          if 'web_claims_issues' in d and 'no_verified_claims' in d['web_claims_issues']]
+    print(f"\n5. NO VERIFIED WEB CLAIMS ({len(no_verified_claims)} files)")
+    
+    # Digital platforms
+    no_platforms = [f for f, d in all_issues.items() 
+                    if 'digital_platform_issues' in d]
+    print(f"6. NO DIGITAL PLATFORMS ({len(no_platforms)} files)")
+    
+    # Wikidata
+    no_wikidata = [f for f, d in all_issues.items() 
+                   if d.get('wikidata_issue') in ['no_wikidata_enrichment', 'wikidata_not_found']]
+    print(f"7. NO WIKIDATA ENRICHMENT ({len(no_wikidata)} files)")
+    
+    # URLs
+    no_url = [f for f, d in all_issues.items() 
+              if 'url_issues' in d and 'no_url' in d['url_issues']]
+    print(f"8. NO URL ({len(no_url)} files)")
+    
+    # Save detailed report
+    report_file = CUSTODIAN_DIR.parent / 'reports' / 'dutch_data_quality_scan.yaml'
+    report_file.parent.mkdir(exist_ok=True)
+    
+    report = {
+        'scan_timestamp': datetime.now().isoformat(),
+        'total_files': total_files,
+        'files_with_issues': len(all_issues),
+        'issue_counts': dict(sorted_issues),
+        'detailed_issues': all_issues
+    }
+    
+    with open(report_file, 'w', encoding='utf-8') as f:
+        yaml.dump(report, f, default_flow_style=False, allow_unicode=True)
+    
+    print(f"\n\nDetailed report saved to: {report_file}")
+    print(f"Scan completed: {datetime.now().isoformat()}")
+
+if __name__ == '__main__':
+    main()

scripts/scan_dutch_fast.py

@@ -0,0 +1,199 @@
+#!/usr/bin/env python3
+"""Fast data quality scan - optimized for speed."""
+
+import os
+import re
+import yaml
+from pathlib import Path
+from collections import defaultdict
+from datetime import datetime
+
+# Use C loader for speed
+try:
+    from yaml import CSafeLoader as SafeLoader
+except ImportError:
+    from yaml import SafeLoader
+
+CUSTODIAN_DIR = Path("/Users/kempersc/apps/glam/data/custodian")
+
+def extract_ghcid_type(filename):
+    match = re.match(r'NL-[A-Z]{2}-[A-Z]{3}-([A-Z])-', filename)
+    return match.group(1) if match else None
+
+def scan_file_fast(filepath):
+    """Fast scan using string operations where possible."""
+    filename = filepath.name
+    issues = []
+    
+    try:
+        with open(filepath, 'r', encoding='utf-8') as f:
+            content = f.read()
+    except Exception as e:
+        return ['parse_error']
+    
+    # Quick string-based checks first
+    
+    # Absolute paths
+    if '/Volumes/KINGSTON/' in content or '/Users/kempersc/' in content:
+        issues.append('absolute_paths')
+    
+    # No URL
+    if '\nurl:' not in content and 'url: ' not in content[:500]:
+        issues.append('no_url')
+    
+    # HTTP instead of HTTPS
+    if 'url: http://' in content:
+        issues.append('http_not_https')
+    
+    # No digital_platforms
+    if 'digital_platforms:' not in content:
+        issues.append('no_digital_platforms')
+    elif 'digital_platforms: []\n' in content or 'digital_platforms:\n-' not in content:
+        issues.append('empty_digital_platforms')
+    
+    # No verified_claims
+    if 'verified_claims:' not in content:
+        issues.append('no_verified_claims')
+    
+    # Wikidata NOT_FOUND
+    if "status: NOT_FOUND" in content:
+        issues.append('wikidata_not_found')
+    elif 'wikidata_enrichment:' not in content:
+        issues.append('no_wikidata_enrichment')
+    
+    # Unknown type in filename
+    ghcid_type = extract_ghcid_type(filename)
+    if ghcid_type == 'U':
+        issues.append('unknown_type_U')
+    
+    # Parse YAML only for complex checks
+    try:
+        data = yaml.load(content, Loader=SafeLoader)
+    except:
+        issues.append('yaml_parse_error')
+        return issues
+    
+    if not data:
+        issues.append('empty_file')
+        return issues
+    
+    # Check GHCID type mismatch
+    if 'original_entry' in data:
+        oe = data['original_entry']
+        expected = None
+        if 'type' in oe and oe['type'] and isinstance(oe['type'], list):
+            expected = oe['type'][0]
+        elif 'type_organisatie' in oe and oe['type_organisatie']:
+            type_map = {'archive': 'A', 'archief': 'A', 'library': 'L', 
+                       'bibliotheek': 'L', 'museum': 'M', 'gallery': 'G'}
