This document provides an overview of concepts and techniques in data visualization. It discusses the work of Gregory Bateson in information and mind, Jacques Bertin's seven visual variables to represent data, and color use guidelines from Brewer. It also includes examples of TGV transportation networks displayed using visual variables, a dashboard example, theories on pre-attentive visual variables, and techniques for displaying quantity through location from historical figures like Playfair, Minard and Neurath.

1. Data Visualization Concepts
Prepared by:
Paul Kahn – Experience Design Director
February, 2013
Media Lab, Aalto University
Helsinki, Finland

2. Gregory Bateson (1904-1980)
British anthropologist, social scientist, linguist, visual
anthropologist, semiotician and cyberneticist whose work intersected
that of many other fields
Major books:
Steps To An Ecology of the Mind, 1972
Mind and Nature: A Necessary Unity, 1979

3. Information and Mind
All information is communicated as differences
The mind operates with hierarchies and networks to create gestalten.
Hierarchies are nested containers
Networks are links connecting discrete nodes
Information architecture is
the re/shaping of information/differences into hierarchies and networks
we search for and visualize the patterns that connect
The pattern that connects is the pathways for accessing differences

4. Jacques Bertin (1918-2010)
Visual Variables for Quantitative Information
“Matrix theory of graphics,” Information Design Journal,
Vol. 10, No. 1. (2002)
Semiology of graphics: Diagrams, Networks, Maps
(Univ of Wisconsin, 1983; ESRI, 2010)
originally published as Sémiologie graphique (1967)

5. Seven Visual Variables To Represent Data
5

6. 6
Variables of the Image (1-3)
• X/Y Position
• Size: Z value of quantity (area) superimposed on position
• Value: Z value of content (fill) superimposed on position

7. 7
Variables of the Image (Beniot Martin)

8. 8
Differential Variables (4-5 )
• Grain/Pattern: Variation of value within glyph
• Color: hue of glyph content

9. 9
Differential Variables (6-7 )
• Orientation: relative position in relation to XY grid
• Shape: abstract shapes distinguished by outline:
dots, squares, triangles, diamonds, metaphors

10. 10
Les variables visuelles (Beniot Martin)

11. 11
TGV Network
Network map 2011

12. 12
TGV Network
• X/Y Position
• Size: Z value of quantity (area)
• Value: Z value of content (fill)
• Grain/Pattern
• Color
• Orientation
• Shape

13. 13
TGV Network
• X/Y Position
• Size: Z value of quantity (area)
• Value: Z value of content (fill)
• Grain/Pattern
• Color
• Orientation
• Shape

14. 14
TGV Network
TGV Change of service
speed to Marseille
BEFORE

15. 15
TGV Network
TGV Change of service
speed to Marseille
AFTER

16. 16
Color Use Guidelines for Data Representation
Brewer, C. A. 1999. Color Use Guidelines for Data Representation, Proceedings of
the Section on Statistical Graphics, American Statistical Association

17. 17
Online resources
Brewer, C. A. 1999. Color Use Guidelines for Data
Representation, Proceedings of the Section on
Statistical Graphics, American Statistical
Association
http://www.personal.psu.edu/cab38/ColorSch/ASApaper
.html
No more excuses: a list of references to learn how
to use color
http://diuf.unifr.ch/people/bertinie/visuale/2009/0
5/infovis_color_theory_in_few_li.html

18. 18
Dashboard example

19. 19
Dashboard example

20. 20
CogSci Theory (Dan Berlin)
Pre-attentive Visual Variables (1-4)
From Designing Interfaces by Jenifer Tidwell

21. 21
Pre-attentive Visual Variables (5-8)

22. 22
Don’t make me think
Immediate Visual Scan Repeated Visual
Scan
An interaction is intuitive
when the user makes the least effort to grasp the
difference.

23. 23
Steps of Visual Cognition
Preattentive
Perception Cognition
Processing
Perception
• All based on changes in contrast: hue, brightness, and color
palette
• We detect differences, physiologically and psychologically
Pre-attentive Processing
• Processed in under 250 milliseconds (Healey, Booth, and Enns, 1995)
• Parallel (bottom-up) processing
Cognition
• Serial (top-down) processing

24. 24
Elementary Perceptual Tasks
We are good at some tasks,
but not others
• Good at: position, length,
direction
• Bad at: area (of a circle),
volume, saturation
This is why you will see
line or bar graphs to
convey data
• You will never (well, shouldn’t)
see a graph that uses color
saturation to convey data (i.e.
using different shades of
orange)

25. 25
Preattentive Processing
Second step of visual perception
“The perception of a pattern can often
• Sits between perception and cognition
be the basis of a new insight.”
• Processed in under 250 milliseconds
- Colin Ware, Information Visualization
• Understanding without training or cognition
• Serial vs. parallel processing
• Forms objects in the mind’s eye
Preattentive variables
• Proximity, similarity, connectedness, continuity, symmetry, closure, relative size,
figure and ground, intensity, curvature,
line length, color, orientation, brightness, and direction of movement.
• Overlapping variables
• Many theories as to how we deal with these – Feature Integration Theory, for one (2
variables at most)
Variable hierarchy

26. Example: Periodic Table of Elements
Dmitri Mendeleev’s original table (1869)

29. Periodic Table as a metaphor

30. Displaying Quantity in Location
William Playfair (1759-1823): space as a metaphor for quantity

31. 31
Charles Joseph Minard (1781-1870)
Thickness of line
(also known as a
Sankey Diagram)

32. Otto Neurath (1882-1945), Gerd Arntz (1900-1988)
— Isotype: Repeated unit as an expression for quantity

33. Otto Neurath, Modern Man in the Making (1939)

35. Maps & Diagrams | September 2011 | 35

36. US Population density (2000), Read Agnew & Don Moyers,
UNDERSTANDING USA