1. 1 Information Design Scott Matthews Courses: 12-706 / 19-702

2. 12-706 and 73-3592 Admin Issues  Group HW 1 Due Today  I forgot to attach 1 reading (handout)

3. 12-706 and 73-3593 Information Design  What is it? Idea of carefully linking what data you have with what you want to say  “God” of the field: Edward Tufte (.com)  Substance of lecture - Text from his books  The eye can recognize 150 Mbits of information  Perhaps most important: don’t just blindly use built- in graph/graphic tools when you have a significant point to make  a.k.a. Excel and Powerpoint are not friends!  They create simplistic graphs that dumb us down  Your graphics say a lot about your perceived command

4. 12-706 and 73-3594 Meta questions  What question are you trying to answer?  OR what statement are you trying to make?  What is the right medium for doing so?  What visual components are needed to convey your point as clearly as possible?

5. 12-706 and 73-3595 Source: Frees and Miller, “Designing Effective Graphs”, 1997. Note the “click on Excel graph button” step is noticeably absent

6. 12-706 and 73-3596 Strive for “Graphical Excellence” z"consists of complex ideas communicated with clarity, precision, and efficiency zis that which gives to the viewer the greatest number of ideas in the shortest time with the least “ink” in the smallest space zis nearly always multivariate z“requires telling the truth about the data.” zAim for “minimalist approach”

7. 12-706 and 73-3597 Graphics/Viz should: z"show the data zinduce viewer to think about the substance rather than about methodology, graphic design, the technology, etc. zavoid distorting what the data have to say zmake large data sets coherent zencourage the eye to compare different pieces of data zserve a reasonably clear purpose: description, exploration, tabulation, or decoration zbe closely integrated with the statistical and verbal descriptions of a data set."

8. 12-706 and 73-3598 Content Focus z“Above all else show the data." zThe focus should be on the content of the data, not the visualization technique. This leads to design transparency. zThe success of a visualization is based on deep knowledge and care about the substance, and the quality, relevance and integrity of the content zAssume that the viewer is just as smart as you and cares just as much zNever ‘dumb-down’ a visualization.

9. 12-706 and 73-3599 Integrity - Misleading visualizations are common zTo help limit unintentional visualization lies: y“Representation of numbers, as physically measured on the surface of the graphic, should be directly proportional to the numerical quantities represented yClear, detailed, and thorough labeling should be used to defeat graphical distortion and ambiguity yWrite out explanations of the data on the graphic itself. Label important events in the data if needed yShow data variation, not design variation yThe number of information-carrying (variable) dimensions depicted should not exceed the number of dimensions in the data yGraphics must not quote data out of context

10. 12-706 and 73-35910 “Lie Factor” zLie-factor = size-of-effect-shown-in- visualization / size-of-effect-in-data

11. 12-706 and 73-35911 Design Guidelines zVisualizations "are paragraphs about data and should be treated as such." Words, pictures, and numbers are all part of the information to be visualized, not separate entities y"have a properly chosen format and design yuse words, numbers, and drawing together yreflect balance, proportion, sense of relevant scale yoften have a narrative quality, a story to tell about data yavoid content-free decoration, including “chartjunk” (miscellaneous graphics that have nothing to do with the data)

12. 12-706 and 73-35912 Summary  You should look at and understand the data first, THEN plan out what you want your visual to “say”  And THEN choose how to make the visual  Choose: table or graph?  Fight the urge to have Excel graph it for you to identify important trends / points

13. 12-706 and 73-35913 Graphs  Best when message is in “shape” of data - e.g., increasing trend, pattern, outliers  Every element you show should be the result of choices you make: e.g., axes, labels, units (and digits), titles, colors, shading.  3-D graphs rarely useful  Avoid pie charts (we don’t “get” angles well)  Fight the defaults - e.g., grey backgrounds!  If you will paste into a report, do not put a title on the chart (put the title in the report)  Given all this, why do people use Excel?

14. 12-706 and 73-35914 Source: Frees and Miller

15. 12-706 and 73-35915 Tables  Nicely formatted table usually beats graph  Best for:  looking up and/or comparing individual values  Showing precise values (e.g., digits)  Format them so that you are drawn to them  Select digits (units) carefully  Try to sort via a numeric column  Add bars to separate items if needed

16. 12-706 and 73-35916 Source: Frees and Miller

17. 12-706 and 73-35917 Examples, and what’s wrong?  Think of Tufte’s “rules” above. Specify.  Hint: think about “message to convey” and how.

18. 12-706 and 73-35918 Source: NY Times, Aug 9, 1978, p. D-2 Fuel Economy Standards for Autos Set by Congress and Supplemented by the Transportation Department. In miles per gallon.

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25. 12-706 and 73-35925 What’s wrong? What could we do better?

26. 12-706 and 73-35926 Sorted by 5-yr Formatted nicer (big small) Source:http://edwardtufte.com

27. 12-706 and 73-35927 Consistent scale in this case Causes lots of crossover and Clutter.

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29. 12-706 and 73-35929 Labels on both sides!

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31. 12-706 and 73-35931 How far we’ve come!

32. 12-706 and 73-35932 Sources  E. Tufte, “The Visual Design of Quantitative Information”, Graphics Press, 2001.  Stephen Few, various, www.perceptualedge.com