Visualizing Multidimensional Data with Glyph SPLOMs

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dc.contributor.authorYates, Andrewen_US
dc.contributor.authorWebb, Allisonen_US
dc.contributor.authorSharpnack, Michaelen_US
dc.contributor.authorChamberlin, Helenen_US
dc.contributor.authorHuang, Kunen_US
dc.contributor.authorMachiraju, Raghuen_US
dc.contributor.editorH. Carr, P. Rheingans, and H. Schumannen_US
dc.date.accessioned2015-03-03T12:35:32Z
dc.date.available2015-03-03T12:35:32Z
dc.date.issued2014en_US
dc.description.abstractScatterplot matrices or SPLOMs provide a feasible method of visualizing and representing multi-dimensional data especially for a small number of dimensions. For very high dimensional data, we introduce a novel technique to summarize a SPLOM, as a clustered matrix of glyphs, or a Glyph SPLOM. Each glyph visually encodes a general measure of dependency strength, distance correlation, and a logical dependency class based on the occupancy of the scatterplot quadrants. We present the Glyph SPLOM as a general alternative to the traditional correlation based heatmap and the scatterplot matrix in two examples: demography data from the World Health Organization (WHO), and gene expression data from developmental biology. By using both, dependency class and strength, the Glyph SPLOM illustrates high dimensional data in more detail than a heatmap but with more summarization than a SPLOM. More importantly, the summarization capabilities of Glyph SPLOM allow for the assertion of ''necessity'' causal relationships in the data and the reconstruction of interaction networks in various dynamic systems.en_US
dc.description.seriesinformationComputer Graphics Forumen_US
dc.identifier.doi10.1111/cgf.12386en_US
dc.identifier.issn1467-8659en_US
dc.identifier.urihttps://doi.org/10.1111/cgf.12386en_US
dc.publisherThe Eurographics Association and John Wiley and Sons Ltd.en_US
dc.titleVisualizing Multidimensional Data with Glyph SPLOMsen_US
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33-Issue 3
EuroVis14: Eurographics Conference on Visualization