Increasing the perceptual salience of relationships in parallel coordinate plots

Jonathan M. Harter; Xunlei Wu; Oluwafemi S. Alabi; Madhura Phadke; Lifford Pinto; Daniel Dougherty; Hannah Petersen; Steffen Bass; Russell M. Taylor II

doi:10.1117/12.907486

24 January 2012 Increasing the perceptual salience of relationships in parallel coordinate plots

Jonathan M. Harter, Xunlei Wu, Oluwafemi S. Alabi, Madhura Phadke, Lifford Pinto, Daniel Dougherty, Hannah Petersen, Steffen Bass, Russell M. Taylor II

Author Affiliations +

Proceedings Volume 8294, Visualization and Data Analysis 2012; 82940T (2012) https://doi.org/10.1117/12.907486
Event: IS&T/SPIE Electronic Imaging, 2012, Burlingame, California, United States

Abstract

We present three extensions to parallel coordinates that increase the perceptual salience of relationships between axes in multivariate data sets: (1) luminance modulation maintains the ability to preattentively detect patterns in the presence of overplotting, (2) adding a one-vs.-all variable display highlights relationships between one variable and all others, and (3) adding a scatter plot within the parallel-coordinates display preattentively highlights clusters and spatial layouts without strongly interfering with the parallel-coordinates display. These techniques can be combined with one another and with existing extensions to parallel coordinates, and two of them generalize beyond cases with known-important axes. We applied these techniques to two real-world data sets (relativistic heavy-ion collision hydrodynamics and weather observations with statistical principal component analysis) as well as the popular car data set. We present relationships discovered in the data sets using these methods.

Citation Download Citation

Jonathan M. Harter, Xunlei Wu, Oluwafemi S. Alabi, Madhura Phadke, Lifford Pinto, Daniel Dougherty, Hannah Petersen, Steffen Bass, and Russell M. Taylor II "Increasing the perceptual salience of relationships in parallel coordinate plots", Proc. SPIE 8294, Visualization and Data Analysis 2012, 82940T (24 January 2012); https://doi.org/10.1117/12.907486

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