This document discusses creating effective data visualizations. It summarizes a research paper on graphical perception and methods for analyzing scientific data. The speaker then outlines several tips for designing visualizations, such as never using pie charts, only stacking bars when it tells a story, graphing what you want to convey, and showing the zero point. Levels of recognition from graphical encodings are also presented. Recommended further reading on information visualization is provided.

1. “Graphical Perception and Graphical
Methods for Analyzing Scientific Data”
Or how to create data visualizations that tell a story
Papers We Love Berlin ; June 19th ; Juhis ; @hamatti

3. Hi, I’m Juhis!
Developer Community & Web Dev @ Futurice
Founder of Turku <3 Frontend
Used to build data visualizations at Chartio
@hamatti in Twitter
from Helsinki, !

4. 0.000 5.000
9.961 4.373
9.649 6.841
4.063 9.911
0.245 6.545
2.321 0.778
0.039 4.373
3.757 9.843
0.476 7.129
3.159 0.351
9.222 2.321
3.455 9.755
1.355 1.577
9.990 5.314
3.159 9.649
8.645 8.423
1.813 1.147
7.129 0.476
1.813 8.853
9.524 2.871
4.686 9.990
9.755 3.455
9.649 3.159
0.351 6.841
8.423 1.355
8.853 1.813
6.841 0.351
2.321 9.222
5.937 9.911
7.939 9.045
7.409 0.618
9.911 4.063
0.089 5.937
2.871 9.524
9.755 6.545
8.187 1.147
7.679 9.222
4.373 0.039
0.010 4.686
1.577 1.355
0.039 5.627
10.000 5.000
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5. @hamattiPapers We Love Berlin

6. Read the paper
"Graphical Perception and Graphical Methods
for Analyzing Scientific Data" by William S.
Cleveland and Robert McGill
bit.ly/pwlb-dataviz

7. Input — Output
Quantitative &
categorical data
encode through
position, shape, size,
symbols and color
Graph
decode through
human visual system
Understanding
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8. “A graphical method is successful only if the
decoding is effective. No matter how clever
and how technologically impressive the
encoding, it fails if the decoding process fails.”
Cleveland & McGill, 1985
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9. “A graphical method is successful only if the
decoding is effective. No matter how clever
and how technologically impressive the
encoding, it fails if the decoding process fails.”
Cleveland & McGill, 1985
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10. Levels of recognition
1. Position along a common scale
2. Position on an identical but non-aligned scales
3. Length
4. Angle or slope
5. Area
6. Volume / Density / Saturation
7. Hue
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11. 1. Position along a common scale
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12. 2. Position on an identical but non-aligned scales
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13. 3. Length
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14. #1 Never use pie charts
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15. “Pie charts should
never be used”
Edward Tufte
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16. 4. Angle / Slope & 5. Area
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17. #2 Don’t stack –
unless it tells a story
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20. #3 Graph what you
want to tell
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23. #4 Show the zero
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28. #5 Don’t get fancy
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30. https://www.thedataschool.co.uk/ellen-blackburn/a-simple-way-to-make-a-radar-chart/

31. #5 Don’t get fancy
#1 Never use pie charts
#2 Don’t stack – unless it tells a story
#3 Graph what you want to tell
#4 Show the zero
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32. Extra reading
The Visual Display of Quantitative Data, Edward Tufte
Information Dashboard Design, Stephen Few
Information Graphics, Sandra Rendgen
Cartographies of Time, Daniel Rosenberg
Visualize This, Nathan Yau
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33. @hamatti
https://hamatti.org
https://futurice.com
juhis@futurice.com
Thank you!