Visual Analysis

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Visual analysis aims for supporting the verification or falsification of given hypotheses about a dataset visually. This means that users perform a directed search for information. A high degree of interactivity is required here as well. Since hypotheses are given a priori visual analysis techniques should be able to guide the users during the search process. Visual analysis techniques are often tailored to one certain analysis problem (i.e., a limited set of hypotheses).
For confirmatory analysis, one or more hypotheses about the data serve as a starting point. The process can be described as a goal-oriented examination of these hypotheses. As a result, visualization either confirms these hypotheses or rejects them.
[Keim et al., 2006]

see also: Visual Exploration, Visual Presentation, and Visual Analytics.

Main characteristics:

  • main purpose: confirm/reject hypotheses
  • user has clear question / hypothesis
  • directed
  • automatic methods
  • user is steering / controlling
  • user: confirm


  • [Keim et al., 2006] Keim, D.A.; Mansmann, F. and Schneidewind, J. and Ziegler, H., Challenges in Visual Data Analysis, Proceedings of Information Visualization (IV 2006), IEEE, p. 9-16, 2006.
  • [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.