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The visualization pipeline describes the (step-wise) process of creating visual representations of data.
- 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.
- Filtering: selection of data portions to be visualized -- usually user-centered.
- 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.
- Rendering: geometric data are transformed to image data.
- [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.