Automatic expansion of spatial ontologies for geographic information retrieval

Abstract

One of the most prominent scenarios for capturing implicit knowledge from heterogeneous data sources concerns the geospatial data domain. In this scenario, ontologies play a key role for managing the totality of geospatial concepts, categories and relations at different resolutions. However, the manual development of geographic ontologies implies an exhausting work due to the rapid growth of the data available on the Internet. In order to address this challenge, the present work describes a semi-automatic approach to build and expand a geographic ontology by integrating the information provided by diverse spatial data sources. The generated ontology can be used as a knowledge resource in a Geographic Information Retrieval system. As a main novelty, the use of OWL 2 as an ontology language allowed us to model and infer new spatial relationships, regarding the use of other less expressive languages such as RDF or OWL 1. Two different spatial ontologies were generated for two specific geographic regions by applying the proposed approach, and the evaluation results showed their suitability to be used as geographic-knowledge resources in Geographic Information Retrieval contexts.