+            expected = type_map.get(oe['type_organisatie'].lower())
+        
+        if expected and ghcid_type and ghcid_type != expected:
+            issues.append(f'wrong_type:{ghcid_type}→{expected}')
+    
+    # Check Google Maps mismatch
+    if 'google_maps_enrichment' in data and 'original_entry' in data:
+        gm_name = data['google_maps_enrichment'].get('name', '').lower()
+        org_name = data['original_entry'].get('organisatie', '').lower()
+        
+        if gm_name and org_name:
+            gm_words = set(gm_name.split()) - {'de', 'het', 'van', 'en', 'stichting'}
+            org_words = set(org_name.split()) - {'de', 'het', 'van', 'en', 'stichting'}
+            
+            if gm_words and org_words:
+                overlap = len(gm_words & org_words)
+                similarity = overlap / max(len(gm_words), len(org_words))
+                if similarity < 0.25:
+                    issues.append('google_maps_mismatch')
+    
+    # Check coordinates
+    if 'location' in data:
+        loc = data['location']
+        lat = loc.get('latitude')
+        lon = loc.get('longitude')
+        if lat is None or lon is None:
+            issues.append('missing_coordinates')
+        elif not (50.5 < lat < 53.7 and 3.3 < lon < 7.3):
+            issues.append('coords_outside_NL')
+    else:
+        issues.append('no_location')
+    
+    return issues
+
+def main():
+    print(f"Fast scan started: {datetime.now().isoformat()}")
+    
+    files = sorted(CUSTODIAN_DIR.glob("NL-*.yaml"))
+    total = len(files)
+    
+    print(f"Scanning {total} Dutch custodian files...")
+    
+    issue_counts = defaultdict(int)
+    files_with_issues = defaultdict(list)
+    
+    for i, fp in enumerate(files):
+        issues = scan_file_fast(fp)
+        for issue in issues:
+            issue_counts[issue] += 1
+            files_with_issues[issue].append(fp.name)
+    
+    print(f"\nScan complete: {datetime.now().isoformat()}")
+    print("\n" + "=" * 80)
+    print("DATA QUALITY SUMMARY REPORT")
+    print("=" * 80)
+    print(f"\nTotal files: {total}")
+    
+    # Count files with any issue
+    all_issue_files = set()
+    for files_list in files_with_issues.values():
+        all_issue_files.update(files_list)
+    
+    print(f"Files with issues: {len(all_issue_files)} ({100*len(all_issue_files)/total:.1f}%)")
+    print(f"Clean files: {total - len(all_issue_files)}")
+    
+    print("\n" + "-" * 80)
+    print("ISSUE BREAKDOWN")
+    print("-" * 80)
+    
+    # Sort by count
+    for issue, count in sorted(issue_counts.items(), key=lambda x: -x[1]):
+        pct = 100 * count / total
+        bar = "█" * int(pct / 2)
+        print(f"{issue:35} {count:5} ({pct:5.1f}%) {bar}")
+    
+    # Critical issues detail
+    print("\n" + "=" * 80)
+    print("CRITICAL ISSUES (require manual fix)")
+    print("=" * 80)
+    
+    critical_issues = ['wrong_type:', 'google_maps_mismatch', 'absolute_paths', 'unknown_type_U']
+    
+    for critical in critical_issues:
+        matching = [(k, v) for k, v in files_with_issues.items() if critical in k or k == critical]
+        if matching:
+            for issue_key, file_list in matching:
+                print(f"\n{issue_key} ({len(file_list)} files):")
+                for f in file_list[:15]:
+                    print(f"  - {f}")
+                if len(file_list) > 15:
+                    print(f"  ... and {len(file_list) - 15} more")
+    
+    # Save report
+    report_path = CUSTODIAN_DIR.parent / 'reports' / 'dutch_data_quality_fast.yaml'
+    report_path.parent.mkdir(exist_ok=True)
+    
+    report = {
+        'scan_timestamp': datetime.now().isoformat(),
+        'total_files': total,
+        'files_with_issues': len(all_issue_files),
+        'issue_counts': dict(sorted(issue_counts.items(), key=lambda x: -x[1])),
+        'files_by_issue': {k: v for k, v in files_with_issues.items()}
+    }
+    
+    with open(report_path, 'w') as f:
+        yaml.dump(report, f, default_flow_style=False, allow_unicode=True)
+    
+    print(f"\n\nFull report saved: {report_path}")
+
+if __name__ == '__main__':
+    main()

scripts/transform_crawl4ai_to_digital_platform.py

@@ -0,0 +1,575 @@
+#!/usr/bin/env python3
+"""
+Transform crawl4ai_enrichment data into proper digital_platform YAML structure.
