EDWARD TUFTE. The Visual Display of Quantitative Information. Envisioning Information. Edward Tufte

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1 EDWARD TUFTE The Leonardo da Vinci of data. -The New York Times The Visual Display of Quantitative Information Envisioning Information Edward Tufte

2 Edward Tufte Background Info Visual Display of Quantitative Info Envisioning Info Audio Video Clip Our Class Edward Tufte is an American statistician, who is known for his data visualization and information graphics. He is also professor of statistics, political science and computer science. He earned a BA and an MS in statistics from Stanford University, and a PhD in political science from Yale. He published a total of five books on the visual display of information and data, some of which are highly reguarded, such as: The Visual Display of Quantitative Information, Envisioning Information and his most recent publication, Beautiful Evidence. Edward Tufte was born in 1942 and grew up in Beverly Hills, California

3 Invention of the sparkline, most commonly used in stock activity. A sparkline is a small intense, simple, word-sized graphic with typographic resolution. Sparklines mean that graphics are no longer cartoonish special occasions with captions and boxes, but rather sparkline graphic can be everywhere a word or number can be: embedded in a sentence, table, headline, map, spreadsheet, graphic. -Tufte, May 27, 2004

4 The small multiples method is one that Tufte uses often to portray multiple graphs of information. At the heart of quantitative reasoning is a single question: Compared to what? Small multiple designs, multivariate and data bountiful, answer directly by visually enforcing comparisons of changes, of the differences among objects, of the scope of alternatives. For a wide range of problems in data presentation, small multiples are the best design solution. -Tufte, Envision Information, page 67

5 Visual Display of Quantitative Information This book discusses statistical graphics, charts and tables, as well as the theory behind the design of information graphics or data graphics. The book goes into a detailed analysis of succesful ways in which to display complex, statistical information with quick, easy and effective design techniques. The first edition was published in The most important contribution so far to the study of the graph. -Journal of American Statisitcal Association

6 Graphical Integrity The representation of numbers, as physically measured on the surface of the graphic itself, should be directly proportional to the numerical quantities represented Clear, detailed, and thorough labeling should be used to defeat graphical distortion and ambiguity. Write out explanations of the data on the graphic itself. Label important events in the data. Graphics must not quote data out of context

7 Data-Ink and Graphical Redesign A large share of ink on a graphic should present data-information, the ink changing as the data change. Data-ink is the non-erasable core of a graphic, the non-redundant ink arranged in response to variation in the numbers represented. How to maximize the data-ink ratio, within reason: 1. Erase non-data-ink, within reason 2. Erase redundant data-ink 3. Revise and edit

8 Chartjunk: Vibrations, Grids, and Ducks Forgo chartjunk, including moiré vibration, the grid and the duck The interior decoration of graphics generates a lot of ink that does not tell the viewer anything new. The purpose of decoration varies to make the graphic appear more scientific and precise, to enliven the display, to give the designer an opportunity to exercise artistic skills. Regardless of its cause, it is all non-dataink or redundant data-ink, that it is often chartjunk.

9 Multifunctioning Graphical Elements Mobilize every graphical element, perhaps several times over, to show the data. The graphical element that actually locates or plots the data is the data measure. The complexity of multifunctioning elements can sometimes turn data graphics into visual puzzles, cryptographical mysteries for the viewer to decode.

10 Aesthetics and Technique in Data Graphical Design

11 Aesthetics and Technique in Data Graphical Design Graphical elegance is often found in simplicity of design and complexity of data. Have a properly chosen format and design, and use words, numbers, and drawings together. Reflect a balance, a proportion, and a sense of relevant scale. Display an accessible complexity of detail, often have a narrative quality, a story to tell about the data. Drawn in a professional manner, with the technical details of production. Avoid content-free decoration, including chartjunk. Data graphics are paragraphs about data and should be treated as such. Greater in length than in height, and labels that read left to right. If the nature of the data suggests the shape of the graphic, follow that suggestion, otherwise, move toward horizontal graphics about 50 percent wider than tall

12 Envisioning Information This book tackles the problem of conveying multiple variable information on a 2-d space. It teaches us ways in which we can communicate more information per unit to make good, clear and smart presentations. This book won 17 awards, and was published in This is one of the best books on graphic design ever published... - Milton Glaser

13 Escaping Flatland

14 Escaping Flatland Introduce multiple dimensions on a two-space surface. Focus more on the point then on the presentation, good design strategies are transparent. Find patterns. Remember that words may not be the most appealing to everyone but symbols are universal and understood by all. More small images in sequence allow more comparison with your eyes and a better understanding. Respect the audiences intelligence. Edward Tufte

15 Micro/Macro Readings

16 Micro/Macro Readings Simpleness of data design and design in general, means better clarity of reading. Micro/macro information: visualization is condensed, slowed, and personalized. Things are made clear by adding detail. Stem and leaf plots, are an example.

17 Layering and Separation Would Tufte approve of this diagram?

18 Layering and Separation No! He would not. However, to make the visual depictions more effective, reduce them down, by using: Visual relationships. Macro annotation, which can help explain micro detail. Use light, color, size, space effectively. Remove the weight, avoid vibration.

19 Color and Information Edward Tufte

20 Color and Information Use color to label, to measure, to represent or imitate reality, and to enliven or decorate. If not chosen correctly, colors can seriously ruin results and confuse people Color spots against a muted field highlight data and weave an overall harmony.

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22 How does this relate to what we re doing? Tufte teaches us that the best way to lay out information in the simplest form for the viewer. He focuses on maximum use of space and resources with the least amount of complexity and confusion. He also teaches us how we can go further than the 2D space we are given, and we can use 3D graphs to make specific information more clear. All our projects have to do with organizing information and portraying it in a simple, effective way so that it is easily understood and well balanced.

23 A cluttered and confusing graph is not an issue of too much information, it is an issue of poor design.

24 Power Corrupts. PowerPoint Corrupts Absolutely. Tufte hates powerpoint, just like Liz! He says that, PowerPoint style routinely disrupts, dominates, and trivializes content. Edward Tufte

25 Works Cited Tufte, Edward R. Envisioning Information. Cheshire, Conn. (P.O. Box 430, Cheshire 06410): Graphics, Print. Tufte, Edward R. The Visual Display of Quantitative Information. Cheshire, Conn. (Box 430, Cheshire 06410): Graphics, Print