Structural Alignment Methods with Applications to Geospatial Ontologies

We consider the problem of enabling interoperability and information sharing among geospatial applications that use ontologies to describe their concepts and the relationships among them. We present two fully automatic alignment methods that use the graph structures of a pair of ontologies to establish their alignment, that is, the semantic correspondences between their concepts. We have tested our methods on geospatial ontologies pertaining to wetlands and four other pairs that belong to a repository that has been used in the Ontology Alignment Evaluation Initiative (OAEI). Using these ontologies, we have compared the effectiveness (precision and recall) of our methods against the Similarity Flooding Algorithm that was proposed by others and show that for each of the tested ontologies one of our methods is at least as effective as their method. We have tuned the performance of our methods by introducing a greedy approach that reduces the number of concepts that get compared. This approach reduces runtime by approximately 30% with a minor compromise to the effectiveness of the results. To further validate our approach, we participated in the OAEI competition to align a pair of ontologies, each with a few thousand concepts.