+
+This script processes custodian YAML files that have crawl4ai_enrichment data
+and creates/updates the digital_platform block conforming to the LinkML schema.
+
+Schema Reference:
+- DigitalPlatform: schemas/20251121/linkml/modules/classes/DigitalPlatform.yaml
+- AuxiliaryDigitalPlatform: schemas/20251121/linkml/modules/classes/AuxiliaryDigitalPlatform.yaml
+- DigitalPlatformTypeEnum: schemas/20251121/linkml/modules/enums/DigitalPlatformTypeEnum.yaml
+
+Usage:
+    python scripts/transform_crawl4ai_to_digital_platform.py [--dry-run] [--file FILE]
+"""
+
+import argparse
+import logging
+import re
+import sys
+from collections import defaultdict
+from datetime import datetime, timezone
+from pathlib import Path
+from typing import Any
+from urllib.parse import unquote, urlparse
+
+import yaml
+
+# Configure logging
+logging.basicConfig(
+    level=logging.INFO,
+    format='%(asctime)s - %(levelname)s - %(message)s',
+    handlers=[
+        logging.StreamHandler(sys.stdout),
+        logging.FileHandler(f'logs/transform_digital_platform_{datetime.now().strftime("%Y%m%d_%H%M%S")}.log')
+    ]
+)
+logger = logging.getLogger(__name__)
+
+
+# Mapping from crawl4ai detected_catalog_urls type to DigitalPlatformTypeEnum
+# and to the appropriate slot (collection_web_addresses or inventory_web_addresses)
+CATALOG_TYPE_MAPPING = {
+    # Image collections → collection_web_addresses
+    'beeldbank': {
+        'platform_types': ['PHOTOGRAPH_COLLECTION'],
+        'slot': 'collection_web_addresses',
+        'description': 'Image/photograph collection'
+    },
+    # Genealogy → collection_web_addresses (specialized database)
+    'genealogie': {
+        'platform_types': ['GENEALOGY_DATABASE'],
+        'slot': 'collection_web_addresses',
+        'description': 'Genealogy records database'
+    },
+    # Archives/inventories → inventory_web_addresses
+    'archieven': {
+        'platform_types': ['ARCHIVES_PORTAL'],
+        'slot': 'inventory_web_addresses',
+        'description': 'Archival finding aids and inventories'
+    },
+    'inventaris': {
+        'platform_types': ['ARCHIVES_PORTAL'],
+        'slot': 'inventory_web_addresses',
+        'description': 'Archival inventory'
+    },
+    # Collections → collection_web_addresses
+    'collectie': {
+        'platform_types': ['ONLINE_DATABASE'],
+        'slot': 'collection_web_addresses',
+        'description': 'General collection access'
+    },
+    # Library → collection_web_addresses
+    'bibliotheek': {
+        'platform_types': ['DIGITAL_LIBRARY'],
+        'slot': 'collection_web_addresses',
+        'description': 'Library catalog'
+    },
+    # Search interfaces → collection_web_addresses
+    'zoeken': {
+        'platform_types': ['ONLINE_DATABASE'],
+        'slot': 'collection_web_addresses',
+        'description': 'Search interface'
+    },
+    # Kranten (newspapers) → collection_web_addresses
+    'kranten': {
+        'platform_types': ['ONLINE_NEWS_ARCHIVE'],
+        'slot': 'collection_web_addresses',
+        'description': 'Historical newspapers'
+    },
+}
+
+# Mapping for external archive platforms to AuxiliaryDigitalPlatformTypeEnum
+EXTERNAL_PLATFORM_MAPPING = {
+    'archieven.nl': {
+        'platform_name': 'Archieven.nl',
+        'auxiliary_platform_type': 'AGGREGATOR',
+        'description': 'National Dutch archives aggregator'
+    },
+    'archiefweb.eu': {
+        'platform_name': 'Archiefweb.eu',
