8-Dec-02 SMD157, Information Visualization 1 L Information Visualization SMD157 Human-Computer Interaction Fall 2002 8-Dec-02 SMD157, Information Visualization 2 L Overview • What is information visualization? • What do we need to do? • Guidelines for design of information seeking applications • The human visual system • Perception plus the Gestalt principles • Coding of data 8-Dec-02 SMD157, Information Visualization 3 L What is Information Visualization?
21
Embed
Information Visualization - Start page at · · 2002-12-08Human-Computer Interaction Fall 2002 8 ... • What is information visualization? • What do we need to do? • Guidelines
This document is posted to help you gain knowledge. Please leave a comment to let me know what you think about it! Share it to your friends and learn new things together.
Transcript
8-Dec-02SMD157, Information
Visualization 1
L
Information Visualization
SMD157Human-Computer Interaction
Fall 2002
8-Dec-02SMD157, Information
Visualization 2
L Overview
• What is information visualization?• What do we need to do? • Guidelines for design of information seeking
applications• The human visual system• Perception plus the Gestalt principles• Coding of data
8-Dec-02SMD157, Information
Visualization 3
L
What is Information Visualization?
8-Dec-02SMD157, Information
Visualization 4
L Information versus Scientific Visualization
8-Dec-02SMD157, Information
Visualization 5
L Why Information Visualization?
• Comprehension• Context• Interaction• Patterns
8-Dec-02SMD157, Information
Visualization 6
L
What Do We Need to Do
Shneiderman’s Abstract Tasks
8-Dec-02SMD157, Information
Visualization 7
L What do we need to do?
• Overview• Zoom• Filter• Details-on-
demand• Relate• History• Extract
8-Dec-02SMD157, Information
Visualization 8
L What do we need to do?
• Overview• Zoom• Filter• Details-on-
demand• Relate• History• Extract
8-Dec-02SMD157, Information
Visualization 9
L What do we need to do?
• Overview• Zoom• Filter• Details-on-
demand• Relate• History• Extract
8-Dec-02SMD157, Information
Visualization 10
L What do we need to do?
• Overview• Zoom• Filter• Details-on-
demand• Relate• History• Extract
8-Dec-02SMD157, Information
Visualization 11
L What do we need to do?
• Overview• Zoom• Filter• Details-on-
demand• Relate• History• Extract
8-Dec-02SMD157, Information
Visualization 12
L What do we need to do?
• Overview• Zoom• Filter• Details-on-
demand• Relate• History• Extract
8-Dec-02SMD157, Information
Visualization 13
L What do we need to do?
• Overview• Zoom• Filter• Details-on-
demand• Relate• History• Extract
8-Dec-02SMD157, Information
Visualization 14
L
Guidelines for Designing Information Seeking Applications
8-Dec-02SMD157, Information
Visualization 15
L Guidelines
• Visualization is not always the best solution.• User tasks must be supported.• Three dimensions are not necessarily better
than two.• Navigation and zooming do not replace filtering.• The graphic method should depend on the data.• Multiple views should be coordinated.• Test your designs with users.
8-Dec-02SMD157, Information
Visualization 16
L Visualization Is Not Always the Best Solution
• Dedicated procedures are:- Faster- Less error prone
• Use visualization when:- User goals are less well-defined.- Good algorithms are lacking- The user needs to explore the data
8-Dec-02SMD157, Information
Visualization 17
L User Tasks Must Be Supported
• Specific support is better than general tools.• Example, comparing two directories
8-Dec-02SMD157, Information
Visualization 18
L Three Dimensions Are Not Necessarily Better Than Two
• Pros:- Extra continuous data dimension- Easier to separate coincident points
• Quantitative (can do arithmetic)- Spatial- Geographical- Time
8-Dec-02SMD157, Information
Visualization 49
L Visual Structures for Data Presentation
• Spatial substrate- Up to three dimensions
• Position encoding techniques- Composition (orthogonal placement, the scatter plot)- Alignment - Folding (SeeSoft)- Recursion (e.g., the desktop metaphor)- Overloading (multiple plots in the same space, tiling)
8-Dec-02SMD157, Information
Visualization 50
L Composition
8-Dec-02SMD157, Information
Visualization 51
L Alignment
8-Dec-02SMD157, Information
Visualization 52
L Folding in SeeSoft
8-Dec-02SMD157, Information
Visualization 53
L Recursion
8-Dec-02SMD157, Information
Visualization 54
L Overloading
8-Dec-02SMD157, Information
Visualization 55
L Visual Structures
• Marks- Points, lines, areas, volumes
• Graphical attributes of the marks- Position (spatial)- Size- Gray Scale- Orientation- Color- Texture- Shape
Extent
Differential
Limited Extent,Differential
8-Dec-02SMD157, Information
Visualization 56
L Effectiveness of Graphical Attributes
Attribute Quantitative Ordinal NominalPosition + + +Size + + +Gray scale o + -Orientation o o +Color o o +Texture o o +Shape - - +
8-Dec-02SMD157, Information
Visualization 57
L Attribute Qualities
• Position- X, Y are strongest- Z interacts with size
• Size- Reasonable differences limit number of categories- Small differences can be perceived if adjacent and
the same shape.
8-Dec-02SMD157, Information
Visualization 58
L Attribute Qualities
• Gray scale- Hard to perceive many discrete steps (about 4 max.)- Interactions with background make absolute value
perception difficult
- Small differences are however relatively easy to detect
8-Dec-02SMD157, Information
Visualization 59
L Attribute Qualities, Color
• Subject to interference- Blue X and box are the same
color
- Blue+red causes focus problems
• People can recognize about 12 distinct colors
• These colors are culturally independent
• Summary- Especially good for categories
XX
whiteblack
redyellow green
green yellow
blue brown
pinkpurpleorangegray
8-Dec-02SMD157, Information
Visualization 60
L Attribute Qualities
• Orientation- Rotation can express
values
- Perception of absolute difference limited to about 45°
+ higher for adjacent symbols
- Perception tends to blend areas of nearly identical adjacent symbols
• Texture- Best adapted to
comparisons- Contrast/Intensity can give
some absolute values- Similar adjacent areas
blend
• Shape- No nature mapping to
value- Useful for nominal data
with many values
8-Dec-02SMD157, Information
Visualization 61
L Questions?
8-Dec-02SMD157, Information
Visualization 62
L References
• Card, S., Mackinlay, J., and Shneiderman, B. eds. Readings in Information Visualization Using Vision to Think, Morgan Kaufmann, 1999, ISBN 1-55860-533-9.
• Wiss, U. & Carr, D. An empirical study of task support in 3D information visualizations, Proceedings IEEE Conference on Information Visualization (IV’99), 392-399. (http://www.ida.liu.se/~davca/postscript/3visStudy.pdf)
• Carr, D., "Guidelines for Designing Information Visualization Applications", Proceedings of ECUE'99, Stockholm, Sweden, December 1-3, 1999. (http://www.ida.liu.se/~davca/postscript/VizGuidelines.pdf)
• Ware & Franck, Evaluating stereo and motion cues for visualizinginformation nets in three dimensions; ACM Trans. Graph. 15, 2, Apr. 1996), 121-140.
• Ware, Information Visualization: Perception for Design; Morgan Kaufmann, 2000, ISBN 1-55860-511-8.