An efficient method of data quality using quality evaluation ontology

O. Hoon Choi, Jung Eun Lim, Hong Seok Na, Doo Kwon Baik

Research output: Chapter in Book/Report/Conference proceedingConference contribution

5 Citations (Scopus)

Abstract

In SOA (Service Oriented Architecture) and RTE (Real-Time Enterprise) environment, an assurance of data quality is important. Because we do not assure data accuracy among dynamic clustering data set. Traditional methodology for assuring data quality is data profiling and data auditing. However, that is needed lots of time and cost to analysis of metadata and business process for integrating system before evaluating data quality. In this paper, we propose an efficient methodology of assuring data quality with considering dynamic clustering data set. To extract evaluate rules for data quality, we use ontology that has meanings of each word in itself. We gain the relationship among word in ontology, and then make SQL to evaluate data accuracy, especially focused on data meaning.

Original languageEnglish
Title of host publicationProceedings - 3rd International Conference on Convergence and Hybrid Information Technology, ICCIT 2008
Pages1058-1061
Number of pages4
DOIs
Publication statusPublished - 2008
Event3rd International Conference on Convergence and Hybrid Information Technology, ICCIT 2008 - Busan, Korea, Republic of
Duration: 2008 Nov 112008 Nov 13

Publication series

NameProceedings - 3rd International Conference on Convergence and Hybrid Information Technology, ICCIT 2008
Volume2

Other

Other3rd International Conference on Convergence and Hybrid Information Technology, ICCIT 2008
Country/TerritoryKorea, Republic of
CityBusan
Period08/11/1108/11/13

ASJC Scopus subject areas

  • Information Systems
  • Software

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