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 Worldview Gap Rationale Gap Representation of Data
Analyst
Perceptual
Processes
Worldview Gap
Perceiving
Useful
Relationships
Worldview Gap: The gap between what is being shown and what actually needs to be shown to draw a straightforward represenational conclusion for making a decision
Rationale Gap: The gap between perceiving a relationship and actually being able to explain confidence in that relationship and the usefulness of that relationship
Rationale Gap
Higher-Level
Analytic
Activity
Explaining
Relationships
Robert Amar: InfoVis 2004

8. Worldview Gap:
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
Robert Amar: InfoVis 2004

9. Analytic Gaps Worldview Gap Rationale Gap Representation of Data
Analyst
Perceptual
Processes
Worldview Gap
Perceiving
Useful
Relationships
Worldview Gap: The gap between what is being shown and what actually needs to be shown to draw a straightforward represenational conclusion for making a decision
Rationale Gap: The gap between perceiving a relationship and actually being able to explain confidence in that relationship and the usefulness of that relationship
Rationale Gap
Higher-Level
Analytic
Activity
Explaining
Relationships
Robert Amar: InfoVis 2004

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

11. Analytic Gaps Worldview Gap Rationale Gap Representation of Data
Analyst
Perceptual
Processes
Worldview Gap
Perceiving
Useful
Relationships
Worldview Gap: The gap between what is being shown and what actually needs to be shown to draw a straightforward represenational conclusion for making a decision
Rationale Gap: The gap between perceiving a relationship and actually being able to explain confidence in that relationship and the usefulness of that relationship
Rationale Gap
Higher-Level
Analytic
Activity
Explaining
Relationships
Robert Amar: InfoVis 2004

12. Knowledge Tasks Worldview Tasks Rationale Tasks Domain Parameters
Multivariate Explanation
Confirm Hypotheses
Rationale Tasks
Expose Uncertainty
Concretize Relationships
Formulate Cause and Effect
Domain Parameters: Facilitate acquisition and transfer of knowledge and/or metadata about domain parameters
- Multivariate Explanation: Support the discovery of useful correlative models – especially those involving many variables
Confirm Hypotheses: Provide facilities for users to formulate and confirm hypotheses about the data set
Expose Uncertainty: Expose the sources and effects of uncertainty in data measures and aggregations
- Concretize Relationships: Show the elements comprising relationships and translate into real-world outcomes
- Formulate Cause and Effect: Clarify the source and nature of possible causations
Robert Amar: InfoVis 2004

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

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

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

16. Rationale Task 1: Expose Uncertainty
Expose the sources and effects of uncertainty in data measures and aggregations
Good to reexplain “rationale” concept
Robert Amar: InfoVis 2004

17. Rationale Task 1: Expose Uncertainty
See Nick’s contest entry (ThemeExplorer?) – explicitly dealing with missing abstracts
Consider augmenting this slide with “improvements”
SeeIT (Visible Decisions)
Grocery Store Spending Survey Visualization, Augmented
Robert Amar: InfoVis 2004

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

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

20. Knowledge Tasks Worldview Tasks Rationale Tasks Domain Parameters
Multivariate Explanation
Confirm Hypotheses
Rationale Tasks
Expose Uncertainty
Concretize Relationships
Formulate Cause and Effect
Domain Parameters: Facilitate acquisition and transfer of knowledge and/or metadata about domain parameters
- Multivariate Explanation: Support the discovery of useful correlative models – especially those involving many variables
Confirm Hypotheses: Provide facilities for users to formulate and confirm hypotheses about the data set
Expose Uncertainty: Expose the sources and effects of uncertainty in data measures and aggregations
- Concretize Relationships: Show the elements comprising relationships and translate into real-world outcomes
- Formulate Cause and Effect: Clarify the source and nature of possible causations

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