Journal of the Computational Structural Engineering Institute of Korea (한국전산구조공학회논문집)

Computational Structural Engineering Institute of Korea (한국전산구조공학회)
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Evaluation of Organization and Use of Data Model for Structural Experiment Information

구조실험정보를 위한 데이터 모델의 구성 및 사용성 평가

  • Lee, Chang-Ho (School of Architecture, Hankyong National Univ.)
  • Received : 2015.10.11
  • Accepted : 2015.11.02
  • Published : 2015.12.29
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Abstract

The data model for structural experiment information formally organizes the information involved in the structural experiments before the data repository using the data model is implemented. The data model is particularly required for the data repositories for the large-scale structural experiment information and the general information for various types of experiments, such as the NEEShub Project Warehouse developed by NEES. This paper proposes criteria for evaluating the organization and the use of design model for structural experiment information. The term of AVE(attribute value existence) indicates the ratio of attributes who values exist in objects, and then used for defining the Attribute AVE for the use of an attribute, the Class AVE for a class, the Class Level AVE for a class including its lower-level classes, the Project AVE for a project including all classes at class levels, and the Data Model AVE for a data model including projects. These criteria are applied to the projects in the NEES data model, and it is successively possible to numerically describe the evaluation of the use of classes and attributes in the data model.

구조실험을 위한 데이터 모델은 구조실험에 관련된 실험정보를 정형화하여 표현하므로 데이터 저장소를 개발하는데 이용할 수 있다. 데이터 모델은 특히 대규모의 구조실험정보 또는 일반적인 다양한 실험정보를 위한 데이터 저장소에 효과적인데 예를 들면 NEES에서 개발한 NEEShub Project Warehouse가 있다. 본 논문은 데이터 모델의 구성과 사용을 평가하기 위한 평가요소를 제안하고 있다. 클래스의 속성이 값을 갖는지를 의미하는 AVE(attribute value existence)란 용어를 도입하여 속성의 사용성에 대한 Attribute AVE, 클래스의 사용성에 대한 Class AVE, 하위레벨에 있는 클래스를 포함하는 Class Level AVE, 하나의 프로젝트의 모든 클래스를 포함하는 Project AVE, 모든 프로젝트를 포함하는 데이터 모델에 대한 Data Model AVE를 정의하였다. 이러한 평가요소들을 NEES 데이터 모델의 프로젝트들에 적용하였는데 데이터 모델내의 클래스와 객체에 대한 사용성을 수치적으로 기술하여 평가하는 것이 가능하였다.

Keywords

References

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