• DocumentCode
    1026198
  • Title

    An Information-Theoretic View of Visual Analytics

  • Author

    Chen, Chaomei

  • Author_Institution
    Drexel Univ., Philadelphia
  • Volume
    28
  • Issue
    1
  • fYear
    2008
  • Firstpage
    18
  • Lastpage
    23
  • Abstract
    Visual analytics is an emerging discipline that helps connect dots. It facilitates analytical reasoning and decision making through integrated and highly interactive visualization of complex and dynamic data and situations. Solving mysteries is only part of the game. Visual analytics must augment analyst and decision-maker capabilities to assimilate complex situations and reach informed decisions. In information theory, the information value carried by a message is the difference in information entropy before and after receipt of the message. Information entropy is a macroscopic measure of uncertainty defined on a frequency or probability distribution. The information-theoretical approach attempts to quantify discrepancies of the information content of distributions.
  • Keywords
    data visualisation; decision making; entropy; interactive systems; probability; decision making; information entropy; information-theoretic view; interactive data visualization; macroscopic measure; probability distribution; visual analytical reasoning; Information analysis; Information entropy; Loss measurement; Measurement uncertainty; Microscopy; Probability distribution; Profitability; Q measurement; Visual analytics; Visualization; theory; visual analytics;
  • fLanguage
    English
  • Journal_Title
    Computer Graphics and Applications, IEEE
  • Publisher
    ieee
  • ISSN
    0272-1716
  • Type

    jour

  • DOI
    10.1109/MCG.2008.2
  • Filename
    4418745