한국산학기술학회논문지 (Journal of the Korea Academia-Industrial cooperation Society)

  • 제9권2호
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  • Pages.422-430
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  • 2008
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  • 1975-4701(pISSN)
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  • 2288-4688(eISSN)
한국산학기술학회 (The Korea Academia-Industrial cooperation Society)
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온톨로지 분석 기반의 UML클래스 모델을 이용한 데이터 통합

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

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

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.

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.

키워드

참고문헌

  1. Ram, S. and Park, J. Semantic conflict resolution ontology(SCROL): an ontology for detecting and resolving data and schema-level semantic conflicts. Knowledge and Data Engineering, IEEE Transactions on, 16 (2). 189-202, 2004. https://doi.org/10.1109/TKDE.2004.1269597
  2. Gruber, T., A Translation Approach to Portable Ontology Specifications. Knowledge Acquisition, 5 (2). 199 - 220, 1993. https://doi.org/10.1006/knac.1993.1008
  3. Swasrukkiet, S. A Methodology for Integration of Object-Oriented Data Models Using Heuristics and Analysis of Relationships between Class. Department of Computer Engineering, Chulalongkorn University, Bangkok, 1999.
  4. DSTC. Ontology Definition MetaModel - DSTC Initial Submission, OMG, 2003.
  5. Mena, E., Illarramendi, A., et al. OBSERVER: An Approach for Query Processing in Global Information Systems based on Interoperation across Pre-existing Ontologies. Distributed and Parallel Databases -- An International Journal, 8 (2). 223-271, 1996.
  6. Stumme, G. and Maedche, A., FCA-MERGE: Bottom-Up Merging of Ontologies. in The Seventeenth International Joint Conference on Artificial Intelligence, 2001.
  7. Noy, N.F. and Musen, M.A., PROMPT: Algorithm and Tool for Automated Ontology Merging and Alignment. in The Seventeenth National Conference on Artificial Intelligence and Twelfth Conference on Innovative Applications of Artificial Intelligence, (2000), AAAI Press / The MIT Press, 450 - 455.
  8. McGuinness, D.L., Fikes, R., et al., An Environment for Merging and Testing Large Ontologies. in Proceedings of the Seventh International Conference on Principles of Knowledge Representation and Reasoning (KR2000), (Breckenridge, Colorado, 2000).
  9. Wache, H., Vogele, T., et al., Ontology-Based Integration of Information - A Survey of Existing Approaches. in The Seventeenth International Joint Conference on Artificial Intelligence, 2001.
  10. Arens, Y., Hsu, C.-N., et al. Query Processing in the SIMS Information Mediator. in eadings in agents, Morgan Kaufmann Publishers Inc, 82 - 90, 1998.
  11. Goh, C.H., Bressan, S.p., et al. Context Interchange: New Features and Formalisms for the Intelligent Integration of Information. ACM Transactions on Information Systems (TOIS), 17 (3). 270-293, 1997.
  12. Wache, H., Scholz, T., et al., An integration method for the specification of rule-oriented mediators. in Database Applications in Non-Traditional Environments, 1999. (DANTE '99) Proceedings. 1999 International Symposium on, 109-112, 1999.
  13. Colomb, R.M., Gerber, A., et al., Issues in Mapping Metamodels in the Ontology Development Metamodel Using QVT. in The 1st International Workshop on the Model-Driven Semantic Web (MSDW 2004), 2004.
  14. Dean, M. Java2OWL, DAML.org, 2003.