The DOI matches its Crossref record; 6 of the 6 references it cites were found in a registry or an index.
A taxonomy of visualization techniques using the data state reference model
Abstract
In previous work, researchers have attempted to construct taxonomies of information visualization techniques by examining the data domains that are compatible with these techniques. This is useful because implementers can quickly identify various techniques that can be applied to their domain of interest. However, these taxonomies do not help the implementers understand how to apply and implement these techniques. The author extends and proposes a new way to taxonomize information visualization techniques by using the Data State Model (E.H. Chi and J.T. Reidl, 1998). In fact, as the taxonomic analysis in the paper will show, many of the techniques share similar operating steps that can easily be reused. The paper shows that the Data State Model not only helps researchers understand the space of design, but also helps implementers understand how information visualization techniques can be applied more broadly.
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Cites
The eyes have it: a task by data type taxonomy for information visualizations
Shneiderman, B. (2002) · Proceedings 1996 IEEE Symposium on Visual Languages · doi:10.1109/vl.1996.545307 · Cited by 4,535
Readings in Information Visualization: Using Vision to Think
Card, S. K., Mackinlay, J. D., & Shneiderman, B. (1999) · Cited by 3,935
The structure of the information visualization design space
Card, S. K., & Mackinlay, J. (2002) · Proceedings of VIZ '97: Visualization Conference, Information Visualization Symposium and Parallel Rendering Symposium · doi:10.1109/infvis.1997.636792 · Cited by 347
An operator interaction framework for visualization systems
Chi, E. H.-H., & Riedl, J. T. (2002) · Proceedings IEEE Symposium on Information Visualization (Cat. No.98TB100258) · doi:10.1109/infvis.1998.729560 · Cited by 192
Self-citationA spreadsheet approach to information visualization
Chi, E. H.-H., Barry, P. J., Riedl, J., et al. (2002) · doi:10.1109/infvis.1997.636761 · Cited by 76
Self-citationA framework for information visualization spreadsheets
Riedl, J., & Huai-hsin, E. (1999) · University of Minnesota eBooks · Cited by 24
Cited by
Low-Level Components of Analytic Activity in Information Visualization
Amar, R., Eagan, J., & Stasko, J. (2006) · Proceedings of the 2005 IEEE Symposium on Information Visualization (INFOVIS'05) · doi:10.1109/infovis.2005.24 · Cited by 512
A Taxonomy of Clutter Reduction for Information Visualisation
Ellis, G., & Dix, A. (2007) · IEEE Transactions on Visualization and Computer Graphics · doi:10.1109/tvcg.2007.70535 · Cited by 375
Visual learning analytics of educational data: A systematic literature review and research agenda
Vieira, C., Parsons, P., & Byrd, V. (2018) · Computers & Education · doi:10.1016/j.compedu.2018.03.018 · Cited by 316
Quality Metrics in High-Dimensional Data Visualization: An Overview and Systematization
Bertini, E., Tatu, A., & Keim, D. (2011) · IEEE Transactions on Visualization and Computer Graphics · doi:10.1109/tvcg.2011.229 · Cited by 257
Accessible Visualization: Design Space, Opportunities, and Challenges
Kim, N. W., Joyner, S. C., Riegelhuth, A., & Kim, Y. (2021) · Computer Graphics Forum · doi:10.1111/cgf.14298 · Cited by 137
Metadata
- Authors
- Chi, E. H.
- Venue
- IEEE Symposium on Information Visualization 2000. INFOVIS 2000. Proceedings
- Publisher
- IEEE Comput. Soc
- Published
- 2002-11-08
- Pages
- 69-75
- OpenAlex
- W2164244016
- Cited by
- 466
- References
- 6
- FWCI
- 11.46
- Type
- conference paper
- Language
- en
- Open access
- closed
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