High value information in engineering organisations

  • Authors:

  • Yuyang Zhao;L. C. M. Tang;M. J. Darlington;S. A. Austin;S. J. Culley

  • Affiliations:

  • Department of Mechanical Engineering, University of Bath, Bath, BA2 7AY, UK;Department of Civil and Building Engineering, Loughborough University, Loughborough, Leicestershire, LE11 3TU, UK;Department of Mechanical Engineering, University of Bath, Bath, BA2 7AY, UK;Department of Civil and Building Engineering, Loughborough University, Loughborough, Leicestershire, LE11 3TU, UK;Department of Mechanical Engineering, University of Bath, Bath, BA2 7AY, UK

  • Venue:
  • International Journal of Information Management: The Journal for Information Professionals
  • Year:
  • 2008

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Abstract

The management of information in engineering organisations is facing a particular challenge in the ever-increasing volume of information. It has been recognised that an effective methodology is required to evaluate information in order to avoid information overload and to retain the right information for reuse. By using, as a starting point, a number of the current tools and techniques which attempt to obtain 'the value' of information, it is proposed that an assessment or filter mechanism for information is needed to be developed. This paper addresses this issue firstly by briefly reviewing the information overload problem, the definition of value, and related research work on the value of information in various areas. Then a ''characteristic'' based framework of information evaluation is introduced using the key characteristics identified from related work as an example. A Bayesian Network diagram method is introduced to the framework to build the linkage between the characteristics and information value in order to quantitatively calculate the quality and value of information. The training and verification process for the model is then described using 60 real engineering documents as a sample. The model gives a reasonable accurate result and the differences between the model calculation and training judgements are summarised as the potential causes are discussed. Finally, several further issues including the challenge of the framework and the implementations of this evaluation assessment method are raised.