Mediation system for dealing with semantic problems in databases

Integration of heterogeneous data sources is a difficult task for providing users with the unified interface without semantic heterogeneity problems. We can classify this type of heterogeneity into query-level heterogeneity and data source-level heterogeneity. The first level is related to different expressions defined by different users to the same query. The second level of heterogeneity is related to various representations of the data value and to different definitions to describe the same data. In this context, we propose a novel semantic mediation system to solve the diverse levels of semantic heterogeneity in databases. We use ONTology of Alimentation RISks (ONTARIS), our domain ontology on alimentation risks as well as a shared schema of mediator. The results of the experimental evaluation suggest that correct identification and construction of ontology schema matching play a very important role in solving semantic heterogeneity at both the query and database levels.

• semantic mediation
• semantic heterogeneity
• heterogeneous data integration
• ontology mapping
• food safety
• ontology-based data access

• Semantic Web and Ontologies
• Biomedical Text Mining and Ontologies
• Advanced Database Systems and Queries
• semantic mediation
• semantic heterogeneity
• heterogeneous data integration
• ontology mapping
• food safety
• ontology-based data access
• Artificial Intelligence
• Molecular Biology
• Computer Networks and Communications
• Computer Science
• Biochemistry, Genetics and Molecular Biology