Semantic heterogeneity in global information systems: The role of metadata, context and ontologies

Semantic heterogeneity has been identied as one of the most important and toughest prob lems when dealing with interoperability and cooperation among multiple databases It was earlier studied in the context of exchanging sharing and integrating data especially during the schemaview analysis phase of schema or view integration or when writing a view or query using a multidatabase language With the advent of global interconnectivity we now need to deal with more heterogeneous information resources consisting of a variety of digital data and the scale of the problem has changed from a few databases to millions of information resources thus making it more important than ever to address this problem It is also recognized that the problem has only become harder and that simplistic solutions involving only representational or structural components of data will not work beyond a very restricted set of cases In this chapter we explore approaches to tackle the semantic heterogeneity problem in the context of Global Information Systems GIS which are systems geared to handle information requests on the Global Information Infrastructure GII These approaches are based on the capture and representation of metadata contexts and ontologies In order to handle infor mation overload it would be advantageous to abstract out the representational details of the underlying data and capture the information content by using domain specic metadata The next important step is that of understanding the context of the query using metadata to con struct the context and identifying the relevant data in that context Another critical issue that arises here is that of dierent vocabularies used to characterize similar information We present an approach to deal with this problem at the metadatacontext level by using terms from do main specic ontologies to construct metadatacontext We deal with semantic heterogeneity at this level and propose an approach using terminological relationships to achieve semantic interoperabilit