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Achieving Data Quality in Engineering Asset Management

Achieving Data Quality in Engineering Asset Management
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Author(s): Jing Gao (University of South Australia, Australia), Shien Lin (University of South Australia, Australia) and Andy Koronios (University of South Australia, Australia)
Copyright: 2006
Pages: 4
Source title: Emerging Trends and Challenges in Information Technology Management
Source Editor(s): Mehdi Khosrow-Pour, D.B.A. (Information Resources Management Association, USA)
DOI: 10.4018/978-1-59904-019-6.ch163
ISBN13: 9781616921286
EISBN13: 9781466665361

Abstract

Data Quality (DQ) is a critical issue for effective asset management (AM). DQ problems can result in severe negative consequences for an organisation. Several research studies have indicated that most organizations have DQ problems. This paper aims to explore DQ issues associated with engineering asset management (EAM). The study applies an AM DQ research framework in a preliminary case study of two large Australian utility organisations. The findings of the study suggest that the importance of DQ issues for engineering asset management is often overlooked; thus, there is a need for more scrutinised studies in order to raise general awareness.

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