A Model-Based Visualization Taxonomy

Frameworks for organizing literature and ideas in visualization are valuable since they allow us to gain a higherlevel understanding of the state of visualization research. Current taxonomies of visualization techniques are problematic because the terminology is vague. We present a new taxonomy based on models of a data set rather than attributes of the data itself. This method addresses several problems with existing classification schemes and generates less ambiguous visualization categories.

[1]  William Schroeder,et al.  The Visualization Toolkit: An Object-Oriented Approach to 3-D Graphics , 1997 .

[2]  Ben Shneiderman,et al.  The eyes have it: a task by data type taxonomy for information visualizations , 1996, Proceedings 1996 IEEE Symposium on Visual Languages.

[3]  Ben Shneiderman,et al.  Readings in information visualization - using vision to think , 1999 .

[4]  Jock D. Mackinlay,et al.  The structure of the information visualization design space , 1997, Proceedings of VIZ '97: Visualization Conference, Information Visualization Symposium and Parallel Rendering Symposium.

[5]  Colin Ware,et al.  Information Visualization: Perception for Design , 2000 .

[6]  Download Book,et al.  Information Visualization in Data Mining and Knowledge Discovery , 2001 .

[7]  Ken Brodlie,et al.  Scientific visualization: techniques and applications , 1992 .

[8]  Ed H. Chi,et al.  A taxonomy of visualization techniques using the data state reference model , 2000, IEEE Symposium on Information Visualization 2000. INFOVIS 2000. Proceedings.

[9]  Daniel A. Keim,et al.  Visual exploration of large data sets , 2001, Commun. ACM.