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Visualization
& Storytelling Workshop
Policy communication with charts
Jose Berengueres † Mariam AlMheiri
CIT, UAEU, Al Ai...
Agenda
• Good chart / bad chart
• How to use charts to think++
Schedule
13:30 Intro
13:40 (1) Making sense of data
14:10 break
14:20 (2) Communicating w/ charts
14:50 break
15:00 (3) St...
Schedule
13:30 Intro
13:40 (1) Making sense of data
14:10 break
14:20 (2) Communicating w/ charts
14:50 break
15:00 (3) St...
data > information > kn > wisdom
1 What is data?
data > information > kn > wisdom
many --------------------> one
many ----------------------> scarce ?
--------------------...
data > information > kn > wisdom
many --------------------> one
many ----------------------> scarce ?
--------------------...
data > information > kn > wisdom
1 What is data?
data > HOW ? > wisdom
2 How to arrive to wisdom?
data > HOW ? > wisdom
2 How to arrive to wisdom?
Synthesis process: the dialectic combination of thesis and antithesis int...
3 Exercise! Match the words
data
information
kn
wisdom
NO!
data
information
kn
wisdom
3 Exercise! Match the words
data
information
kn
wisdom
?
3 Exercise! Match the words
Reflection:
Wisdom not just a summary, it
is something more. Cont...
4 Exercise! synthesise (the meaning) of the last 10 slides
synthesis: ______________________________
5 Lets draw it
SHARE YOUR SOLUTIONS
Solution A
Solution B
wisdom
info
data
A vs B
wisdom
info
data
6 Exercise! Visualize the following Gender statistic
Of all the 23,859 respondents
of the 2018 kaggle data science survey ...
Solutions
Solutions
pie chart ?
bar chart ?
stack bar ?
vertical vs. horizontal?
isomeasure?
personas?
Solutions
Solutions
Solutions
Solutions
Solutions
Solutions
7 Exercise! Visualize this
A goal of gender parity has been set. How would you visualize it?
Solutions
Solutions
Solutions
8 Bezos vs. Musk: Chart war
Flashback!
Synthesis process: the dialectic combination of thesis and antithesis into a
higher stage of truth (is this sam...
9 Execisie! is this data, information or knowledge?
https://www.kaggle.com/paultimothymooney/2018-kaggle-machine-learning-...
10 Execisie! Summarizing vs. mk meaning – #HMW make more meaning?
Solutions
https://www.kaggle.com/harriken/storytelling-the-2018-kaggle-survey#cohorts
11 Execisie! Salary distribution of data scientists...
#HMW make more meaning?
https://www.kaggle.com/headsortails/what-we...
How to use gravity to convey power?
< -- ? -- >
Solutions
https://www.kaggle.com/harriken/storytelling-the-2018-kaggle-survey#cohorts
Solutions
https://www.kaggle.com/harriken/storytelling-the-2018-kaggle-survey#cohorts
Solutions
https://www.kaggle.com/harriken/storytelling-the-2018-kaggle-survey#cohorts
Solutions
https://www.kaggle.com/harriken/storytelling-the-2018-kaggle-survey#cohorts
12 Data scientist by country
#HMW more meaning?
hint!
Solutions
hint!
Solutions
Recap part 1
Schedule
13:30 Intro
13:40 (1) Making sense of data
14:10 break
14:20 (2) Communicating w/ charts
14:50 break
15:00 (3) St...
12 Cultural locales
• color meaning by country
• color awarenes by gender
• color awarenss by profession
• sexism awarenes...
13 Storytelling patterns
Patterns of succesful storytelling
• A/B (testing, advertising)
• What is... What could be (duart...
14 Storytelling patterns in charts: symbolic charts
1. Winners
2. Visualizing ALL OR NOTHING relationships
3. Expressing E...
15 Most popular viz libs HMW make meaning?
hint!
Solutions
16 Visualizing ALL OR NOTHING relationships.
Exercise! HMW viz this?
Solutions
17 Expressing enormity. Exercise! How would you express the follwowing..
• # of chart in the universe 102,023,342,012
• # ...
Expressing enormity
Solutions
Expressing enormity
Expressing enormity
18 Gender distribution in data scientist. HMW empathise this chart?
Solutions
19 Age bias in arrests in USA. Exercise! HMW empathise this chart?
https://www.kaggle.com/harriken/police-dogs-and-grey-ha...
Solutions
19 Gender & Violence in in arrests in USA. Exercise! HMW empathise this
chart?
https://www.kaggle.com/harriken/police-dogs...
Solutions
20 Log vs. Volumetric charts. Exercise! HMW viz this?
$ bn
All 83000
Stocks 66000
Physical 31000
Gold 8200
USD 1500
Apple ...
20 Log vs. Volumetric charts
Schedule
13:30 Intro
13:40 (1) Making sense of data
14:10 break
14:20 (2) Communicating w/ charts
14:50 break
15:00 (3) St...
Wardley Maps – atool
to map strategy for
visual ppl
thank you
[1] https://www.aauw.org/research/solving-the-equation/
[2] https://www.theverge.com/2018/11/2/18057716/google-walkout-20-...
#Dgo2019 Conference workshop A3 - viza
#Dgo2019 Conference workshop A3 - viza
#Dgo2019 Conference workshop A3 - viza
#Dgo2019 Conference workshop A3 - viza
#Dgo2019 Conference workshop A3 - viza
#Dgo2019 Conference workshop A3 - viza
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#Dgo2019 Conference workshop A3 - viza

