Data quality enhanced asset management metadata model

  • Jing Gao
  • Andy Koronios
  • Steve Kennett
  • Halina Scott
Conference paper


Researchers 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). The development of metadata standards is considered as an effective approach to address various data quality issues. Our literature review shows that there has been little study on the development of metadata standards for engineering asset management. Thus, this research has proposed a preliminary EAM metadata model as a result of the study into various related mature metadata standards with a strong focus on data quality assurance. It is believed that this model will provide useful contributions to generic or organisational specific metadata standard development in engineering asset management organizations.


Data Warehouse Asset Management Metadata Standard Move Picture Expert Group Data Quality Assurance 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag 2010

Authors and Affiliations

  • Jing Gao
    • 1
  • Andy Koronios
    • 1
  • Steve Kennett
    • 2
  • Halina Scott
    • 3
  1. 1.School of Computer and Information ScienceUniversity of South AustraliaMawson LakesAustralia
  2. 2.Maritime Platforms DivisionDefence Science and Technology OrganisationMelbourneAustralia
  3. 3.Strategy & Research, Logistics Mgmt GroupDefence materiel organisationSydneyAustralia

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