Title: Developing a data quality framework for asset management in engineering organisations

Authors: Shien Lin, Jing Gao, Andy Koronios, Vivek Chanana

Addresses: Strategic Information Management Lab, School of Computer and Information Science, University of South Australia, Mawson Lakes, SA 5095, Australia. ' Strategic Information Management Lab, School of Computer and Information Science, University of South Australia, Mawson Lakes, SA 5095, Australia. ' Strategic Information Management Lab, School of Computer and Information Science, University of South Australia, Mawson Lakes, SA 5095, Australia. ' Strategic Information Management Lab, School of Computer and Information Science, University of South Australia, Mawson Lakes, SA 5095, Australia

Abstract: Data Quality (DQ) is seen as critical to effective business decision-making. However, maintaining DQ is often acknowledged as problematic. Asset data is the key enabler in gaining control of assets. The quality asset data provides the foundation for effective Asset Management (AM). Researches have indicated that achieving AM DQ is the key challenge engineering organisations face today. This paper investigates the DQ issues emerging from the unique nature of engineering AM data. It presents an exploratory research of a large scale national-wide DQ survey on how Australian engineering organisations address DQ issues, and proposes an AM specific DQ framework.

Keywords: data quality; DQ; engineering asset management; information quality; Australia.

DOI: 10.1504/IJIQ.2007.013378

International Journal of Information Quality, 2007 Vol.1 No.1, pp.100 - 126

Published online: 23 Apr 2007 *

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