Frameworks for Information Visualization

1. Frameworks for Information Visualization

2. Motivation “The purpose of visualization is insight, not pictures. The main goals of this insight are discovery, decision making, and explanation” Card, Mackinlay, Shneiderman, Reading in information visualization: using vision to think. 1999

3. Overview • A Knowledge Task-Based Framework for Design and Evaluation of Information Visualization • Robert Amar, John Stasko • Distributed Cognition as a Theoretical Framework for Information Visualization • Zhicheng liu, Nancy J. Nersessian, and John T. Stasko

4. Overview • A Knowledge Task-Based Framework for Design and Evaluation of Information Visualization • Robert Amar, John Stasko • Distributed Cognition as a Theoretical Framework for Information Visualization • Zhicheng liu, Nancy J. Nersessian, and John T. Stasko

5. Representational Primacy • Definition: The pursuit of faithful data replication and comprehension • Can be limiting • Focus to much on low-level tasks that do not map well to the true needs of users

6. Goals • Learning a domain • Complex Decision making under uncertainty

7. Analytic Gaps Representation of Data Analyst Perceptual Processes Worldview Gap Perceiving Useful Relationships Rationale Gap Higher-Level Analytic Activity Explaining Relationships Robert Amar: InfoVis 2004

8. The Gap between what is being shown and what actually needs to be shown to draw a straightforward to draw a straightforward representational conclusion for making a decision Worldview Gap: Robert Amar: InfoVis 2004

9. Analytic Gaps Representation of Data Analyst Perceptual Processes Worldview Gap Perceiving Useful Relationships Rationale Gap Higher-Level Analytic Activity Explaining Relationships Robert Amar: InfoVis 2004

10. The gap between perceiving a relationship and actually being able to explain confidence in that relationship and the usefulness of that relationship Rationale gap: Robert Amar: InfoVis 2004

11. Analytic Gaps Representation of Data Analyst Perceptual Processes Worldview Gap Perceiving Useful Relationships Rationale Gap Higher-Level Analytic Activity Explaining Relationships Robert Amar: InfoVis 2004

12. Knowledge Tasks • Worldview Tasks • Domain Parameters • Multivariate Explanation • Confirm Hypotheses • Rationale Tasks • Expose Uncertainty • Concretize Relationships • Formulate Cause and Effect Robert Amar: InfoVis 2004

13. Facilitate acquisition and transfer of knowledge and/or metadata about domain parameters Worldview Task 1:Determine Domain Parameters Robert Amar: InfoVis 2004

14. Support the discovery of useful correlative models – especially those involving many variables Worldview Task 2:Multivariate Explanation Robert Amar: InfoVis 2004

15. Provide facilities for users to formulate and confirm hypotheses about the data set Worldview Task 3:Confirm Hypotheses Robert Amar: InfoVis 2004

16. Expose the sources and effects of uncertainty in data measures and aggregations Rationale Task 1:Expose Uncertainty Robert Amar: InfoVis 2004

17. Rationale Task 1: Expose Uncertainty SeeIT (Visible Decisions) Grocery Store Spending Survey Visualization, Augmented Robert Amar: InfoVis 2004

18. Show the elements comprising relationships and translate into real-world outcomes Rationale Task 2:Concretize Relationships Robert Amar: InfoVis 2004

19. Clarify the source and nature of possible causations Rationale Task 3:Formulate Cause and Effect Robert Amar: InfoVis 2004

20. Knowledge Tasks • Worldview Tasks • Domain Parameters • Multivariate Explanation • Confirm Hypotheses • Rationale Tasks • Expose Uncertainty • Concretize Relationships • Formulate Cause and Effect

21. Using the Tasks • Generate new subtasks for a visualization to support or perform. • Identify possible shortcomings in representation or data. • Discover possible relationships to highlight or use as the basis for a visualization.

22. Overview • A Knowledge Task-Based Framework for Design and Evaluation of Information Visualization • Robert Amar, John Stasko • Distributed Cognition as a Theoretical Framework for Information Visualization • Zhicheng liu, Nancy J. Nersessian, and John T. Stasko

23. Representations • External: distributed cognitive activity is directly observable • Internal: not observable, but can identify where and when they are being processed by observing external representations.

24. External Representations

25. Distributed Representations Rule 1: Only one disk can be transferred at a time Rule 2: a disk can only be transferred to a pole on which it will be the largest Rule 3: only the largest disk on a pole can be transferred to another pole. [Zhang and Normal, 1993]

26. Interaction • The ability to modify one’s environment to save on internal computation Liu, InfoVis ‘08

27. Interaction [Kirsh and Maglio, 1994]

28. Distributed Cognition • Interaction is used to coordinate an external and internal representation, making the environment an extension of one’s self

29. Distributed Cognition (Single) 2314 x 184

30. Distributed Cognition (Single) 2314 x 184

31. Distributed Cognition (Group) Length

32. Evaluation • The Whole is greater then the sum of its parts • In situ observations and ethnographic approaches of cognitive system • Empirical observations used for developing theories and taxonomies

33. Benefits to considering theories • Descriptive: Identify key concepts and provide a conceptual framework • Explanatory: rhetorically support explaining relationships and processes to support education and training • Predictive: make predictions about performance in existing and new situations • Prescriptive: provide guidelines and warnings for design • Generative: facilitate creativity and discovery in future research