Semantic Conflict Resolution Ontology (SCROL): An Ontology for Detecting and Resolving Data and Schema-Level Semantic Conflicts
Issue No. 02 - February (2004 vol. 16)
Sudha Ram , IEEE
Jinsoo Park , IEEE
<p><b>Abstract</b>—Establishing semantic interoperability among heterogeneous information sources has been a critical issue in the database community for the past two decades. Despite the critical importance, current approaches to semantic interoperability of heterogeneous databases have not been sufficiently effective. We propose a common ontology called <b>S</b>emantic <b>C</b>onflict <b>R</b>esolution <b>O</b>nto<b>l</b>ogy (SCROL) that addresses the inherent difficulties in the conventional approaches, i.e., federated schema and domain ontology approaches. SCROL provides a systematic method for automatically detecting and resolving various semantic conflicts in heterogeneous databases. SCROL provides a dynamic mechanism of comparing and manipulating contextual knowledge of each information source, which is useful in achieving semantic interoperability among heterogeneous databases. We show how SCROL is used for detecting and resolving semantic conflicts between semantically equivalent schema and data elements. In addition, we present evaluation results to show that SCROL can be successfully used to automate the process of identifying and resolving semantic conflicts.</p>
Heterogeneous databases, ontology, semantic conflict resolution, semantic modeling.
S. Ram and J. Park, "Semantic Conflict Resolution Ontology (SCROL): An Ontology for Detecting and Resolving Data and Schema-Level Semantic Conflicts," in IEEE Transactions on Knowledge & Data Engineering, vol. 16, no. , pp. 189-202, 2004.