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Visualizing risk management data associated with capital expenditure projects

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Title: Visualizing risk management data associated with capital expenditure projects
Author: Nezafatkhah, Sadaf
Degree Master of Applied Science - MASc
Program Civil Engineering
Copyright Date: 2011
Publicly Available in cIRcle 2011-09-27
Abstract: Described in this thesis is an approach for visualizing data associated with the risk management function for large capital expenditure projects. The thesis first explores the current use of data visualization in support of the analytical reasoning involved in the risk management process and then explores some additional images that facilitate the process of extracting information in response to specific analytical reasoning needs. Contributions include casting light on the state-of-the-art of the use of data visualization in support of risk management (i.e. visualization tools that exist) and setting out the kind of analytical reasoning that could be supported by the use of data visualization (i.e. target analytical reasoning based on which visualization tools should be developed). By identifying analytical reasoning tasks of interest, risk visualization tools can be structured to respond to them. A few visual representations of risk related data are proposed and their potential worth is judged by assessing how well they respond to the analytical reasoning tasks of interest. We found that one of the main challenges in representing multidimensional risk data for construction projects is the ability to visualize in a non-cluttered manner the large amount of information contained in the risk register of a full scale project. Therefore, it is important to equip images with interactive features in order to visualize subsets of information (by phase, by product, by participant, and by location.). We have concluded that with respect to the visualization tools suggested, although they respond to the analytic reasoning needs targeted, easily become cluttered when a large amount of information is to be visualized, thus limiting their application.
URI: http://hdl.handle.net/2429/37663
Scholarly Level: Graduate

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