Similarity assessment between multiple geographic representations

Multiple representations include geographic data with different levels of detail, witch can turn into inconsistency. Inconsistency is caused due to the semantic, syntactic and spatial heterogeneity of data. In this paper we propose a methodology to asses similarity between spatial representations, taking account thematic, structural and spatial aspects of data. We also propose a metric called degree of semantic interoperability to asses a possible integration of data and to represent how data is consistent between data sources. As case study we work with towns in Mexico. Similarity is analyzed at different levels and in order to make it useful and clear to the user, it is represented in a graphic way.