Data and Information Quality Research in Engineering Construction Projects: A Review of Literature

This article presents a review of the research on Data and Information Quality (DQ/IQ) assessment in engineering construction. Through a review of 445 articles on the topic, only nine were found in the context of engineering construction. The analysis of these nine articles revealed six challenges in performing DQ/IQ assessment in this context: the iterative nature of concurrent engineering, the uniqueness of engineering data, lack of integration between processes, lack of integration between systems, lack of timely information, and lack of relevant DQ/IQ assessment frameworks and tools. The specific contributions of this paper are the identification of DQ/IQ challenges in engineering construction, their consequences, and implications for the development of relevant DQ/IQ assessment frameworks and tools. Additionally, it also identifies an area where Information Systems research can contribute, thereby extending the reach of the discipline.

[1]  Ismail Abdul Rahman,et al.  Preliminary Study on Causative Factors Leading to Construction Cost Overrun , 2011 .

[2]  Richard Y. Wang,et al.  Anchoring data quality dimensions in ontological foundations , 1996, CACM.

[3]  Diane M. Strong,et al.  Data quality in context , 1997, CACM.

[4]  Qinli Dyrhaug,et al.  A generalized Critical Success Factor Process Model for Managing Offshore Development Projects in Norway , 2002 .

[5]  Richard Y. Wang,et al.  Information Products for Remanufacturing: Tracing the Repair of an Aircrfat Fuel-Pump , 2001, IQ.

[6]  Mysore Ramaswamy,et al.  ON THE PHENOMENON OF INFORMATION DILUTION , 2006 .

[7]  Murali Sambasivan,et al.  Causes and effects of delays in Malaysian construction industry , 2007 .

[8]  Sameh M. El-Sayegh,et al.  Significant factors causing delay in the UAE construction industry , 2006 .

[9]  Richard T. Watson,et al.  Analyzing the Past to Prepare for the Future: Writing a Literature Review , 2002, MIS Q..

[10]  Stephen O. Ogunlana,et al.  Large construction projects in developing countries: a case study from Vietnam , 2004 .

[11]  M. Pollitt,et al.  The Welfare Implications of Oil Privatization: A Cost-Benefit Analysis of Norway's Statoil , 2009 .

[12]  Florence Yean Yng Ling,et al.  Strengths, Weaknesses, Opportunities, and Threats for Architectural, Engineering, and Construction Firms: Case Study of Vietnam , 2009 .

[13]  Andy Koronios,et al.  A data quality framework for engineering asset management , 2008, WCE 2008.

[14]  Andy Koronios,et al.  The Deficiencies of Current Data Quality Tools in the Realm of Engineering Asset Management , 2006, AMCIS.

[15]  Soffi Westin,et al.  Information quality in large engineering and construction projects: a delphi case study , 2011, ECIS.

[16]  Morgan Ericsson,et al.  A Metrics-Based Approach to Technical Documentation Quality , 2010, 2010 Seventh International Conference on the Quality of Information and Communications Technology.

[17]  Richard Y. Wang,et al.  Data quality assessment , 2002, CACM.

[18]  Chitu Okoli,et al.  A Guide to Conducting a Systematic Literature Review of Information Systems Research , 2010 .

[19]  Andy Koronios,et al.  Developing a data quality framework for asset management in engineering organisations , 2007, Int. J. Inf. Qual..

[20]  Sandeep Purao,et al.  Action Design Research , 2011, MIS Q..

[21]  Stuart E. Madnick,et al.  Overview and Framework for Data and Information Quality Research , 2009, JDIQ.

[22]  Diane M. Strong,et al.  Beyond Accuracy: What Data Quality Means to Data Consumers , 1996, J. Manag. Inf. Syst..

[23]  Paul M. Goodrum,et al.  Construction Craft Workers’ Perceptions of the Factors Affecting Their Productivity , 2009 .

[24]  Carlo Batini,et al.  Methodologies for data quality assessment and improvement , 2009, CSUR.

[25]  Stephen O. Ogunlana,et al.  Problems causing delays in major construction projects in Thailand , 2008 .

[26]  Alan R. Hevner,et al.  Design Science in Information Systems Research , 2004, MIS Q..

[27]  Frank Lauterwald,et al.  Supporting the Production of High-Quality Data in Concurrent Plant Engineering Using a MetaDataRepository , 2010, AMCIS.

[28]  Yang W. Lee,et al.  Crafting Rules: Context-Reflective Data Quality Problem Solving , 2003, J. Manag. Inf. Syst..

[29]  Rafael Sacks,et al.  An Empirical Study of Information Flows in Multidisciplinary Civil Engineering Design Teams using Lean Measures , 2011 .