X−SOM: Ontology Mapping and Inconsistency Resolution

Abstract

Data integration is an old but still open issue in the database research area, where Semantic Web technologies, such as ontologies, may be of great help. Aim of the Context-ADDICT project is to provide support for the integration and context-aware reshaping of data coming from heterogeneous data sources. Within this framework, we use ontology extraction, alignment and tailoring to find and solve conflicts due to data source heterogeneity. In this paper we present X-SOM: an ontology mapping tool developed within the Context-ADDICT project. The contribution of this high precision mapping tool is twofold: (i) a modular and extensible architecture that automatically combines several matching techniques by means of a neural network,and (ii) a subsystem for the (semi)-automatic resolution of semantic inconsistencies. Besides describing the tool components, we discuss the prototype implementation, which has been tested against the OAIE 2006 benchmark with promising results, and effectively exploited within the Context-ADDICT project.