+        'auxiliary_platform_type': 'ARCHIVAL_REPOSITORY',
+        'description': 'Web archiving service'
+    },
+    'memorix.nl': {
+        'platform_name': 'Memorix',
+        'auxiliary_platform_type': 'DIGITAL_ARCHIVE',
+        'description': 'Heritage information management platform'
+    },
+    'opendata.archieven.nl': {
+        'platform_name': 'Open Data Archieven.nl',
+        'auxiliary_platform_type': 'OPEN_DATA_PORTAL',
+        'description': 'Open data from Dutch archives'
+    },
+    'regionaalarchief': {
+        'platform_name': 'Regionaal Archief',
+        'auxiliary_platform_type': 'ARCHIVES_PORTAL',
+        'description': 'Regional archive portal'
+    },
+    'delpher.nl': {
+        'platform_name': 'Delpher',
+        'auxiliary_platform_type': 'DIGITAL_LIBRARY',
+        'description': 'KB digitized newspapers, books, and periodicals'
+    },
+    'wiewaswie.nl': {
+        'platform_name': 'WieWasWie',
+        'auxiliary_platform_type': 'GENEALOGY_DATABASE',
+        'description': 'Dutch genealogy database'
+    },
+}
+
+
+def normalize_url(url: str) -> str:
+    """Normalize URL by decoding and extracting base path."""
+    if not url:
+        return url
+    
+    # URL decode
+    decoded = unquote(url)
+    
+    # Parse URL
+    parsed = urlparse(decoded)
+    
+    # Reconstruct without query parameters for deduplication key
+    base_url = f"{parsed.scheme}://{parsed.netloc}{parsed.path}"
+    
+    # Remove trailing slash for consistency (except root)
+    if base_url.endswith('/') and len(parsed.path) > 1:
+        base_url = base_url[:-1]
+    
+    return base_url
+
+
+def extract_base_path_key(url: str) -> str:
+    """Extract base path for deduplication (without query params)."""
+    parsed = urlparse(url)
+    return f"{parsed.netloc}{parsed.path}".rstrip('/')
+
+
+def deduplicate_catalog_urls(catalog_urls: list[dict]) -> list[dict]:
+    """
+    Deduplicate catalog URLs, preferring entries with XPath provenance.
+    
+    Strategy:
+    1. Group URLs by base path (without query params)
+    2. For each group, prefer entries with xpath provenance
+    3. Return one representative URL per type per base path
+    """
+    if not catalog_urls:
+        return []
+    
+    # Group by (base_path, type)
+    grouped: dict[tuple[str, str], list[dict]] = defaultdict(list)
+    
+    for entry in catalog_urls:
+        url = entry.get('url', '')
+        url_type = entry.get('type', 'unknown')
+        base_key = extract_base_path_key(url)
+        grouped[(base_key, url_type)].append(entry)
+    
+    # Select best entry from each group
+    deduplicated = []
+    for (base_key, url_type), entries in grouped.items():
+        # Sort: entries with xpath first, then by URL length (shorter preferred)
+        sorted_entries = sorted(
+            entries,
+            key=lambda e: (0 if e.get('xpath') else 1, len(e.get('url', '')))
+        )
+        best = sorted_entries[0]
+        
+        # Normalize the URL
+        best_copy = best.copy()
+        best_copy['url'] = normalize_url(best['url'])
+        deduplicated.append(best_copy)
+    
+    return deduplicated
+
+
+def generate_platform_id(ghcid: str) -> str:
+    """Generate platform_id URI from GHCID."""
+    ghcid_lower = ghcid.lower().replace('_', '-')
+    return f"https://nde.nl/ontology/hc/platform/{ghcid_lower}-website"
+
+
+def extract_ghcid_from_file(file_path: Path) -> str | None:
+    """Extract GHCID from filename."""
