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Visualizing Data (GSA - PIC)

Visualizing Data (GSA - PIC)

Data Visualization: Using Data to Tell a Story
May 24, 2023
Aaron Chafetz and Tim Essam | USAID

Presented to GSA's Performance Improvement Council (PIC) Workshop Series

Aaron

May 24, 2023
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  1. Visualizing Data Using Data to Tell a Story May 24,

    2023 | Virtual | GSA Performance Improvement Council Workshop Series
  2. 2 This presentation was made possible by the support of

    the American people through the United States Agency for International Development (USAID) under the U.S. President's Emergency Plan for AIDS Relief (PEPFAR). The contents in this presentation are the sole responsibility of the authors, and do not necessarily reflect the views of USAID, PEPFAR or the United States Government.
  3. 4 ADMINISTRATOR POWER On A New Vision for Global Development

    Georgetown University | Nov 2021 “At USAID, in addition to a 25 percent target of our assistance going to local partners, today I’m announcing that by the end of the decade, 50 percent of our programming, at least half of every dollar we spend, will need to place local communities in the lead to either co-design a project, set priorities, drive implementation, or evaluate the impact of our programs.” 4
  4. 6 THE ECONOMIST “Change is possible. In corners of USAID,

    greater risk has lead to good results. The President’s Emergency plan for AIDS Relief, a $100bn project reckoned to have saved 25 m lives since 2003, upped the share of funding it hands directly to local groups from 32% in 2018 to 53% in 2021.”
  5. 7

  6. 8 “PEPFAR has prioritized, and made significant progress toward, transitioning

    a substantial majority of our funding by agency to local partners…” PEPFAR 2022 Annual Report to Congress - State Department
  7. 9 Figure H. Funding Local Partners for Sustainable Epidemic Control

    PEPFAR 2022 Annual Report to Congress - State Department
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  15. 18 Figure H. Funding Local Partners for Sustainable Epidemic Control

    PEPFAR 2022 Annual Report to Congress - State Department
  16. 20

  17. SESSION PRESENTERS 21 AARON Chafetz Senior Economist [email protected] TIM Essam

    Senior Data Scientist [email protected] US Agency for International Development Bureau for Global Health | Office of HIV/AIDS | Strategic Information Branch
  18. 23 SESSION AUDIENCE Do you create or consume visuals? What

    is your favorite chart type? Does your agency have guidance on what makes a good visual?
  19. Bottom Line Up Front (BLUF) • Be intentional • Be

    guided by a central question • Be patient, good visualization takes time 25
  20. Learning Objectives 26 • Understand the benefits of visualizing and

    exploring data • Be able to identify problems with a visualization • Discover how text can enhance visualizations • Feel comfortable with data visualization principles
  21. 28 How many 4s are in the visual? Adapted from

    An Economist's Guide to Visualizing Data - Jon Schwabish
  22. 29 8 8 2 7 5 4 6 1 5

    6 4 6 8 2 4 8 8 1 4 5 8 1 8 8 0 4 3 8 4 7 6 7 3 6 0 7 0 1 8 5 How many 4s are in the visual? Adapted from An Economist's Guide to Visualizing Data - Jon Schwabish
  23. 30 8 8 2 7 5 4 6 1 5

    6 4 6 8 2 4 8 8 1 4 5 8 1 8 8 0 4 3 8 4 7 6 7 3 6 0 7 0 1 8 5 How many 4s are in the visual? Adapted from An Economist's Guide to Visualizing Data - Jon Schwabish
  24. 31 8 8 2 7 5 4 6 1 5

    6 4 6 8 2 4 8 8 1 4 5 8 1 8 8 0 4 3 8 4 7 6 7 3 6 0 7 0 1 8 5 These are 4s. What we typically see How many 4s are in the visual? Adapted from An Economist's Guide to Visualizing Data - Jon Schwabish
  25. These choices aren’t random; there are good reasons graphics teams

    do what they do Covid response hampered by population data glitches - FT/Oliver Barnes & John Burn-Murdoch 32
  26. 34 8 8 2 7 5 4 6 1 5

