Data Visualization for Academic Writing

A talk given to the Scientific Writing Workshop graduate class (Astr597), taught by Prof. Dalcanton at the University of Washington

1. Data Visualization for Academic Writing James R. A. Davenport NSF Astronomy & Astrophysics Postdoctoral Fellow, Western Washington University DIRAC Fellow, University of Washington jradavenport 1
2. about me jradavenport
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4. Aurora Borealis - Frederic Edwin Church (1865) jradavenport
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11. Data Visualization or Visual Storytelling jradavenport
12. “The best statistical graph ever drawn…” -Edward Tufte (except it wasn’t drawn for PowerPoint or computers) jradavenport
13. “The%thing%I've%spent%more%2me%on…% is%trying%to%iden2fy%all%those%things%in% peoples%minds%that%serve%as%obstacles% to%them%understanding”% =%Al%Gore% jradavenport
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15. CO 2$ jradavenport
16. CO 2$ Temperature$ jradavenport
17. omg$ CO 2$ Temperature$ omg jradavenport
18. omg$ CO 2$ Temperature$ A great visualization: sells the message, worth 1000 words (or $1.2 Trillion annually) omg jradavenport
19. What I won’t cover: - how to make graphs - types of graphs/plots - graphing languages What I want to cover: - why we make plots - why we publish plots - 5 points to consider jradavenport
20. Why do we make plots? a.k.a. charts, graphs, visualizations, figures, diagrams, maps… jradavenport
21. Why do we make plots? • Development • data exploration • idea generation • debug code • Presentation • talks • posters • papers Each use/format has unique concerns! jradavenport
22. Anscombe’s Quartet All panels have the same - mean (in X and Y) - variance (in X and Y) - linear regression - “r” coefficient Development: Exploratory Data Analysis made popular by Tufte jradavenport
23. Presentation: Talks & Posters jradavenport
24. A Tale of One Plot jradavenport
25. Exploration jradavenport
26. Finished Product jradavenport
27. Match Kepler to Gaia (DR1/TGAS) Select Main Sequence Filter out “junk” Davenport (2017) jradavenport Lecture Slide
28. Poster jradavenport
29. ApJ Webpage jradavenport
30. ApJ Printed jradavenport
31. ApJ Printed B/W jradavenport
32. Your plots (need to) tell the story at a glance! Point #1 paper poster jradavenport
33. One plot does not work for all audiences/needs jradavenport
34. The Dimensions of Art 65,000 pieces of art from the Tate Modern Width Height Width jradavenport
35. The Dimensions of Art 65,000 pieces of art from the Tate Modern jradavenport
36. One plot does not work for all audiences/needs jradavenport
37. One plot does not work for all audiences/needs 1st LIGO detection, Abbott et al. (2016) LIGO MAGAZINE First detection! LIGO Hanford signal 9:50:45 UTC, 14 September 2015 LIGO Livingston signal issue 8 3/2016 LIGO Scientific Collaboration LIGO Magazine, 2016 jradavenport
38. One plot does not work for all audiences/needs Davenport et al. (2016) blog post jradavenport
39. Make multiple versions of a plot! Point #2 & make them available for people to use! jradavenport
40. Your camera doesn’t matter – Ken Rockwell (Photographer) A brief aside…. jradavenport
41. A brief aside…. Your graphing language doesn’t matter – me, just now A short example: jradavenport
42. A brief aside…. Can you tell which is IDL, Python, Excel ? Kepler data from Davenport et al. (2014) jradavenport
43. Don’t tool shame Point #3 jradavenport
44. DESIGN DESIGN DESIGN DESIGN DESIGN jradavenport
45. A handy design acronym: PARC Proximity Alignment Repetition Contrast Gwen Eadie, DIRAC
46. A handy design acronym: PARC Proximity Alignment Repetition Contrast https://mdst485class.wordpress.com/2016/06/16/this-is-c-r-a-p/ Gwen Eadie, DIRAC
47. Keep it Clean !0.025& !0.02& !0.015& !0.01& !0.005& 0& 0.005& 0.01& 0.015& 0.02& 120& 120.5& 121& 121.5& 122& 122.5& 123& 123.5& Series1& Series1' (0.025' (0.02' (0.015' (0.01' (0.005' 0' 0.005' 0.01' 0.015' 120.5377519' 120.7625304' 120.8238336' 120.885137' 120.9464403' 121.0077433' 121.0690467' 121.1303499' 121.1916532' 121.2938252' 121.3551285' 121.4164317' 121.477735' 121.5594728' 121.620776' 121.6820793' 121.7433826' 121.8046857' 121.8864234' 121.9477266' 122.0090298' 122.0703332' 122.1316365' 122.1929397' 122.254243' 122.3155463' 122.3768494' 122.4381527' 122.499456' 122.5607592' 122.6220625' 122.6833658' 122.744669' 122.8059722' 122.8672756' 122.9490132' 123.0103164' 123.0716198' Series1' Default plots from Excel jradavenport
48. Keep it Clean Clean plots from Excel and Matplotlib (Python) jradavenport
49. Avoid Gimmicks jradavenport
50. Avoid Gimmicks examples given for matplotlib… jradavenport
51. 0 50 100 150 200 April May June July Make things comparable jradavenport
52. Be Consistent jradavenport
53. Color in visualizations: best friend, worst enemy jradavenport
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63. Try to use good design principles, especially contrast. Point #4 jradavenport
64. Attention to Details jradavenport
65. “… when data understanding is supported by perceptual rather than cognitive processes” — Enrico Bertini Visualization works … Daniela Huppenkothen, DIRAC
66. Visualization is about managing the viewer’s attention! Daniela Huppenkothen, DIRAC
67. Daniela Huppenkothen, DIRAC
68. human vision is not like photography! Daniela Huppenkothen, DIRAC
69. pre-attentive task https://www.csc2.ncsu.edu/faculty/healey/PP/ Daniela Huppenkothen, DIRAC
70. pre-attentive task https://www.csc2.ncsu.edu/faculty/healey/PP/ Daniela Huppenkothen, DIRAC
71. serial search https://www.csc2.ncsu.edu/faculty/healey/PP/ Daniela Huppenkothen, DIRAC
72. brief vocabulary lesson Semiotics: the study of signs and symbols in communication Everything must have meaning jradavenport
73. time height tall short birth death Everything must have meaning jradavenport
74. time height tall short birth death Everything must have meaning possible meanings: growth over time, growth-spurts, jradavenport
75. time height tall short birth death Everything must have meaning jradavenport
76. time height tall short birth death Everything must have meaning possible meanings: …tall people die? Astronomers are notoriously bad at this! jradavenport
77. Use value-added meaning when possible! Point #5 - Repeat layouts/designs - give colors/shapes meanings - re-use colors consistently jradavenport
78. If they’re thinking about your plot, 
 they’re not thinking about your science Point #5 restated jradavenport
79. If they’re thinking about your plot, 
 they’re not thinking about your science Try to use good design principles, 
 especially contrast. Don’t tool shame Make multiple versions of a plot! Your plots (need to) tell the story at a glance! CONCLUSIONS jradavenport
80. Extra Slides jradavenport
81. Let’s play a game... Art or Data?
83. Data Art 4 hours using Eclipse, traced with IOGraph “14 Billions” (2010) by Tomás Saraceno
84. Art “14 Billions” (2010) by Tomás Saraceno
85. Data 4 hours using Eclipse, traced with IOGraph
87. Ellsworth Kelly Jaz Parkinson Data Art
89. Ellsworth Kelly Data Art James Davenport