Semantic Conflicts Reconciliation as a Viable Solution for Semantic Heterogeneity Problems

Abstract

Achieving semantic interoperability is a current challenge in the field of data integration in order to bridge semantic conflicts occurring when the participating sources and receivers use different or implicit data assumptions. Providing a framework that automatically detects and resolves semantic conflicts is considered as a daunting task for many reasons, it should preserve the local autonomy of the integrated sources, as well as provides a standard query language for accessing the integrated data on a global basis. Many existing traditional and ontology-based approaches have tried to achieve semantic interoperability, but they have certain drawbacks that make them inappropriate for integrating data from a large number of participating sources.We propose semantic conflicts reconciliation (SCR) framework, it is ontology-based system in which all data semantics explicitly described in the knowledge representation phase and automatically taken into account through the interpretation mediation service phase, so conflicts detected and resolved automatically at the query time.