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    • 33-Issue 3
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    Visualizing Multidimensional Data with Glyph SPLOMs

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    Date
    2014
    Author
    Yates, Andrew
    Webb, Allison
    Sharpnack, Michael
    Chamberlin, Helen
    Huang, Kun
    Machiraju, Raghu
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    Abstract
    Scatterplot 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.
    BibTeX
    @article {10.1111:cgf.12386,
    journal = {Computer Graphics Forum},
    title = {{Visualizing Multidimensional Data with Glyph SPLOMs}},
    author = {Yates, Andrew and Webb, Allison and Sharpnack, Michael and Chamberlin, Helen and Huang, Kun and Machiraju, Raghu},
    year = {2014},
    publisher = {The Eurographics Association and John Wiley and Sons Ltd.},
    ISSN = {1467-8659},
    DOI = {10.1111/cgf.12386}
    }
    URI
    http://dx.doi.org/10.1111/cgf.12386
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    • 33-Issue 3
    • EuroVis14: Eurographics Conference on Visualization

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