Semantic similarity assessment in support of spatial data integration

Mir Abolfazl Mostafavi
Department of geomatics, 
Laval University, Quebec city, Canada
Tel: +001 418 656 2131 2750, Fax: +001 418 656 7411

New advances in spatial information technology have made available large amount of spatial data from different sources with different quality levels. Today, the important challenge for the scientists in geographical information sciences is how to  integrate these data in order to respond to the new and emerging needs of the  society for the higher spatial data quality. Modern and personalized applications of the geospatial data require efficient, interactive and on-the-fly data integration. Semantic similarity assessment plays a very important role in ontology and spatial data integration. This paper, reviews different methods for semantic similarity assessment and proposes a new logical  based method in order to establish the necessary links between different ontologies. These links are then used in order to create a new ontology that will serve as basis for the integration of the spatial databases. For this study, we used the national topographic database of Canada and the topographic database of the Quebec province. Both of these databases cover the same geographical area. Most of the features in the databases are the same but, differences occur in the definitions of concepts, categories, classification, granularity and resolution, spatial relations, metric and topological constrains and etc. In this experimentation, the ontologies of the databases are formalised and represented in a knowledgebase then, a matching process proposed between the two ontologies and results were analysed in order to evaluate the proposed method for the similarity assessment of the concepts. Finally, further investigations are proposed in order to take in to account the ontology of the users in the integration process in order to guarantee the external quality of the integrated databases. 

Keywords: similarity assessment, Ontology, data quality, data integration, semantic

In: Caetano, M. and Painho, M. (eds). Proceedings of the 7th International Symposium on Spatial Accuracy Assessment in Natural Resources and Environmental Sciences, 5 – 7 July 2006, Lisboa, Instituto Geográfico Português

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