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http://dx.doi.org/10.9708/jksci.2011.16.6.119

A Data Cleansing Strategy for Improving Data Quality of National R&D Information - Case Study of NTIS  

Shin, Sung-Ho (Dept. of Information Technology Research, KISTI)
Yoon, Young-Jun (Dept. NTIS, KISTI)
Yang, Myung-Suk (Dept. NTIS, KISTI)
Kim, Jin-Man (Dept. NTIS, KISTI)
Shon, Kang-Ryul (Dept. NTIS, KISTI)
Publication Information
Journal of the Korea Society of Computer and Information / v.16, no.6, 2011 , pp. 119-130 More about this Journal
Abstract
On the point of data quality management, data quality is influenced by quality policy, quality organization, business process, and business rule. Business rules, guide of data manipulation, have effects on data quality directly. In case of building an integration database among distributed databases, defining business rule is more important because data integration needs to consider heterogeneous structure, code, and data standardization. Also data value has various figures depended on data type, unit, and transcription. Finally, database structure and data value problem have to be solved to improve data quality. For handling them, it is needed to draw database integration model and cleanse data in integrated database. NTIS(stands for National science and Technology Information Service) has an aim to serve users who need all information about national R&D by internet, and for that aim, it has a integrated database which has been made with several database sources. We prove that database integration model and data cleansing are needed to build a successful integrated database through NTIS case study.
Keywords
Data Quality; Data Cleansing; Database Integration;
Citations & Related Records
Times Cited By KSCI : 1  (Citation Analysis)
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