    6 4 6 8 2 4 8 8 1 4 5 8 1 8 8 0 4 3 8 4 7 6 7 3 6 0 7 0 1 8 5 There are 6 fours in the visual below. How many 4s are in the visual? Adapted from An Economist's Guide to Visualizing Data - Jon Schwabish
  27. 35 “Effective graphics avoid taxing working memory, guide attention, and

    respect familiar conventions” -Franconeri et al., 2021
  28. 37 x1 x2 x3 x4 y1 y2 y3 y4 10

    10 10 8 8.04 9.14 7.46 6.58 8 8 8 8 6.95 8.14 6.77 5.76 13 13 13 8 7.58 8.74 12.74 7.71 9 9 9 8 8.81 8.77 7.11 8.84 11 11 11 8 8.33 9.26 7.81 8.47 14 14 14 8 9.96 8.1 8.84 7.04 6 6 6 8 7.24 6.13 6.08 5.25 4 4 4 19 4.26 3.1 5.39 12.5 12 12 12 8 10.84 9.13 8.15 5.56 7 7 7 8 4.82 7.26 6.42 7.91 5 5 5 8 5.68 4.74 5.73 6.89 Average 9.0 9.0 9.0 9.0 7.5 7.5 7.5 7.5 Variance 11.0 11.0 11.0 11.0 4.1 4.1 4.1 4.1 St. Dev. 3.3 3.3 3.3 3.3 2.0 2.0 2.0 2.0
  29. 38 x1 x2 x3 x4 y1 y2 y3 y4 10

    10 10 8 8.04 9.14 7.46 6.58 8 8 8 8 6.95 8.14 6.77 5.76 13 13 13 8 7.58 8.74 12.74 7.71 9 9 9 8 8.81 8.77 7.11 8.84 11 11 11 8 8.33 9.26 7.81 8.47 14 14 14 8 9.96 8.1 8.84 7.04 6 6 6 8 7.24 6.13 6.08 5.25 4 4 4 19 4.26 3.1 5.39 12.5 12 12 12 8 10.84 9.13 8.15 5.56 7 7 7 8 4.82 7.26 6.42 7.91 5 5 5 8 5.68 4.74 5.73 6.89 Average 9.0 9.0 9.0 9.0 7.5 7.5 7.5 7.5 Variance 11.0 11.0 11.0 11.0 4.1 4.1 4.1 4.1 St. Dev. 3.3 3.3 3.3 3.3 2.0 2.0 2.0 2.0
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  32. 44 “Titles and supporting text should convey the message of

    a visualization” -Borkin et al., 2015
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  45. 1 2 66 1 Good data viz is iterative and

    happens behind the scenes
  46. 1 3 2 67 1 Good data viz is iterative

    and happens behind the scenes
  47. 1 4 3 2 68 1 Good data viz is

    iterative and happens behind the scenes
  48. 1 5 4 3 2 69 1 Good data viz

    is iterative and happens behind the scenes
  49. 1 6 5 4 3 2 70 1 Good data

    viz is iterative and happens behind the scenes
  50. “ 72 Do No Harm Guide - J. Schwabish and

    A. Feng | Institute • Use people-first language • Order labels and responses purposefully • Carefully consider colors, icons, and shapes ”
  51. 74 Declutter and Focus: Empirically Evaluating Design Guidelines for Effective

    Data Communication - Ajani et al., 2022 Cluttered
  52. 76 Focused Declutter and Focus: Empirically Evaluating Design Guidelines for

