This project introduces the Discrete Local Irregular Grid (DLIG) — a novel ontology design pattern to represent and integrate geographic information semantically on the Web of Data. It focuses on overcoming heterogeneity in authoritative geographic ontologies by enhancing their interoperability, spatial reasoning, and semantic richness. Existing geographic datasets often lack semantic uniformity and structural consistency, which hinders effective reasoning and integration. The project seeks to address inconsistencies in administrative and topographic representations across mapping agencies and proposes a uniform model to support scalable, structured, and semantically enriched geospatial data.
Research Questions
- What are the limitations of current geospatial ontologies representing authoritative geographic datasets?
- How can a uniform geospatial ontology be developed for complete and scalable representation?
- Can this ontology support global geographic knowledge graph construction?
- How can the model address gaps in under-represented regions lacking RDF-based frameworks?
- What approach enables integration of volunteered geographic data with authoritative models?
Key Contributions
- Design of the DLIG ontology pattern for spatial hierarchy and semantic completeness
- Proposal of a spatial semantic completeness metric
- Integration framework for authoritative datasets using DLIG
- Case studies with global datasets including GADM and regional data (e.g., Saudi Arabia)
- Enrichment of volunteered geographic information using the DLIG model
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