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WasGeo: Advancing Spatial Intelligence Through SQL, SPARQL, and OWL Integration

Author

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  • Najla Sassi

    (MIS Department, School of Business, King Faisal University, Al Ahsa, Saudi Arabia)

  • Wassim Jaziri

    (MIS Department, School of Business, King Faisal University, Al Ahsa, Saudi Arabia)

Abstract

In this paper the authors propose Well-Architected Semantic GEOframework (WasGeo), a unified framework for addressing semantic heterogeneity and intrinsic complexity in geospatial data. Its architecture integrates relational databases and semantic technologies to support Structured Query Language for data handling, SPARQL Protocol and Resource Description Framework Query Language for semantic querying, and Web Ontology Language for ontology reasoning. The performance of the proposed framework was tested using predefined queries processed on LinkedGeoData datasets. Benchmark comparisons were made to evaluate WasGeo against Ontop and GeoSPARQL. The proposed framework achieved a reasoning accuracy of 95%, processed up to 1 million Resource Description Framework triples, and demonstrated execution times ranging from 0.3 to 7.7 seconds. Comparative benchmarks show that WasGeo provides greater reasoning depth than GeoSPARQL and Ontop, while maintaining better balance between scalability and analytical power. These results position WasGeo as a robust and practical framework for advanced semantic geospatial querying, although future enhancements are needed for scalability.

Suggested Citation

  • Najla Sassi & Wassim Jaziri, 2025. "WasGeo: Advancing Spatial Intelligence Through SQL, SPARQL, and OWL Integration," International Journal on Semantic Web and Information Systems (IJSWIS), IGI Global, vol. 21(1), pages 1-19, January.
    • Handle: RePEc:igg:jswis0:v:21:y:2025:i:1:p:1-19
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