    Effective Data Communication - Ajani et al., 2022
  53. 86 PEPFAR Annual Report to Congress 2022 “PEPFAR has prioritized,

    and made significant progress toward, transitioning a substantial majority of our funding by agency to local partners”
  54. 95 Sorted Colors Clutter Title Labels Axes Four operating units

    achieved USAIDʼs 70% goal Local partner share of budget 70% goal All of these operating units fell short of the 70% of goal.
  55. 96 “PEPFAR has prioritized, and made significant progress toward, transitioning

    a substantial majority of our funding by agency to local partners”
  56. 97 Sorted Colors Clutter Title Labels Axes Four operating units

    achieved USAIDʼs 70% goal Local partner share of budget 70% goal All of these operating units fell short of the 70% of goal. “PEPFAR has prioritized, and made significant progress toward, transitioning a substantial majority of our funding by agency to local partners”
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  61. Data Wrapper 110 OHA Style Guide Do No Harm Guide

    Adobe Color colorbrewer viz-palette Click any box for a link to the resource Color Brewer Color Palettes
  62. 111 Click any box for a link to the resource

    MS Palettes Excel Hacks Excel Data Viz Open Source Tools R & Rstudio Tableau Tutorials
  63. Recall Test • How many 4s were in the visual

    at the beginning? • Pick the three states with the largest measles outbreaks in the 1930s and 1940s? (bonus: what year was the measle vaccine first introduced?) • How many countries / operating units had more than 70% of local partner funding? 112
  64. Recapping our Bottom Line • Be intentional • Be guided

    by a central question • Be patient, good visualization takes time 113 Aaron Chafetz [email protected] Tim Essam [email protected]
  65. 114 Viva Magenta 18-1750 Color of the Year 2023 PANTONE

    COLOR Outfit abcdef ABCDEF 123456 Google Fonts TYPEFACE
  66. 115 Notes and Attributions • Gestalt Principles - https://www.interaction-design.org/literature/topics/gestalt-principles •

    1.3.3 Gestalt rules from Kieran Healy's Data Visualization - https://socviz.co/lookatdata.html • DatasauRus Package - https://cran.r-project.org/web/packages/datasauRus/vignettes/Datasaurus.html • What Questions to Ask When Creating Charts - https://blog.datawrapper.de/better-charts/ • How We’ve Learned Data Viz, and Why You May Want To Do It Differently - https://medium.com/nightingale/how-weve-learned-data-viz-and-why-you-may-want-to-do-it-differently-ec1267bd39b2 • PEPFAR Annual Report to Congress - https://www.state.gov/wp-content/uploads/2022/05/PEPFAR2022.pdf • Graphic design has rules, and they work … - https://twitter.com/MR_RO_BO_T/status/1533517961377587201 • #RotateTheDamnPlot - https://twitter.com/ikashnitsky/status/1521960898440613889?s=20&t=rxuGq6l-O8BMdYDG-zzw9A • bar charts and dot plots and line graphs, oh my! - https://www.storytellingwithdata.com/blog/bar-charts-and-dot-plots-and-line-graphs-oh-my • Examples from: Three Simple Flexible tools for Empowered Data Visualization - https://www.youtube.com/watch?v=W02ZlvulHSY • OHA Style Guide - https://issuu.com/achafetz/docs/oha_styleguide • Better Visualizations - Jon Schwabish • Covid response hampered by population data glitches - Oliver Barnes & John Burn-Murdoch - https://www.ft.com/content/125fbaf8-175a-4e2e-852a-9995ca5176b2 • M. A. Borkin et al., "Beyond Memorability: Visualization Recognition and Recall," in IEEE Transactions on Visualization and Computer Graphics, vol. 22, no. 1, pp. 519-528, 31 Jan. 2016, doi: 10.1109/TVCG.2015.2467732. • Franconeri, S. L., Padilla, L. M., Shah, P., Zacks, J. M., & Hullman, J. (2021). The Science of Visual Data Communication: What Works. Psychological Science in the Public Interest, 22(3), 110–161. • Ajani K, Lee E, Xiong C, Knaflic CN, Kemper W, Franconeri S. Declutter and Focus: Empirically Evaluating Design Guidelines for Effective Data Communication. IEEE Trans Vis Comput Graph. 2022 Oct;28(10):3351-3364. doi: 10.1109/TVCG.2021.3068337. Epub 2022 Sep 1. PMID: 33760737.