Generating a network of information dependencies automatically

Year: 2012
Editor: Onishi, M.; Maurer, M.; Kirner, K.; Lindemann, U.
Author: Senescu, R. R.; Head, A. W.; Steinert, M.; Fischer, M. A.
Series: DSM
Institution: Stanford University, USA
Section: Modelling Approaches and Information Acquisition
Page(s): 139-152
ISBN: 978-3-446-43354-0


Creating design structure matrices (DSM) requires hours of up front effort. Though previous research
demonstrated a return on investment for applying DSM methods to project planning and control,
widespread industry adoption remains elusive. Even without improved workflow plans, revealing
information dependencies has been shown to improve collaboration within teams and process sharing
between teams. This paper contributes the proof-of-concept Automatic Information Dependency
Algorithm (AIDA) which infers a network of information dependence in real-time by capturing how
professionals interact with files. Though not yet able to predict dependencies well enough for industry
adoption, we aim to lay the foundation for embedding DSM methods in projects at a level
commensurate with the way professionals use Windows Explorer.

Keywords: Automated, information, dependencies, network inference

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