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High value information in engineering organizations

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conference contribution
posted on 2009-07-29, 08:50 authored by Yuyang Zhao, L.C.M. Tang, M.J. Darlington, Simon Austin, S.J. Culley
The management of information in engineering organizations is facing a particular challenge in the ever-increasing volume of information. It has been recognized 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 judgments are summarized as the potential causes are discussed. Finally several further the issues including the challenge of the framework and the implementations of this evaluation assessment method are raised.



  • Architecture, Building and Civil Engineering


ZHAO, Y. ... et al., 2007. High value information in engineering organizations. KIM Project Conference 2007, 28-29 March, Loughborough University, Loughborough, UK


  • AM (Accepted Manuscript)

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This is a conference paper presented at the KIM Project Conference 2007. More details of the KIM project can be found at: http://www-edc.eng.cam.ac.uk/kim/ This paper was also published in the International Journal of Information Management, 28(4), pp. 246-258 [© Elsevier] and the definitive version is available at: http://dx.doi.org/10.1016/j.ijinfomgt.2007.09.007


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