Knowledge Graphs for Locations in the Humanitarian and Development Sector
summary
NRC restructures fragmented location master data into a knowledge graph using Neo4j + RDF mapping and API ingestion to unify records across 40 country operations, removing duplicates and adding provenance metadata for GDPR traceability. The implementation encodes hierarchies (locality→city→province), staff assignments, project funding and partner links, relies on unique identifiers plus ISO and M49 codes, supports dynamic cross-system queries, and omits polygon geometry for now; results show improved consistency and a working single source of truth.
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chapters (10)
- 0:00Introduction and welcome
- 0:44Challenges in location data
- 3:15Organizational data challenges
- 5:25Why knowledge graphs
- 6:51Approach and methodology
- 8:16Ontology design process
- 9:01Core classes and relationships
- 11:13Project and staff details
- 12:42Data properties and codes
- 13:03Neo4j implementation
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