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An Integration of Data by using UML Class Models Based on the Ontology Analysis

온톨로지 분석 기반의 UML클래스 모델을 이용한 데이터 통합

  • 서진원 (공주대학교 컴퓨터공학부) ;
  • 공헌택 (공주대학교 컴퓨터공학부) ;
  • 임재현 (공주대학교 컴퓨터공학부) ;
  • 김치수 (공주대학교 컴퓨터공학부)
  • Published : 2008.04.30

Abstract

Data integration is techniques to combine heterogeneous data from different sources, and to allow users to transparently access all data from multiple sources via a single view. The difficulty with data integration is data heterogeneity (i.e. schema heterogeneity, semantic heterogeneity). Richer semantics of data is a major factor in resolving conflicts among heterogeneous data sources. As UML class model represents only schema-based semantics of data, alternative methods such as ontology is useful for representing additional semantics. This paper proposes a method for integrating two data sources with UML class models by using an analysis of their ontologies. In our framework, ontology will be applied to describe semantics of data in each source. Then the ontologies are analysed and compared to determine their similarities and differences. The result of the comparison is used to devise an integrated ontology that will enable querying on the integrated information.

데이터 통합은 상이한 소스로부터 이종의 데이터를 결합하고, 사용자에게 단일 접근 점을 통해 다중 소스의 모든 데이터에 투명하게 액세스하는 것을 허용하는 기술이다. 데이터 통합의 어려움은 데이터의 이종성 즉, 스키마의 이종성, 시멘틱의 이종성이다. 따라서 데이터의 풍부한 시멘틱이 데이터 소스의 이종성으로 인한 충돌을 해결하기 위한 주요한 요인이다. 그러나 UML 클래스 모델에서는 데이터의 스키마 기반 시멘틱만을 표현하기 때문에 온톨로지와 같은 대안책을 이용해 추가적인 시멘틱을 제공하는 것이 바람직하다. 본 논문에서는 온톨로지 분석을 이용해 UML 클래스 모델로 표현된 두 데이터 소스를 통합하기 위한 방법을 제시한다. 여기서 온톨로지는 각 소스의 데이터에 대한 시멘틱을 표현하는데 적용된다. 온톨로지의 유사성과 차이점을 결정하기 위해 온톨로지를 분석하고 비교한다. 비교 결과는 통합 정보에 대해 질의가 가능한 통합 온톨로지를 구축하는데 사용된다.

Keywords

References

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