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Ensuring data Quality for Asset Management in Engineering organisations

Ensuring data Quality for Asset Management in Engineering organisations
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Author(s): Shien Lin (University of South Australia, Australia), Jing Gao (University of South Australia, Australia) and Andy Koronios (University of South Australia, Australia)
Copyright: 2007
Pages: 7
Source title: Managing Worldwide Operations and Communications with Information Technology
Source Editor(s): Mehdi Khosrow-Pour, D.B.A. (Information Resources Management Association, USA)
DOI: 10.4018/978-1-59904-929-8.ch100
ISBN13: 9781599049298
EISBN13: 9781466665378

Abstract

Data Quality (DQ) has been an acknowledged issue for a long time. Researches have indicated that maintaining the quality of data is often acknowledged as problematic, but is also seen as critical to effective decision-making in engineering asset management (AM). This paper investigates the issues emerging from unique nature of engineering asset data. It discusses the various AM data quality issues and presents exploratory research on how engineering asset organizations in Australia are addressing DQ issues based on a large scale national-wide DQ survey that was conducted. It provides a better understanding of AM DQ issues and assists in identifying elements which will contribute towards the development of an AM specific DQ framework. The research findings suggest that while the organizations are concerning the quality of data, there is a disconnection between data custodians and data producers and high level data owners. The majority of AM organizations still adopt a reactive approach on DQ management. This paper reports on a national survey as well as structured interviews with a number of stakeholders from engineering asset management organizations.

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