Ontology Mapping by Identity Conditions

1 The Aim of Research In our research, we focus on ontology mapping. The imperial goal of ontology mapping is to resolve semantic heterogeneity that is one of the key challenges in integrating and sharing data and knowledge across disparate sources, data warehousing, multi-agent systems and the Semantic Web. The process of ontology mapping concerns how classes from one ontology can be semantically mapped to classes of another ontology in an automated way. The recent methodologies and tools for ontology mapping are attempted in semi-automatic and automatic. They have a discovery of matches by using a common reference ontology, referring linguistic ontologies, analyzing lexical information and structural information, applying statistic and probabilistic models with prior matches, and machine learning techniques. The majority of mapping tools use the structural information to discover mappings. This information includes subsumption relationships (super-sub), related properties of a class, domains and ranges of properties, class siblings, and so on. As structural information consists of semantic heterogeneity such as different namings, schemas, and domains of classes an exhaustive discovery of mappings between two ontologies is a really complex process in practice. Though all the tools intend their processes to be automatic, a considerable amount of user interaction is necessarily involved for verification and thus a complete automation is still beyond of the current results. Therefore, we observe an alternative mapping approach to reduce complexity and to increase accuracy of matches with less of user intervention.