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Data Visualization Theory

©2014 Karen L. Thompson University of Idaho

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First, a word about terminology.

• Data visualization, information design, infographics, graphics, visuals, illustrations etc. are all terms that are often used in over-lapping ways. No single definition is used consistently by those who create these products.

• Some use the term infographics to mean a subset of data visualization, and others restrict the phrase data visualization to its own category as separate from infographics.

• No matter what they are called, however, all visualizations rest upon theoretical foundations. Two of the leading theorists are Edward Tufte and Nigel Holmes.

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Edward Tufte

Professor Emeritus at Yale University,where he taught courses in statisticalevidence, information design, andinterface design.

He is noted for his writings oninformation design and as a pioneerin the field of data visualization.

http://www.edwardtufte.com/tufte

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His books on analytical design have received more than 40 awards for content and design.

The slides that follow about Tufte’s theory of visual design is from the second chapter of The Visual Display of Quantitative Information.

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Tufte’s ViewTufte coined the termchartjunk to refer to useless,non-informative decorationsand/or pictorial representations ofdata that oversimplify, obscure, ordistort its meaning.

Tufte advocates complex “datarich” illustrations such as thisexample that plots data points inthe damage to the O-ring thatcaused the space shuttle Challengerdisaster.

He also asserts that the highresolution format of the printedpage is preferable because it allows the viewer to workmore closely with the visual andat an “unhurried pace.”

Sometimes decorations can help editorialize about the substance of the graphic. But it's wrong to distort the data measures—the ink locating values of numbers—in order to make an editorial comment or fit a decorative scheme.

Edward Tufte

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Tufte uses this graphic from the statistician FJ Anscombe to demonstrate why it is important to graph data before analyzing it.

The quartet consists of four sets of data that have identical simple statistical properties.

They are, however, very different when graphed. As Tufte points out, the key take-away here is that graphics do not simply represent the data in visual form, they reveal what the data means.

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Tufte also uses an the example of an early data map to explain how visual representations of data reveal meaning useful to solving problems.

In 1854, Dr. John Snow plotted the location of deaths from cholera in London for September in 1854.

By analyzing the scatter of dots (which marked deaths), Snow observed that cholera occurred almost exclusively among those who lived near (and drank from) the Broad Street water pump (circled on this map).

With this information, he ended the epidemic that had killed over 500 people.

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Nigel HolmesNigel Holmes is one of the firstinformation designers to bring datavisualization to a large, mainstreamaudience.

He worked at Time magazine creating“explanation graphics,” visualizationsthat not only presented information butalso explained concepts.

He is often viewed as the anti-Tufte.

The image to the left of this text is anexplanation graphic Holmes createdaimed at helping the viewer understandhow bar codes work.

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Holmes’ View

• Holmes expanded the use of visual elements to tell other types of stories such as pictorially illustrating a concept or even a mundane task.

• His explanation graphics use icons, design elements, and visual metaphors. His graphics are both static and dynamic.

• You can view his work here: http://nigelholmes.com/

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Tufte vs. Holmes?

• Although Tufte and Holmes are often viewed as having opposing views, I think their theories are simply pointing out different data visualization concerns.

• When creating your infographic, keep both of these concerns in mind.

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Tufte

• Tufte is concerned that some visual elements can encourage oversimplification of the data in ways that obscure or distort its meaning.

Sometimes decorations can help editorialize about the substance of the graphic. But it's wrong to distort the data measures—the ink locating values of numbers—in order to make an editorial comment or fit a decorative scheme.

Edward Tufte

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Holmes

• Holmes is concerned with making complex information more easily understood and retained by the audience.

Too much illustration gets in the way of the info; too much reliance on abstract data can leave the reader floundering in a sea of lines and numbers.

Nigel Holmes

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Definition of Infographics

• Information graphics or infographics are graphic visual representations of information, data or knowledge intended to present complex information quickly and clearly.

• They can improve cognition by utilizing graphics to enhance the human visual system’s ability to see patterns and trends. The process of creating infographics can be referred to as data visualization, information design, or information architecture.

from Wikepedia

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Difference between Infographics and Posters

• Posters are designed to be printed. Here are some standard sizes of posters.

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Infographics are designed to be viewed on the web.

Viewers prefer to scroll vertically rather than horizontally, so the format of content-rich infographics is often long and narrow like these examples.

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Not All Infographics Visualize Data

• Many infographics are aimed at explaining a complex topic such as Holmes’ infographic about bar codes.

These explanation infographics often do not contain data or, if they do, the data is not the main focus of the infographic.

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Infographics that are data visualizations, focus on conveying statistical or other numerical data in an interesting way.

For this project, you will create an infographic that visualizes data.

Infographics that Visualize Data

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More examples of infographics that visualize data.

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Infographics are Visual Arguments

• Visual arguments may be aimed at high or low levels of persuasion.

This infographic about human resources is aimed at a low-level of persuasion. Its goal is to convey this non-controversial data in a visually interesting way.

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Visual Arguments and Levels of PersuasionAn infographic explaining the loss of biodiversity in the world is aimed at a High-Level of persuasion.

When working with controversial subjects, it is often best to simply help viewers understand the facts. Infographics that visualize data are useful in supporting narratives aimed at persuading an audience to take action.

An infographic about the calorie counts in fast food would be aimed at aLower Level of persuasion. It’s aim is mostly to help the viewer make better food choices.