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    Visualizing node attribute uncertainty in graphs

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    View/Open: Singh_VisualizingNodeAttribute.pdf (1.8MB) Bookview

    Creator
    Cesario, Nathaniel
    Pang, Alex
    Singh, Lisa
    Abstract
    Visualizations can potentially misrepresent information if they ignore or hide the uncertainty that are usually present in the data. While various techniques and tools exist for visualizing uncertainty in scientific visualizations, there are very few tools that primarily focus on visualizing uncertainty in graphs or network data. With the popularity of social networks and other data sets that are best represented by graphs, there is a pressing need for visualization systems to show uncertainty that are present in the data. This paper focuses on visualizing a particular type of uncertainty in graphs – we assume that nodes in a graph can have one or more attributes, and each of these attributes may have an uncertainty associated with it. Unlike previous efforts in visualizing node or edge uncertainty in graphs by changing the appearance of the nodes or edges, e.g. by blurring, the approach in this paper is to use the spatial layout of the graph to represent the uncertainty information. We describe a prototype tool that incorporates several uncertainty-to-spatial layout mappings and describe a scenario showing how it might be used for a visual analysis task.
    Description
    Computer Science
    Permanent Link
    http://hdl.handle.net/10822/761517
    Date Published
    2011
    Subject
    Information visualization
    Type
    text
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    • Faculty Scholarship - Computer Science Department
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    Georgetown University Seal
    ©2009 - 2023 Georgetown University Library
    37th & O Streets NW
    Washington DC 20057-1174
    202.687.7385
    digitalscholarship@georgetown.edu
    Accessibility