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Distinct 3D Glyphs with Data Layering for Highly Dense Multivariate Data Plots

Lombeyda, Santiago V. (2016) Distinct 3D Glyphs with Data Layering for Highly Dense Multivariate Data Plots. . (Submitted)

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A carefully constructed scatterplot can reveal plenty about an underlying data set. However, in most cases visually mining and understanding a large multivariate data set requires more finesse, and greater level of interactivity to really grasp the full spectrum of the information being presented. We present a paradigm for glyph design and use in the creation of single plots presenting multiple variables of information. We center our design on two key concepts. The first concept is that visually it is easier to discriminate between completely distinct shapes rather than subtly different ones, specially when partially occluded. The second one is that users ingest information in layers, i.e. in an order of visual relevance. Using this paradigm, we present complex data as binned into desired and relevant discrete categories. We show results in the areas of high energy physics and security, displaying over 6 distinct data variables in each single plot, yielding a clear, highly readable, and effective visualization.

Item Type:Report or Paper (Discussion Paper)
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Additional Information:We would like to thank: Julian Bunn for providing High Energy Physics data, and serving as an expert evaluator from the field; Roy Williams for providing the VAST graph and serving as expert evaluators from the field; Mathieu Desbrun for aid in refining of ideas and editing. This work was funded by the Moore Foundation through Caltech’s Cell Center, and by the NNSA’s Predictive Science Academic Alliance Program (PSAAP), through Caltech’s PSAAP Center of Excellence.
Funding AgencyGrant Number
Gordon and Betty Moore FoundationUNSPECIFIED
Department of Energy (DOE) National Nuclear Security AdministrationUNSPECIFIED
Record Number:CaltechAUTHORS:20160203-080718999
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Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:64180
Deposited By: Tony Diaz
Deposited On:03 Feb 2016 23:24
Last Modified:03 Oct 2019 09:35

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