Enhancing Supply Chain Resilience and Transparency Through Spatial Knowledge Graphs
summary
Constructs a spatial knowledge graph linking factory addresses (geocoded via Google Maps/OpenSupplyHub), materials and products, WWF risk-filter scores, German Federal Foreign Office warnings, Esri Living Atlas hazard events and NewsCatcher headlines, ingesting PDFs and polygon impact zones. Uses Neo4j for complex OpenCypher queries and ARJS Knowledge for map visualization, runs centrality and clustering to flag high‑impact nodes, and builds dashboards that reveal specific supplier–material vulnerabilities; social‑risk signals prove noisy and delivery‑route impacts remain unmodeled.
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chapters (7)
- 0:00Introduction and motivation
- 0:30Defining project goals
- 1:23Data sourcing and integration
- 4:24Data model development
- 5:30Technology and implementation
- 8:12Analysis and visualization
- 9:18Conclusion and future outlook
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