Data Visualization

The State of the Art

  • Frits H. Post
  • Gregory M. Nielson
  • Georges-Pierre Bonneau

Table of contents

  1. Front Matter
    Pages i-x
  2. Visualization Algorithms and Techniques

    1. Front Matter
      Pages 1-1
    2. Dirk Bartz, Michael Meißner, Gordon Müller
      Pages 3-18
    3. Gerik Scheuermann, Bernd Hamann, Kenneth I. Joy, Wolfgang Kollmann
      Pages 19-35
    4. Benjamin Vrolijk, Freek Reinders, Frits H. Post
      Pages 37-52
    5. Karsten Fries, Jörg Meyer, Hans Hagen, Bernd Lindemann
      Pages 53-66
    6. Stephan Diehl
      Pages 67-75
    7. Yarden Livnat, Charles Hansen, Christopher R. Johnson
      Pages 77-92
  3. Volume Visualization

    1. Front Matter
      Pages 93-93
    2. Issei Fujishiro, Yuriko Takeshima, Shigeo Takahashi, Yumi Yamaguchi
      Pages 95-108
    3. Thomas Theußl, Torsten Möller, Jiří Hladůvka, M. Eduard Gröller
      Pages 109-124
    4. Roger Crawfis, Jian Huang
      Pages 127-140
    5. Craig M. Wittenbrink, Hans J. Wolters, Mike Goss
      Pages 141-156
    6. Nelson Max, Peter Williams, Claudio Silva
      Pages 157-168
    7. Joerg Meyer, Ragnar Borg, Ikuko Takanashi, Eric B. Lum, Bernd Hamann
      Pages 169-182
  4. Information Visualization

    1. Front Matter
      Pages 183-183
    2. Stephen G. Eick
      Pages 185-199
    3. Jing Yang, Matthew O. Ward, Elke A. Rundensteiner
      Pages 201-212
  5. Multiresolution Methods

    1. Front Matter
      Pages 237-237
    2. Emanuele Danovaro, Leila De Floriani, Paola Magillo, Enrico Puppo
      Pages 239-255
    3. Philip J. Rhodes, R. Daniel Bergeron, Ted M. Sparr
      Pages 257-272
    4. Benjamin Gregorski, Kenneth I. Joy, David E. Sigeti, John Ambrosiano, Gerald Graham, Murray Wolinski et al.
      Pages 273-288
    5. Martin Bertram, Mark A. Duchaineau, Bernd Hamann, Kenneth I. Joy
      Pages 289-300
    6. Balakrishna Nakshatrala, David Thompson, Raghu Machiraju
      Pages 301-313
  6. Modelling Techniques

    1. Front Matter
      Pages 315-315
    2. David Ebert, Penny Rheingans
      Pages 317-331
    3. Adam Huang, Gregory M. Nielson
      Pages 333-343
    4. Min Chen, Andrew S. Winter, David Rodgman, Steve Treavett
      Pages 345-362
    5. Shirley F. Konkle, Patrick J. Moran, Bernd Hamann, Kenneth I. Joy
      Pages 363-375
    6. Robert Mencl, Heinrich Müller
      Pages 377-388
  7. Interaction Techniques and Architectures

    1. Front Matter
      Pages 389-389
    2. Jarke J. van Wijk, Cornelius W. A. M. van Overveld
      Pages 391-406
    3. Alexander Hinneburg, Daniel A. Keim
      Pages 407-421
    4. Andrew J. Hanson, Chi-Wing Fu, Eric A. Wernert
      Pages 423-438
    5. H. Hagen, H. Barthel, A. Ebert, M. Bender
      Pages 439-451
  8. Back Matter
    Pages 453-453

About this book


Data visualization is currently a very active and vital area of research, teaching and development. The term unites the established field of scientific visualization and the more recent field of information visualization. The success of data visualization is due to the soundness of the basic idea behind it: the use of computer-generated images to gain insight and knowledge from data and its inherent patterns and relationships. A second premise is the utilization of the broad bandwidth of the human sensory system in steering and interpreting complex processes, and simulations involving data sets from diverse scientific disciplines and large collections of abstract data from many sources.
These concepts are extremely important and have a profound and widespread impact on the methodology of computational science and engineering, as well as on management and administration. The interplay between various application areas and their specific problem solving visualization techniques is emphasized in this book. Reflecting the heterogeneous structure of Data Visualization, emphasis was placed on these topics:

-Visualization Algorithms and Techniques;
-Volume Visualization;
-Information Visualization;
-Multiresolution Techniques;
-Interactive Data Exploration.

Data Visualization: The State of the Art presents the state of the art in scientific and information visualization techniques by experts in this field. It can serve as an overview for the inquiring scientist, and as a basic foundation for developers. This edited volume contains chapters dedicated to surveys of specific topics, and a great deal of original work not previously published illustrated by examples from a wealth of applications. The book will also provide basic material for teaching the state of the art techniques in data visualization.

Data Visualization: The State of the Art is designed to meet the needs of practitioners and researchers in scientific and information visualization. This book is also suitable as a secondary text for graduate level students in computer science and engineering.


3D Administration DOM algorithms computer computer science data structures modeling optimization rendering simulation topology visualization

Editors and affiliations

  • Frits H. Post
    • 1
  • Gregory M. Nielson
    • 2
  • Georges-Pierre Bonneau
    • 3
  1. 1.Delft University of TechnologyThe Netherlands
  2. 2.Arizona State UniversityUSA
  3. 3.University Grenoble I/GRAVIR/IMAGFrance

Bibliographic information

  • DOI
  • Copyright Information Kluwer Academic Publishers 2003
  • Publisher Name Springer, Boston, MA
  • eBook Packages Springer Book Archive
  • Print ISBN 978-1-4613-5430-7
  • Online ISBN 978-1-4615-1177-9
  • Series Print ISSN 0893-3405
  • Buy this book on publisher's site
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