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Evaluation of Organization and Use of Data Model for Structural Experiment Information
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 Title & Authors
Evaluation of Organization and Use of Data Model for Structural Experiment Information
Lee, Chang-Ho;
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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.
 Keywords
data model;class;class level;object;attribute;structural experiment information;NEES;
 Language
Korean
 Cited by
 References
1.
Hong, N.K., Sause, R. (1994) Concepts and Notation for Integrated Structural Design: Product and Precess Models, ATLSS Report No. 94-13, Advanced Technology for Large Structural Systems (ATLSS) Center, Lehigh University, Lehigh University, USA.

2.
Lee, C.-H. (2010) Criteria for Evaluating Characteristics of Data Models for Structural Experiment Information, J. Archit. Inst. Korea: Struct. & Constr., 26(8), pp.29-38.

3.
Lee, C.-H. (2013) Evaluation Criteria of Organizational Characteristics of Data Repositories for Structural Experiment Information, J. Archit. Inst. Korea: Struct. & Constr., 29(7), pp.55-64.

4.
Lee, C.-H. (2014) Evaluation Criteria of Attributes of Classes and Objects of Data Repositories for Structural Experiment Information, J. Comput. Struct. Eng. Inst. Korea, 27(6), pp.653-662. crossref(new window)

5.
Lee, C.-H., Chin, C.H., Marullo, T., Bryan, P., Sause, R., Ricles, J.M. (2008) Data Model for Large-Scale Structural Experiment, J. Earthq. Eng., 12, pp.115-139. crossref(new window)

6.
Lee, C.-H., Sause, R., Hong, N.K. (1998) Overview of Entity-Based Integrated Design Product and Process Models, Adv. Eng. Softw., 29(10), pp.809-823. crossref(new window)

7.
http://www.koced.net Website for the Korea Construction Engineering Development Collaboratory Management Institute (KOCED CMI).

8.
https://nees.org Website for George E. Brown, Jr. Network for Earthquake Engineering Simulation (NEES), USA.

9.
Peng, J., Law, K. (2004) Reference NEESgrid Data Model, Technical Report NEESgrid-2004-40, George E. Brown, Jr. Network for Earthquake Engineering Simulation (NEES), USA.