Data Design: Where Math and Art Collide

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Slides from SXSW 2015 session on the intersection of data and design: http://schedule.sxsw.com/2015/events/event_IAP41090 By Trina Chiasson from https://infoactive.co

Data & Analytics Design Technology

$DATA + DESIGN where math and art collide Trina Chiasson, Infoactive | @trinachi | infoactive.co/data-design$

This year, I did something new.
I worked with 80+ volunteer
contributors to write a
300-page ebook.

How do you write an
open source ebook?
It started with a message…

Hi Trina! Stats dork 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

This is what most statistics textbooks look like.
Most designers say…

HAVE YOU EVER SEEN A BAD INFOGRAPHIC?
24.5%NO
84.5%
YES

THEORY #1
Graphic Designers are evil.
They sacrifice
truthful data representation
for aesthetic gain.

THEORY #2
Marketers are evil.
They sacrifice
truthful data representation
for more clicks.

THEORY #3
Most people aren’t evil.
Good data visualization
is really hard to do.

Who has skills in programming,
design, and data analysis?

Not everyone is blessed with the innate ability
to make brilliant data visualizations.

What data collection looked like,
not too long ago

What data storage looked like,
not too long ago

But what do we do
with all of this data?

The price of light is less
than the cost of darkness.
— Arthur C. Nielsen,
Market Researcher & Founder of ACNielsen

Let’s send our data to a designer
who can make it look pretty.

But most designers
are not trained in stats

How about a friendly
introduction to data?

But how do you write an
open source ebook?

There’s no
open source book
on how to write
an open source book.

Don’t underestimate the
awesomeness of strangers
on the internet.*
* Especially strangers who volunteer to
write books about data in their free time.

In six months,
we wrote and released the
English version.
Data + Design is now being
translated in Chinese, Russian,
Spanish, and French.

Is it true that
dataviz people
hate pie charts?

That’s a complex
question.
Arguments against
pie charts:

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”

Graphical perception: Theory, Experimentation, and Application to the Development of Graphical Models

Men who cannot
read this chart
Men who can read
this chart

So you should use
monochromatic
color scales, right?

Monochromatic scales are
better for continuous data

Red tends to stand out
against other colors

Finding boundaries in color 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.

Our brains look for
baselines to compare
distances

But the dark blue line
is measured on a
vertical scale.

At first glance, you might think that the
dark blue line decreased in value.

http://www.nytimes.com/interactive/2009/11/06/business/economy/unemployment-lines.html?_r=0

In 2008, the Sichuan Earthquake
killed over 60,000 people in China.

“For seven years she lived happily on this earth”
- Mother of an earthquake victim

DATA + DESIGN
where math and art collide
Trina Chiasson, Infoactive | @trinachi | infoactive.co/data-design

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Data Design: Where Math and Art Collide

1. DATA + DESIGN where math and art collide Trina Chiasson, Infoactive | @trinachi | infoactive.co/data-design

2. This year, I did something new. I worked with 80+ volunteer contributors to write a 300-page ebook.

4. How do you write an open source ebook? It started with a message…

5. Hi Trina! Stats dork 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 what most statistics textbooks look like. Most designers say…

7. This isn’t for me

8. HAVE YOU EVER SEEN A BAD INFOGRAPHIC? 24.5%NO 84.5% YES

9. Why do so many infographics suck?

10. THEORY #1 Graphic Designers are evil. They sacrifice truthful data representation for aesthetic gain.

11. THEORY #2 Marketers are evil. They sacrifice truthful data representation for more clicks.

12. THEORY #3 Most people aren’t evil. Good data visualization is really hard to do.

13. Who has skills in programming, design, and data analysis?

14. Not everyone is blessed with the innate ability to make brilliant data visualizations.

15. What data collection looked like, not too long ago

16. What data storage looked like, not too long ago

17. What data collection looks like today

18. 1985: The birth of Excel

19. But what do we do with all of this data?

20. The price of light is less than the cost of darkness. — Arthur C. Nielsen, Market Researcher & Founder of ACNielsen

21. Let’s send our data to a designer who can make it look pretty.

22. But most designers are not trained in stats

23. How about a friendly introduction to data?

24. But how do you write an open source ebook?

25.

26. There’s no open source book on how to write an open source book.

27.

28.

29. Don’t underestimate the awesomeness of strangers on the internet.* * Especially strangers who volunteer to write books about data in their free time.

30. In six months, we wrote and released the English version. Data + Design is now being translated in Chinese, Russian, Spanish, and French.

31.

32.

33.

34. Is it true that dataviz people hate pie charts?

35. That’s a complex question. Arguments against pie charts:

36.

37.

38.

39.

40. 13% 100%

41. 13%

42.

43. 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”

44.

45.

46. Graphical perception: Theory, Experimentation, and Application to the Development of Graphical Models

47.

48.

49. Meat Pies & Color Theory

50. What Color Is This Chart? #TheChart

51. Hot Pie Cold Pie

52. Hot PieCold Pie

53.

54. Men who cannot read this chart Men who can read this chart

55. So you should use monochromatic color scales, right?

56. Monochromatic scales are better for continuous data

57.

58. Be careful with multicolor scales

59.

60. Red tends to stand out against other colors

61. Can you find the red circle?

62. How about now?

63. Which is easier?

64. Finding boundaries in color 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 should I use?

66. It depends, but…

67. BLUE & ORANGE

68. More visual trickery

69.

70. Our brains look for baselines to compare distances

71. But the dark blue line is measured on a vertical scale.

72. Tricky, indeed.

73. Another example…

74. At first glance, you might think that the dark blue line decreased in value.

75.

76. More visual trickery!