Difference between revisions of "Visualization Pipeline"

From InfoVis:Wiki
Jump to navigation Jump to search
m (Reverted edit of 200.238.102.162, changed back to last version by Iwolf)
Line 11: Line 11:
 
*[Card et al., 1999] Card, S. K., Mackinlay, J. D., and Shneiderman, B., editors. Readings in Information Visualization: Using Vision to Think. Morgan Kaufmann, San Francisco. 1999.
 
*[Card et al., 1999] Card, S. K., Mackinlay, J. D., and Shneiderman, B., editors. Readings in Information Visualization: Using Vision to Think. Morgan Kaufmann, San Francisco. 1999.
 
*[Chi, 2000] Chi, E. H. A Taxonomy of Visualization Techniques using the Data State Reference Model. In Proceedings of IEEE Symposium on Information Visualization (InfoVis’00), pages 69–75. IEEE Computer Society Press. 2000.
 
*[Chi, 2000] Chi, E. H. A Taxonomy of Visualization Techniques using the Data State Reference Model. In Proceedings of IEEE Symposium on Information Visualization (InfoVis’00), pages 69–75. IEEE Computer Society Press. 2000.
*[dos Santos and Brodlie, 2004] dos Santos, S. and Brodlie, K. Gaining understanding of multivariate and multidimensional data through visualization. ''Computers
+
*[dos Santos and Brodlie, 2004] dos Santos, S. and Brodlie, K. Gaining understanding of multivariate and multidimensional data through visualization. ''Computers & Graphics'', 28(3):311–325. 2004.
 +
*[Haber and McNabb, 1990] Haber, R. B. and McNabb, D. A. Visualization idioms: A conceptual model for scientific visualization systems. In Visualization in Scientific Computing, pages 74–93. IEEE Computer Society Press. 1990.
 +
*[Tominski, 2006] Christian Tominski, Event-Based Visualization for User-Centered Visual Analysis, PhD Thesis, Institute for Computer Science, Department of Computer Science and Electrical Engineering, University of Rostock, forthcoming 2006.
 +
 
 +
[[Category:Glossary]]

Revision as of 10:01, 11 April 2007

The visualization pipeline describes the (step-wise) process of creating visual representations of data.

The visualization pipeline describes the process of creating visual representations of data [dos Santos and Brodlie, 2004]

  1. Data Analysis: data are prepared for visualization (e.g., by applying a smoothing filter, interpolating missing values, or correcting erroneous measurements) -- usually computer-centered, little or no user interaction.
  2. Filtering: selection of data portions to be visualized -- usually user-centered.
  3. Mapping: focus data are mapped to geometric primitives (e.g., points, lines) and their attributes (e.g., color, position, size); most critical step for achieving Expressiveness and Effectiveness.
  4. Rendering: geometric data are transformed to image data.

References

  • [Card et al., 1999] Card, S. K., Mackinlay, J. D., and Shneiderman, B., editors. Readings in Information Visualization: Using Vision to Think. Morgan Kaufmann, San Francisco. 1999.
  • [Chi, 2000] Chi, E. H. A Taxonomy of Visualization Techniques using the Data State Reference Model. In Proceedings of IEEE Symposium on Information Visualization (InfoVis’00), pages 69–75. IEEE Computer Society Press. 2000.
  • [dos Santos and Brodlie, 2004] dos Santos, S. and Brodlie, K. Gaining understanding of multivariate and multidimensional data through visualization. Computers & Graphics, 28(3):311–325. 2004.
  • [Haber and McNabb, 1990] Haber, R. B. and McNabb, D. A. Visualization idioms: A conceptual model for scientific visualization systems. In Visualization in Scientific Computing, pages 74–93. IEEE Computer Society Press. 1990.
  • [Tominski, 2006] Christian Tominski, Event-Based Visualization for User-Centered Visual Analysis, PhD Thesis, Institute for Computer Science, Department of Computer Science and Electrical Engineering, University of Rostock, forthcoming 2006.