+    stem = file_path.stem
+    # GHCID pattern: CC-RR-CCC-T-ABBREV (e.g., NL-DR-ASS-A-DA)
+    if re.match(r'^[A-Z]{2}-[A-Z]{2,3}-[A-Z]{3}-[A-Z]-', stem):
+        return stem
+    return None
+
+
+def determine_platform_types(catalog_urls: list[dict]) -> list[str]:
+    """
+    Determine platform types from detected catalog URLs.
+    
+    Returns list of DigitalPlatformTypeEnum values.
+    """
+    types_set = set()
+    
+    for entry in catalog_urls:
+        url_type = entry.get('type', '')
+        mapping = CATALOG_TYPE_MAPPING.get(url_type, {})
+        for pt in mapping.get('platform_types', []):
+            types_set.add(pt)
+    
+    # If we have catalog URLs but no specific types, add generic ONLINE_DATABASE
+    if catalog_urls and not types_set:
+        types_set.add('ONLINE_DATABASE')
+    
+    # Always include INSTITUTIONAL_WEBSITE as base type
+    types_set.add('INSTITUTIONAL_WEBSITE')
+    
+    return sorted(list(types_set))
+
+
+def categorize_urls_by_slot(catalog_urls: list[dict]) -> dict[str, list[str]]:
+    """
+    Categorize URLs by target slot (collection_web_addresses vs inventory_web_addresses).
+    """
+    slots = {
+        'collection_web_addresses': [],
+        'inventory_web_addresses': []
+    }
+    
+    seen_urls = set()
+    
+    for entry in catalog_urls:
+        url = entry.get('url', '')
+        if not url or url in seen_urls:
+            continue
+        
+        url_type = entry.get('type', '')
+        mapping = CATALOG_TYPE_MAPPING.get(url_type, {})
+        slot = mapping.get('slot', 'collection_web_addresses')
+        
+        slots[slot].append(url)
+        seen_urls.add(url)
+    
+    return slots
+
+
+def transform_external_platforms(external_platforms: list[dict]) -> list[dict]:
+    """
+    Transform external_archive_platforms to auxiliary_platforms structure.
+    """
+    if not external_platforms:
+        return []
+    
+    auxiliary = []
+    seen_platforms = set()
+    
+    for entry in external_platforms:
+        url = entry.get('url', '')
+        platform_key = entry.get('platform', '')
+        
+        if not url or platform_key in seen_platforms:
+            continue
+        
+        # Find mapping
+        mapping = None
+        for key, config in EXTERNAL_PLATFORM_MAPPING.items():
+            if key in platform_key or key in url:
+                mapping = config
+                break
+        
+        if not mapping:
+            # Generic external platform
+            mapping = {
+                'platform_name': platform_key.replace('.', ' ').title() if platform_key else 'External Platform',
+                'auxiliary_platform_type': 'WEB_PORTAL',
+                'description': 'External heritage platform'
+            }
+        
+        aux_platform = {
+            'platform_name': mapping['platform_name'],
+            'platform_url': url,
+            'auxiliary_platform_type': mapping['auxiliary_platform_type'],
+            'platform_purpose': mapping.get('description', '')
+        }
+        
+        auxiliary.append(aux_platform)
+        seen_platforms.add(platform_key)
+    
+    return auxiliary
+
+
+def get_platform_name(data: dict, ghcid: str) -> str:
+    """
+    Determine the best platform name from available data.
+    
+    Priority:
+    1. custodian_name.emic_name or custodian_name.name
+    2. crawl4ai_enrichment.title (cleaned)
+    3. GHCID-based fallback
+    """
+    # Try custodian_name first
+    custodian_name = data.get('custodian_name', {})
+    if isinstance(custodian_name, dict):
+        name = custodian_name.get('emic_name') or custodian_name.get('name')
+        if name:
+            return f"{name} Website"
+    
+    # Try top-level name
+    if data.get('name'):
+        return f"{data['name']} Website"
+    
+    # Try crawl4ai title
+    crawl4ai = data.get('crawl4ai_enrichment', {})
+    title = crawl4ai.get('title', '')
+    if title:
+        # Clean up title (remove common suffixes)
+        cleaned = re.sub(r'\s*[-–|]\s*.+$', '', title).strip()
+        if cleaned and len(cleaned) > 3:
+            return f"{cleaned} Website"
+    
+    # Fallback to GHCID
+    return f"{ghcid} Website"
+
+
+def transform_crawl4ai_to_digital_platform(data: dict, ghcid: str) -> dict | None:
+    """
+    Transform crawl4ai_enrichment into digital_platform structure.
