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Combining different visualization techniques and applying them on data acquired during ''one'' observation (belonging to the same ''concept'') can yield deeper insights into the data, make finding causal relationships easier, and uncover unforeseen connections. | Combining different visualization techniques and applying them on data acquired during ''one'' observation (belonging to the same ''concept'') can yield deeper insights into the data, make finding causal relationships easier, and uncover unforeseen connections. | ||
Coordinated Multiple Views (CMV): If the different visualization techniques are coordinated (e.g., by [[Linking and Brushing]]). See also the [[CMV2006]] Conference | |||
== References == | == References == | ||
Latest revision as of 11:58, 7 May 2007
[ILOG, 2004]
A multiple view–system uses two or more distinct views to support the investigation of a single conceptual entity.
[Baldonado et al., 2000]
Combining different visualization techniques and applying them on data acquired during one observation (belonging to the same concept) can yield deeper insights into the data, make finding causal relationships easier, and uncover unforeseen connections.
Coordinated Multiple Views (CMV): If the different visualization techniques are coordinated (e.g., by Linking and Brushing). See also the CMV2006 Conference
References
- [Baldonado et al., 2000]: Michelle Q. Wang Baldonado, Allison Woodruff, and Allan Kuchinsky, Guidelines for Using Multiple Views in Information Visualization, in Proc. of Advanced Visual Interfaces (AVI 2000), pages 110-119. ACM Press, 2000.
- [ILOG, 2004] ILOG, Inc., ILOG Discovery Preview, Retrieved at: 2004. http://www2.ilog.com/preview/Discovery/walkthrough/index.html]]