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Theory of Data Graphics

Above all else show the data.
Data Ink is the non-erasable core of a graphic, the non-redundant ink arranged in response to variation in the numbers represented.

Data-ink ratio = _______data-ink__________
___________Total ink used to print the graphic

__________=    proportion of a graphic’s ink devoted to the non-redundant display of
____________data-information
__________=    1.0 – proportion of a graphic that can be erased without loss of
____________data-information

• Maximize the data-ink ratio, within reason
• Erase non-data-ink, within reason

Notes from The Visual Display of Quantitative Information by Edward R. Tufte

Sources of Graphical Integrity and Sophistication

Relational graphics are essential to competent statistical analysis since they confront statements about cause and effect with evidence, showing how one variable affects another.
Much of the world these days is observed and assessed quantitatively – and well-designed graphics are far more effective than words in showing such observations.

Notes from The Visual Display of Quantitative Information by Edward R. Tufte

Visual Area and Numerical Measure

Many efforts using areas to show magnitudes make the mistake of varying both dimensions simultaneously in response to changes in one-dimensional data.
The use of two [or three] varying dimensions to show one-dimensional data is a weak and inefficient technique.
Principal: the number of information-carrying [variable] dimensions depicted should not exceed the number of dimensions in the data.
Context is Essential for Graphical Integrity Principal – Graphics must not quote data out of context
It is the special character of numbers that they have magnitude as well as an order; numbers measure quantity. Graphics can display the quantitative size of changes as well as their direction.

Notes from The Visual Display of Quantitative Information by Edward R. Tufte

Design and Data Variation

Deception results from the incorrect extrapolation of visual expectations generated at one place on the graphic to other places.
The confounding of design variation with data variation over the surface of a graphic leads to ambiguity and deception, for the eye may mix up changes in the design with changes in the data.

Design principle – Show data variation, not design variation

Time-series Principal – In time-series displays of money, deflated and standardized units of monetary measurement are nearly always better than nominal units.

Notes from The Visual Display of Quantitative Information by Edward R. Tufte

To Ensure Graphical Integrity

1. The representation of numbers, as physically measured on the surface of the graphic itself, should be directly proportional to the numerical quantities represented.
2. Clear, detailed and thorough labeling should be used to defeat graphical distortion and ambiguity

Lie Factor =    size of effect shown in graphic
__________size of effect in data

Notes from The Visual Display of Quantitative Information by Edward R. Tufte

Principles of Graphical Excellence

• Graphical Excellence is the well-designed presentation of interesting data – a matter of substance, of statistics and of design.
• Graphical excellence consists of complex ideas communicated with clarity, precisions, and efficiency.
• 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.
• Graphical excellence is nearly always multivariate.
• Graphical excellence requires telling the truth about the data.

Notes from The Visual Display of Quantitative Information by Edward R. Tufte

Data Graphics

• Data Graphics visually display measured quantities by means of the combined use of points, lines, a coordinate system, numbers, symbols, words, shading and color.
• Graphics are instruments for reasoning about quantitative information.
• Graphical Excellence is the efficient communication of complex quantitative ideas.
• Graphics ‘reveal’ data
• For analyzing and communicating statistical information, well designed data graphics are usually the simplest and the most powerful method.
• Graphics ‘reveal’ data
• Statistical graphics, just like statistical calculations, are only as good as what goes into them.
• The skills required for the use of abstract, non-representational pictures to show numbers are diverse – the visual-artistic, empirical-statistical, and the mathematical

Notes from The Visual Display of Quantitative Information by Edward R. Tufte

Many Eyes

“Our goal is to “democratize” visualization and to enable a new social kind of data analysis.”

Many Eyes has developed some great data visualization pieces, and are part of the IBM Visual Communications lab.

so_many_a_second

“so_many_a_second is a visualizer that shows mondial statistics on a human scale. Depicting the ongoing stream of events, this application tries to get the user in touch with the emotional actuality of these objective data.>