Semantic Conflict Resolution Ontology (SCROL): An Ontology for Detecting and Resolving Data and Schema-Level Semantic Conflicts

Sudha Ram, Jinsoo Park

Research output: Contribution to journalArticlepeer-review

136 Scopus citations

Abstract

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 Semantic Conflict Resolution Ontology (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.

Original languageEnglish (US)
Pages (from-to)189-202
Number of pages14
JournalIEEE Transactions on Knowledge and Data Engineering
Volume16
Issue number2
DOIs
StatePublished - Feb 2004

Keywords

  • Heterogeneous databases
  • Ontology
  • Semantic conflict resolution
  • Semantic modeling

ASJC Scopus subject areas

  • Information Systems
  • Computer Science Applications
  • Computational Theory and Mathematics

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