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Semantic Conflicts Reconciliation ( SCR ) : A Framework for Detecting and Reconciling Data-Level Semantic Conflicts .

Integration of heterogeneous data sources is not an easy task that involves reconciliation of various levels of conflicts. Before we can integrate the heterogeneous data, we need to resolve these heterogeneity conflicts. Semantic conflict, if undetected, can lead to disastrous results in even the simplest information system. In this paper, we recommend system architecture to solve the semantic data level conflicts that related to different representation or interpretation of data contexts among different sources and receivers. In the proposed ontology-based approach, all data semantics explicitly described in the knowledge representation phase and automatically taken into account by Interpretation Mediation Services phase so conflicts can automatically detect and resolved at the query runtime. Data sources still independent from the integration process that is mean we can retrieve up to date data and smoothly update the data in each data source without affecting the framework.