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
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
Journal title :
IEEE TRANSACTIONS ON VISUALIZATION AND COMPUTER GRAPHICS