• DocumentCode
    125359
  • Title

    ScagExplorer: Exploring Scatterplots by Their Scagnostics

  • Author

    Tuan Nhon Dang ; Wilkinson, Leland

  • Author_Institution
    Univ. of Illinois at Chicago, Chicago, IL, USA
  • fYear
    2014
  • fDate
    4-7 March 2014
  • Firstpage
    73
  • Lastpage
    80
  • Abstract
    A scatter plot displays a relation between a pair of variables. Given a set of v variables, there are v(v- 1)/2 pairs of variables, and thus the same number of possible pair wise scatter plots. Therefore for even small sets of variables, the number of scatter plots can be large. Scatter plot matrices (SPLOMs) can easily run out of pixels when presenting high-dimensional data. We introduce a theoretical method and a testbed for assessing whether our method can be used to guide interactive exploration of high-dimensional data. The method is based on nine characterizations of the 2D distributions of orthogonal pair wise projections on a set of points in multidimensional Euclidean space. Working directly with these characterizations, we can locate anomalies for further analysis or search for similar distributions in a large SPLOM with more than a hundred dimensions. Our testbed, ScagExplorer, is developed in order to evaluate the feasibility of handling huge collections of scatter plots.
  • Keywords
    computer graphics; data handling; graph theory; interactive systems; 2D distributions; ScagExplorer; high-dimensional data; interactive exploration; large SPLOM; multidimensional Euclidean space; orthogonal pairwise projections; pairwise scatterplots; scatterplot matrices; theoretical method; variables; Clustering algorithms; Correlation; Data visualization; Educational institutions; Layout; Silicon; Time series analysis; Design MethodologyPattern analysis; High-Dimensional Visual Analytics; Leader algorithm; Scagnostics; Scatterplot matrix; forced-directed layout;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Visualization Symposium (PacificVis), 2014 IEEE Pacific
  • Conference_Location
    Yokohama
  • Type

    conf

  • DOI
    10.1109/PacificVis.2014.42
  • Filename
    6787139