An evaluation of ontology matching techniques on geospatial ontologies

Standardization is one of the pillars of interoperability. In this context, efforts promoted by the Open Geospatial Consortium, such as CityGML (Technical University, Berlin), a standard for exchanging three-dimensional models or urban city objects, are welcomed. However, information from other domains of interest (e.g. energy efficiency or building information modeling) is needed for tasks such as land planning, large-scale flooding analysis, or demand/supply energy simulations. CityGML allows extension in order to integrate information from other domains, but the development process is expensive because there is no way to perform it automatically. The discovery of correspondences between CityGML concepts and other domains concepts poses a significant challenge.

Ontology matching is the research field emerged from the Semantic Web to address automatic ontology integration. Using the ontology underlying CityGML and the ontologies which model other domains of interest, ontology matching would be able to find the correspondences that would permit the integration in a more automatic manner than it is done now.

In this paper, we evaluate if ontology matching techniques allow performing an automatic integration of geospatial information modeled from different viewpoints. In order to achieve this, an evaluation methodology was designed, and it was applied to the discovery of relationships between CityGML and ontologies coming from the building information modeling and Geospatial Semantic Web domains. The methodology and the results of the evaluation are presented. The best results have been achieved using string-based techniques, while matching systems give the worst precision and recall. Only in a few cases the values are over 50%, which shows the limitations when these techniques are applied to ontologies with a partial overlap.