• Title of article

    Designing pixel-oriented visualization techniques: theory and applications

  • Author/Authors

    Keim، نويسنده , , D.A.، نويسنده ,

  • Issue Information
    روزنامه با شماره پیاپی سال 2000
  • Pages
    20
  • From page
    59
  • To page
    78
  • Abstract
    Visualization techniques are of increasing importance in exploring and analyzing large amounts of multidimensional information. One important class of visualization techniques which is particularly interesting for visualizing very large multidimensional data sets is the class of pixel-oriented techniques. The basic idea of pixel-oriented visualization techniques is to represent as many data objects as possible on the screen at the same time by mapping each data value to a pixel of the screen and arranging the pixels adequately. A number of different pixel-oriented visualization techniques have been proposed in recent years and it has been shown that the techniques are useful for visual data exploration in a number of different application contexts. In this paper, we discuss a number of issues which are of high importance in developing pixel-oriented visualization techniques. The major goal of this article is to provide a formal basis of pixel-oriented visualization techniques and show that the design decisions in developing them can be seen as solutions of well-defined optimization problems. This is true for the mapping of the data values to colors, the arrangement of pixels inside the subwindows, the shape of the subwindows, and the ordering of the dimension subwindows. The paper also discusses the design issues of special variants of pixel-oriented techniques for visualizing large spatial data sets. The optimization functions for the mentioned design decisions are important for the effectiveness of the resulting visualizations. We show this by evaluating the optimization functions and comparing the results to the visualizations obtained in a number of different application.
  • Keywords
    Information Visualization , visualizing multidimensional and multivariate data , visualizing large data sets , visual dataexploration , visual data mining.
  • Journal title
    IEEE TRANSACTIONS ON VISUALIZATION AND COMPUTER GRAPHICS
  • Serial Year
    2000
  • Journal title
    IEEE TRANSACTIONS ON VISUALIZATION AND COMPUTER GRAPHICS
  • Record number

    401656