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Frameworks for Information Visualization. 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. - PowerPoint PPT Presentation
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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
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
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
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
Goals
Learning a domain Complex Decision making under uncertainty
Analytic Gaps
Rationale Rationale GapGap
Worldview GapWorldview Gap
AnalystAnalystPerceptualPerceptualProcessesProcesses
PerceivingPerceivingUsefulUseful
RelationshipsRelationships
ExplainingExplainingRelationshipsRelationships
RepresentationRepresentationofofDataData
Higher-LevelHigher-LevelAnalyticAnalyticActivityActivity
Robert Amar: InfoVis 2004
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
Analytic Gaps
Rationale Rationale GapGap
Worldview GapWorldview Gap
AnalystAnalystPerceptualPerceptualProcessesProcesses
PerceivingPerceivingUsefulUseful
RelationshipsRelationships
ExplainingExplainingRelationshipsRelationships
RepresentationRepresentationofofDataData
Higher-LevelHigher-LevelAnalyticAnalyticActivityActivity
Robert Amar: InfoVis 2004
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
Analytic Gaps
Rationale Rationale GapGap
Worldview GapWorldview Gap
AnalystAnalystPerceptualPerceptualProcessesProcesses
PerceivingPerceivingUsefulUseful
RelationshipsRelationships
ExplainingExplainingRelationshipsRelationships
RepresentationRepresentationofofDataData
Higher-LevelHigher-LevelAnalyticAnalyticActivityActivity
Robert Amar: InfoVis 2004
Knowledge Tasks
Worldview Tasks1. Domain
Parameters2. Multivariate
Explanation3. Confirm
Hypotheses
Rationale Tasks1. Expose
Uncertainty2. Concretize
Relationships
3. Formulate Cause and Effect
Robert Amar: InfoVis 2004
Facilitate acquisition and transfer of knowledge and/or metadata about domain parameters
Robert Amar: InfoVis 2004
Support the discovery of useful correlative models – especially those involving many variables
Robert Amar: InfoVis 2004
Provide facilities for users to formulate and confirm hypotheses about the data set
Robert Amar: InfoVis 2004
Expose the sources and effects of uncertainty in data measures and aggregations
Robert Amar: InfoVis 2004
Rationale Task 1: Expose Uncertainty
SeeIT (Visible Decisions)Grocery Store Spending Survey Visualization, Augmented Robert Amar: InfoVis
2004
Show the elements comprising relationships and translate into real-world outcomes
Robert Amar: InfoVis 2004
Clarify the source and nature of possible causations
Robert Amar: InfoVis 2004
Knowledge Tasks
Worldview Tasks1. Domain
Parameters2. Multivariate
Explanation3. Confirm
Hypotheses
Rationale Tasks1. Expose
Uncertainty2. Concretize
Relationships
3. Formulate Cause and Effect
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.
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
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.
External Representations
Distributed RepresentationsRule 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]
Interaction
The ability to modify one’s environment to save on internal computation
Liu, InfoVis ‘08
Interaction
[Kirsh and Maglio, 1994]
Distributed Cognition
Interaction is used to coordinate an external and internal representation, making the environment an extension of one’s self
Distributed Cognition (Single)
2314 x 184
Distributed Cognition (Single)
2314 x 184
Distributed Cognition (Group)
Length
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
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
