Overcoming semantic heterogeneity in spatial data infrastructures

In current spatial data infrastructures (SDIs), it is still often difficult to effectively exchange or re-use geographic data sets. A main reason for this is semantic heterogeneity, which occurs at different levels: at the metadata, the schema and the data content level. It is the goal of the work presented in this paper to overcome the problems caused by semantic heterogeneity on all three levels. We present a method based on ontologies and logical reasoning, which enhances the discovery, retrieval, interpretation and integration of geographic data in SDIs. Its benefits and practical use are illustrated with examples from the domains of geology and hydrology.