Visualizing node attribute uncertainty in graphs

Nathaniel Cesario; Alex Pang; Lisa Singh

doi:10.1117/12.872677

24 January 2011 Visualizing node attribute uncertainty in graphs

Nathaniel Cesario, Alex Pang, Lisa Singh

Proceedings Volume 7868, Visualization and Data Analysis 2011; 78680H (2011) https://doi.org/10.1117/12.872677
Event: IS&T/SPIE Electronic Imaging, 2011, San Francisco Airport, California, United States

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.

Citation Download Citation

Nathaniel Cesario, Alex Pang, and Lisa Singh "Visualizing node attribute uncertainty in graphs", Proc. SPIE 7868, Visualization and Data Analysis 2011, 78680H (24 January 2011); https://doi.org/10.1117/12.872677

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