Task

There are a number of different task taxonomies in InfoVis at different levels of granularity.

Task Taxonomy of Relational Information Displays

by: [Zhang, 1996] based on [Carswell and Wickens, 1988]

There are three major types of display tasks:

• information retrieval
• comparison
• information integration

High-level tasks / purposes / goals of Visualization

Sources: [Schumann and Müller, 2000], [Keim et al., 2006]

• Visual Presentation
• Visual Exploration
• Visual Analysis

On the interplay between task and representation

Thus, although there are no best displays that are efficient for all types of tasks, there is a correct or incorrect mapping between the representation of a display and the structure of a task.

[Zhang, 1996]

When a RID [Relational Information Display] has necessary and sufficient information for a task, the mapping between the display and the task is perfect. For example, length is a good representation for ratio comparison tasks because length is on a ratio scale and ratio comparison tasks require ratio scales.

[Zhang, 1996]

Analytic Gaps and Knowledge Tasks

Source: [Amar and Stasko, 2004]

Analytic Gaps

• The Rationale Gap: No “Black Boxes”

We define the Rationale Gap as the gap between perceiving a relationship and actually being able to explain confidence in that relationship and the usefulness of that relationship.

[Amar and Stasko, 2004]

• The Worldview Gap: Show The Wider Perspective

We define the Worldview Gap as the gap between what is being shown and what actually needs to be shown to draw a straightforward representational conclusion for making a decision.

[Amar and Stasko, 2004]

Knowledge Tasks

• Rationale-Based Tasks
  1. Expose Uncertainty
  2. Concretize Relationships
  3. Formulate Cause And Effect

• Worldview-Based Tasks
  1. Determination Of Domain Parameters
  2. Multivariate Explanation
  3. Confirm Hypotheses

Analytic Task Taxonomy

Source: [Amar et al., 2005]

• Retrieve Value
• Filter
• Compute Derived Value
• Find Extremum
• Sort
• Determine Range
• Characterize Distribution
• Find Anomalies
• Cluster
• Correlate

References

• [Amar and Stasko, 2004] R. Amar and J. Stasko, "A knowledge task-based framework for design and evaluation of information visualizations," in the IEEE Symposium on Information Visualization (INFOVIS'04). IEEE Computer Society, 2004, pp. 143-150. [Online]. Available: http://dx.doi.org/10.1109/INFOVIS.2004.10
• [Amar et al., 2005] R. Amar, J. Eagan, and J. Stasko, "Low-level components of analytic activity in information visualization," in 2005 IEEE Symposium on Information Visualization (INFOVIS'05), 2005, pp. 15+. [Online]. Available: http://doi.ieeecomputersociety.org/10.1109/INFOVIS.2005.24
• [Carswell and Wickens, 1988] Carswell, C. M. & Wickens, C. D. (1988). Comparative graphics: History and applications of perceptual integrality theory and the proximity compatibility hypothesis (TR ARL-88-2/AHEL-88-1). Aviation Research Laboratory, University of Illinois at Urbana-Champaign.
• [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.
• [Schumann and Müller, 2000] Heidrun Schumann and Wolfgang Müller, Visualisierung - Grundlagen und allgemeine Methoden. Springer-Verlag, Berlin, 2000.
• [Zhang, 1996] Zhang, J. 1996. A representational analysis of relational information displays. Int. J. Hum.-Comput. Stud. 45, 1 (Jul. 1996), 59-74. DOI= http://dx.doi.org/10.1006/ijhc.1996.0042