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![A table is nearly always better than a dumb pie chart;
the only worse design than a pie chart is several of them,
for then the viewer is asked to compare quantities located
in spatial disarray both within and between charts […]
Given their low density and failure to
order numbers along a visual dimension,
pie charts should never be used.
Edward Tufte, "The Visual Display of Quantitative Information”](https://image.slidesharecdn.com/data-design-sxsw-150316103618-conversion-gate01/85/Data-Design-Where-Math-and-Art-Collide-43-320.jpg)
Uploaded byTrina Chiasson
Data Design: Where Math and Art Collide
The document discusses the creation of an open-source ebook on data visualization, written collaboratively by over 80 volunteers. It highlights the challenges faced in creating effective data visualizations, critiques common design flaws, and presents insights on color usage and graphical representation. The ebook, titled 'Data + Design,' aims to bridge the gap between data analysis and artistic design and is being translated into multiple languages.
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Data Design: Where Math and Art Collide
- 1. DATA + DESIGN wheremath and art collide Trina Chiasson, Infoactive | @trinachi | infoactive.co/data-design
- 2. This year, Idid something new. I worked with 80+ volunteer contributors to write a 300-page ebook.
- 4. How do youwrite an open source ebook? It started with a message…
- 5. Hi Trina! Statsdork from Chicago here… Do you have any plans to include tutorials for basic data cleaning and data selection techniques for users who may not have any statistics background? — Dyanna Gregory
- 6. This is whatmost statistics textbooks look like. Most designers say…
- 7.
- 8. HAVE YOU EVERSEEN A BAD INFOGRAPHIC? 24.5%NO 84.5% YES
- 9. Why do somany infographics suck?
- 10. THEORY #1 Graphic Designersare evil. They sacrifice truthful data representation for aesthetic gain.
- 11. THEORY #2 Marketers areevil. They sacrifice truthful data representation for more clicks.
- 12. THEORY #3 Most peoplearen’t evil. Good data visualization is really hard to do.
- 13. Who has skillsin programming, design, and data analysis?
- 14. Not everyone isblessed with the innate ability to make brilliant data visualizations.
- 15. What data collectionlooked like, not too long ago
- 16. What data storagelooked like, not too long ago
- 17. What data collection lookslike today
- 18. 1985: The birthof Excel
- 19. But what dowe do with all of this data?
- 20. The price oflight is less than the cost of darkness. — Arthur C. Nielsen, Market Researcher & Founder of ACNielsen
- 21. Let’s send ourdata to a designer who can make it look pretty.
- 22. But most designers arenot trained in stats
- 23. How about afriendly introduction to data?
- 24. But how doyou write an open source ebook?
- 26. There’s no open sourcebook on how to write an open source book.
- 29. Don’t underestimate the awesomenessof strangers on the internet.* * Especially strangers who volunteer to write books about data in their free time.
- 30. In six months, wewrote and released the English version. Data + Design is now being translated in Chinese, Russian, Spanish, and French.
- 34. Is it truethat dataviz people hate pie charts?
- 35. That’s a complex question. Argumentsagainst pie charts:
- 40.
- 41.
- 43. A table isnearly always better than a dumb pie chart; the only worse design than a pie chart is several of them, for then the viewer is asked to compare quantities located in spatial disarray both within and between charts […] Given their low density and failure to order numbers along a visual dimension, pie charts should never be used. Edward Tufte, "The Visual Display of Quantitative Information”
- 46. Graphical perception: Theory,Experimentation, and Application to the Development of Graphical Models
- 49. Meat Pies & ColorTheory
- 50. What Color Is ThisChart? #TheChart
- 51. Hot Pie ColdPie
- 52.
- 54. Men who cannot readthis chart Men who can read this chart
- 55. So you shoulduse monochromatic color scales, right?
- 56. Monochromatic scales are betterfor continuous data
- 58.
- 60. Red tends tostand out against other colors
- 61. Can you findthe red circle?
- 62.
- 63.
- 64. Finding boundaries incolor vs. shapes Adapted from: Healey, Christopher G., Kellogg S. Booth, and James T. Ennis. “High-Speed Visual Estimation Using Preattentive Processing.” ACM Transactions on Computer-Human Interaction 3.2 (1996): 4.
- 65. So what colors shouldI use?
- 66.
- 67.
- 68.
- 70. Our brains lookfor baselines to compare distances
- 71. But the darkblue line is measured on a vertical scale.
- 72.
- 73.
- 74. At first glance,you might think that the dark blue line decreased in value.
- 76.
- 79. Same data, differentstory.
- 80. How do wemake data more human?
- 81. US unemployment ratefrom 2007-2009
- 82.
- 85. In 2008, theSichuan Earthquake killed over 60,000 people in China.
- 88. “For seven yearsshe lived happily on this earth” - Mother of an earthquake victim
- 89. How will you shareyour data?
- 90. DATA + DESIGN wheremath and art collide Trina Chiasson, Infoactive | @trinachi | infoactive.co/data-design