Tufte’s Design Principles

Tufte’s Design Principles

CS 7450 - Information Visualization January 27, 2004

John Stasko

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HW 2 - Minivan Data Vis

• What people did

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Classes of solutions

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Data aggregation, transformation

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Tasks - particular versus types

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Envisioning Information

• Let’s hear your views on the book...

Graphical Excellence

• Principles

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Graphical excellence is the well-designed presentation of interesting data---a matter of substance , of statistics , and of design .

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Graphical excellence consists of complex

ideas communicated with clarity, precision

and efficiency.

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Graphical Excellence

• Principles

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Graphical excellence is that which gives to the viewer the greatest number of ideas in the shortest time with the least ink in the smallest space

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Graphical excellence is nearly always multivariate.

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And graphical excellence requires telling the truth about the data.

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Leveraging Human Capabilities

• Data graphics should complement what humans do well

• Quote from top of Vol.2, page 50

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Summary

• 1. Tell the truth

− Graphical integrity

• 2. Do it effectively with clarity, precision…

− Design aesthetics

Let’s look at each of these

1. Graphical Integrity

• Your graphic should tell the truth about

your data

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Example

2002 2001

2000 1999

1998 500

475

450

Stock market crash?

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Example

2002 2001

2000 1999

1998 500

250

0

Show entire scale

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Example

2000 1990

1980 1970

1960 500

250

0

Show in context

Chart Integrity

• Where’s baseline?

• What’s scale?

• What’s context?

Examples: Vol. 1, page 54 (where’s 0?)

Vol. 1, page 54 (what’s component?) Vol. 1, page 57 (change scale)

Vol. 1, page 61 (change scale) Vol. 1, page 74 (show context)

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Watch Size Coding

• Height/width vs. area vs. volume

Examples: Vol. 1, page 69 (area) Vol. 1, page 62 (volume)

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Measuring Misrepresentation

• Visual attribute value should be directly proportional to data attribute value

Size of effect shown in graphic Size of effect in data Lie factor =

4280 9.4 = 454

p.62

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2. Design Aesthetics

• Set of principles to help guide designers

Design Principles

• Maximize data-ink ratio

Data ink ratio = Data ink

Total ink used in graphic

Examples: Vol. 1, page 94 (good and bad)

Vol. 1, page 30 (NYC weather, 2220 numbers)

= proportion of graphic’s ink devoted to the non-redundant display of data-information

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More...

• Above all else, show the data

• Maximize the data-ink ratio

• Erase non-data-ink

• Erase redundant data-ink

• Revise and edit

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More...

• Maximize data density

data density of graphic = number of entries in data matrix area of data graphic

Quote from bottom of Vol. 1, page 168

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Redesign charts

• Bar chart, scatter plot, box plot (See drawings)

Design Principles

• Avoid chartjunk

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Extraneous visual elements that detract from message

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Great narrative: Vol.2, bottom page 33-34

Examples: Vol. 1, page 108 (shimmering display) Vol. 2, page 34 (diamonds are a girls…)

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Design Principles

• Utilize multifunctioning graphical elements (macro/micro readings)

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Graphical elements that convey data information and a design function

Examples: Vol. 1, page 140-1 (bar charts) Vol. 2, pages 36-7 (city maps)

Vol. 2, page 42-44 (Viet Nam Memorial)

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Design Principles

• Use small multiples

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Repeat visually similar graphical elements nearby rather than spreading far apart

Examples: Vol. 1, pages 170- 174 Consumer Reports

Vol. 2, pages 68-69 (trolley cars &

calligraphy)

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Design Principles

• Show mechanism, process, dynamics, and causality

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Cause and effect are key

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Make graphic exhibit causality

Examples: Vol. 3, pages 38-53 (space shuttle) Vol. 3, page 144 (fall in river)

Design Principles

• Escape flatland

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Data is multivariate

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Doesn’t necessarily mean 3D projection

Examples: Vol. 2, page 12 (Japan guide) Vol. 2, page 24 (Java railroad)

Vol. 3, pages 90-91 (history of music)

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Design Principles

• Utilize layering and separation

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1+1 = 3 or more

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Good or bad

Examples: Vol. 2, page 54 (copier assembly) Vol. 2, pages 61-2 (1+1 = 3)

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Design Principles

• Utilize narratives of space and time

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Tell a story of position and chronology through visual elements

Examples: Vol. 1, page 43 & Vol. 2, page 110 (life of beetle) Vol. 2, pages 102-103 (air flight schedules)

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Design Principles

• Content is king

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Quality, relevance and integrity of the content is fundamental

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What’s the analysis task? Make the visual design reflect that

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Integrate text, chart, graphic, map into a coherent narrative

Graph and Chart Tips

• Avoid separate legends and keys -- Just have that information in the graphic

• Make grids, labeling, etc., very faint so that they recede into background

Examples: Vol. 2, page 54, 63 Vol. 3, page 74

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Using Color Effectively

• “The often scant benefits derived from coloring data indicate that even putting a good color in a good place is a complex matter. Indeed, so difficult and subtle that avoiding catastrophe becomes the first principle in bringing color to

information: Above all, do no harm .”

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Proper Color Use

• To label

• To measure

• To represent or imitate reality

• To enliven or decorate

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Color Examples

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Good

− Vol. 2, page 80 Swiss mtn map

− Vol. 2, page 91 or Vol. 3, page 76 Japan sea map (Bad on Vol. 3, page 77)

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Bad

− Vol. 1, page 153 US rate map Great description

− Vol. 2, page 82 US rate map

− Vol. 2, page 88 Computer screens Great quote

Guides for Enhancing Visual Quality

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Attractive displays of statistical info

− have a properly chosen format and design

− use words, numbers and drawing together

− reflect a balance, a proportion, a sense of relevant scale

− display an accessible complexity of detail

− often have a narrative quality, a story to tell about the data

− are drawn in a professional manner, with the technical details of production done with care

− avoid content-free decoration, including chartjunk

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Information Overload

• Text from top of Vol. 2, page 51

• Clutter and confusion are failures of visual design, not attributes of information.

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Minard graphic

size of army

direction latitude

longitude temperature date

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Graphical Displays Should

• Show the data

• Induce the viewer to think about substance rather than about methodology, graphic design the technology of graphic production, or something else

• Avoid distorting what the data have to say

• Present many numbers in a small space

• Make large data sets coherent

• Encourage the eye to compare different pieces of data

• Reveal the data at several levels of detail, from a broad overview to the fine structure

• Serve a reasonably clear purpose:

description, exploration, tabulation, or decoration

• Be closely integrated with statistical and verbal descriptions of a data set

Upcoming

• Interaction and Dynamic Queries (2 days)

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Reading

• Commercial Systems assignment due in a

week

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Sources Used

E. Tufte, The Visual Display of Quantitative Information

E. Tufte, Envisioning Information E. Tufte, Visual Explanations