Unified Management of Place Information on the Web of Data

Abstract

This study addresses the challenges of representing and integrating geographic infor- mation in a semantically enriched and interoperable manner within the semantic web. Existing authoritative geographic ontologies often suffer from heterogeneity, limiting their ability to support spatial reasoning and seamless integration across diverse datasets. To overcome these limitations, this study introduces the Discrete Local Irregular Grid (DLIG), a novel ontology design pattern that encodes hierarchical geographic structures and enhances spatial reasoning capabilities. Reviewing existing geographic ontologies identifies gaps in representing and integrating authoritative data on the web. The study develops the DLIGS ontology design pattern for encoding hierarchical geographic struc- tures and standardising spatial relationships. Integrating the Global Administrative Areas Map (GADM) as a hierarchy within DLIG demonstrates a method for representing admin- istrative hierarchies in regions lacking structured RDF-based frameworks. This process provides a foundation for creating global-scale knowledge graphs with consistent spatial semantics. Further, the research explores the integration of Volunteered Geographic Infor- mation (VGI) with Authoritative Geographic Information (AGI). A method is presented for aligning user-generated data with authoritative models, enriching VGI with spatial semantics and hierarchical definitions. The outcomes of this study illustrate the effective- ness of DLIGS in representing geo knowledge graphs, addressing data heterogeneity, and ensuring semantic consistency across diverse datasets. The research demonstrates significant contributions to geographic knowledge graph construction, providing a methodology for integrating, enriching, and querying geospatial data on a global scale.