+    
+    Args:
+        data: Full custodian YAML data
+        ghcid: Global Heritage Custodian Identifier
+    
+    Returns:
+        digital_platform dict or None if no crawl4ai_enrichment
+    """
+    crawl4ai = data.get('crawl4ai_enrichment')
+    if not crawl4ai:
+        return None
+    
+    # Skip failed fetches - accept 2xx and 3xx status codes
+    status_code = crawl4ai.get('status_code')
+    if status_code is None or status_code >= 400:
+        logger.debug(f"Skipping {ghcid}: HTTP status {status_code}")
+        return None
+    
+    source_url = crawl4ai.get('source_url', '')
+    if not source_url:
+        return None
+    
+    # Get and deduplicate catalog URLs
+    catalog_urls = crawl4ai.get('detected_catalog_urls', [])
+    deduped_catalogs = deduplicate_catalog_urls(catalog_urls)
+    
+    # Determine platform types
+    platform_types = determine_platform_types(deduped_catalogs)
+    
+    # Categorize URLs by slot
+    url_slots = categorize_urls_by_slot(deduped_catalogs)
+    
+    # Transform external platforms
+    external_platforms = crawl4ai.get('external_archive_platforms', [])
+    auxiliary_platforms = transform_external_platforms(external_platforms)
+    
+    # Build digital_platform structure
+    digital_platform = {
+        'platform_id': generate_platform_id(ghcid),
+        'platform_name': get_platform_name(data, ghcid),
+        'homepage_web_address': source_url,
+        'refers_to_custodian': f"https://nde.nl/ontology/hc/{ghcid.lower()}"
+    }
+    
+    # Add platform types if we have more than just INSTITUTIONAL_WEBSITE
+    if platform_types and len(platform_types) > 1:
+        digital_platform['platform_type'] = platform_types
+    elif platform_types:
+        digital_platform['platform_type'] = platform_types
+    
+    # Add collection URLs
+    if url_slots['collection_web_addresses']:
+        digital_platform['collection_web_addresses'] = url_slots['collection_web_addresses']
+    
+    # Add inventory URLs
+    if url_slots['inventory_web_addresses']:
+        digital_platform['inventory_web_addresses'] = url_slots['inventory_web_addresses']
+    
+    # Add auxiliary platforms
+    if auxiliary_platforms:
+        digital_platform['auxiliary_platforms'] = auxiliary_platforms
+    
+    # Add transformation metadata
+    digital_platform['_transformation_metadata'] = {
+        'source': 'crawl4ai_enrichment',
+        'transformation_date': datetime.now(timezone.utc).isoformat(),
+        'catalog_urls_original': len(catalog_urls),
+        'catalog_urls_deduplicated': len(deduped_catalogs),
+        'external_platforms_count': len(external_platforms)
+    }
+    
+    return digital_platform
+
+
+def process_file(file_path: Path, dry_run: bool = False) -> dict:
+    """
+    Process a single custodian YAML file.
+    
+    Returns:
+        dict with processing statistics
+    """
+    stats = {
+        'file': str(file_path.name),
+        'status': 'skipped',
+        'has_crawl4ai': False,
+        'has_digital_platform': False,
+        'catalog_urls': 0,
+        'external_platforms': 0
+    }
+    
+    try:
+        # Read YAML file
+        with open(file_path, 'r', encoding='utf-8') as f:
+            data = yaml.safe_load(f)
+        
+        if not data:
+            stats['status'] = 'empty'
+            return stats
+        
+        # Extract GHCID
+        ghcid = extract_ghcid_from_file(file_path)
+        if not ghcid:
+            stats['status'] = 'no_ghcid'
+            return stats
+        
+        # Check for crawl4ai_enrichment
+        crawl4ai = data.get('crawl4ai_enrichment')
+        if not crawl4ai:
+            stats['status'] = 'no_crawl4ai'
+            return stats
+        
+        stats['has_crawl4ai'] = True
+        stats['catalog_urls'] = len(crawl4ai.get('detected_catalog_urls', []))
+        stats['external_platforms'] = len(crawl4ai.get('external_archive_platforms', []))
+        
+        # Check if digital_platform_v2 already exists (avoid overwriting)
+        if 'digital_platform_v2' in data:
+            stats['has_digital_platform'] = True
+            stats['status'] = 'already_transformed'
+            return stats
+        
+        # Transform to digital_platform
+        digital_platform = transform_crawl4ai_to_digital_platform(data, ghcid)
+        
+        if not digital_platform:
+            stats['status'] = 'transform_failed'
+            return stats
+        
+        # Add to data as digital_platform_v2 (to distinguish from any existing digital_platform)
+        data['digital_platform_v2'] = digital_platform
+        
+        if not dry_run:
+            # Write back to file
+            with open(file_path, 'w', encoding='utf-8') as f:
+                yaml.dump(data, f, allow_unicode=True, default_flow_style=False, sort_keys=False)
+            stats['status'] = 'transformed'
+        else:
+            stats['status'] = 'would_transform'
+            logger.info(f"[DRY-RUN] Would transform {file_path.name}")
+            logger.debug(f"  Platform types: {digital_platform.get('platform_type', [])}")
+            logger.debug(f"  Collection URLs: {len(digital_platform.get('collection_web_addresses', []))}")
+            logger.debug(f"  Inventory URLs: {len(digital_platform.get('inventory_web_addresses', []))}")
+            logger.debug(f"  Auxiliary platforms: {len(digital_platform.get('auxiliary_platforms', []))}")
+        
+        return stats
+        
+    except yaml.YAMLError as e:
+        logger.error(f"YAML error in {file_path.name}: {e}")
+        stats['status'] = 'yaml_error'
+        return stats
+    except Exception as e:
+        logger.error(f"Error processing {file_path.name}: {e}")
+        stats['status'] = 'error'
+        return stats
+
+
+def main():
+    parser = argparse.ArgumentParser(
+        description='Transform crawl4ai_enrichment to digital_platform structure'
+    )
+    parser.add_argument(
+        '--dry-run',
+        action='store_true',
+        help='Show what would be done without making changes'
+    )
+    parser.add_argument(
+        '--file',
+        type=Path,
+        help='Process a single file instead of all NL-*.yaml files'
+    )
+    parser.add_argument(
+        '--verbose', '-v',
+        action='store_true',
+        help='Enable verbose logging'
+    )
+    
+    args = parser.parse_args()
+    
+    if args.verbose:
+        logging.getLogger().setLevel(logging.DEBUG)
+    
+    # Ensure logs directory exists
+    Path('logs').mkdir(exist_ok=True)
+    
+    # Get files to process
+    data_dir = Path('data/custodian')
+    
+    if args.file:
+        if not args.file.exists():
+            logger.error(f"File not found: {args.file}")
+            sys.exit(1)
+        files = [args.file]
+    else:
+        files = sorted(data_dir.glob('NL-*.yaml'))
+    
+    logger.info(f"Processing {len(files)} files...")
+    if args.dry_run:
+        logger.info("DRY-RUN MODE - no files will be modified")
+    
+    # Process files
+    stats_summary = defaultdict(int)
+    total_catalog_urls = 0
+    total_external_platforms = 0
+    
+    for i, file_path in enumerate(files):
+        if (i + 1) % 100 == 0:
+            logger.info(f"Progress: {i + 1}/{len(files)} files processed")
+        
+        stats = process_file(file_path, dry_run=args.dry_run)
+        stats_summary[stats['status']] += 1
+        total_catalog_urls += stats.get('catalog_urls', 0)
+        total_external_platforms += stats.get('external_platforms', 0)
+    
+    # Print summary
+    logger.info("\n" + "=" * 60)
+    logger.info("TRANSFORMATION SUMMARY")
+    logger.info("=" * 60)
+    logger.info(f"Total files processed: {len(files)}")
+    
+    for status, count in sorted(stats_summary.items()):
+        logger.info(f"  {status}: {count}")
+    
+    logger.info(f"\nTotal catalog URLs found: {total_catalog_urls}")
+    logger.info(f"Total external platforms found: {total_external_platforms}")
+    
+    if args.dry_run:
+        logger.info("\n[DRY-RUN] No files were modified. Run without --dry-run to apply changes.")
+
+
+if __name__ == '__main__':
+    main()