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Visualization 
& Storytelling Workshop
Policy communication with charts - presentation by Jose Berengueres † Mariam AlMheiri
CIT, UAEU, Al Ain, AD, UAEU, CIT
CHSS, UAEU, Al Ain, AD, UAEU
MBRS Dubai Jun 18th 2019 – d.go.2019

Veröffentlicht in: Leadership & Management

#Dgo2019 Conference workshop A3 - viza

  1. 1. Visualization & Storytelling Workshop Policy communication with charts Jose Berengueres † Mariam AlMheiri CIT, UAEU, Al Ain, AD, UAEU, CIT CHSS, UAEU, Al Ain, AD, UAEU MBRS Dubai Jun 18th 2019 – d.go.2019 http://dgsoc.org/dgo-2019/
  2. 2. Agenda • Good chart / bad chart • How to use charts to think++
  3. 3. Schedule 13:30 Intro 13:40 (1) Making sense of data 14:10 break 14:20 (2) Communicating w/ charts 14:50 break 15:00 (3) Strategy Mapping
  4. 4. Schedule 13:30 Intro 13:40 (1) Making sense of data 14:10 break 14:20 (2) Communicating w/ charts 14:50 break 15:00 (3) Strategy Mapping
  5. 5. data > information > kn > wisdom 1 What is data?
  6. 6. data > information > kn > wisdom many --------------------> one many ----------------------> scarce ? -----------------------------> value arrow ? 1 What is data?
  7. 7. data > information > kn > wisdom many --------------------> one many ----------------------> scarce ? -----------------------------> value? 1 What is data?
  8. 8. data > information > kn > wisdom 1 What is data?
  9. 9. data > HOW ? > wisdom 2 How to arrive to wisdom?
  10. 10. data > HOW ? > wisdom 2 How to arrive to wisdom? Synthesis process: the dialectic combination of thesis and antithesis into a higher stage of truth
  11. 11. 3 Exercise! Match the words data information kn wisdom NO!
  12. 12. data information kn wisdom 3 Exercise! Match the words
  13. 13. data information kn wisdom ? 3 Exercise! Match the words Reflection: Wisdom not just a summary, it is something more. Context? how to?
  14. 14. 4 Exercise! synthesise (the meaning) of the last 10 slides synthesis: ______________________________
  15. 15. 5 Lets draw it
  16. 16. SHARE YOUR SOLUTIONS
  17. 17. Solution A
  18. 18. Solution B wisdom info data
  19. 19. A vs B wisdom info data
  20. 20. 6 Exercise! Visualize the following Gender statistic Of all the 23,859 respondents of the 2018 kaggle data science survey 4,513 said they were female.
  21. 21. Solutions
  22. 22. Solutions pie chart ? bar chart ? stack bar ? vertical vs. horizontal? isomeasure? personas?
  23. 23. Solutions
  24. 24. Solutions
  25. 25. Solutions
  26. 26. Solutions
  27. 27. Solutions
  28. 28. Solutions
  29. 29. 7 Exercise! Visualize this A goal of gender parity has been set. How would you visualize it?
  30. 30. Solutions
  31. 31. Solutions
  32. 32. Solutions
  33. 33. 8 Bezos vs. Musk: Chart war
  34. 34. Flashback! Synthesis process: the dialectic combination of thesis and antithesis into a higher stage of truth (is this same as adding context?)
  35. 35. 9 Execisie! is this data, information or knowledge? https://www.kaggle.com/paultimothymooney/2018-kaggle-machine-learning-data-science-survey
  36. 36. 10 Execisie! Summarizing vs. mk meaning – #HMW make more meaning?
  37. 37. Solutions https://www.kaggle.com/harriken/storytelling-the-2018-kaggle-survey#cohorts
  38. 38. 11 Execisie! Salary distribution of data scientists... #HMW make more meaning? https://www.kaggle.com/headsortails/what-we-do-in-the- kernels-a-kaggle-survey-story/report
  39. 39. How to use gravity to convey power? < -- ? -- >
  40. 40. Solutions https://www.kaggle.com/harriken/storytelling-the-2018-kaggle-survey#cohorts
  41. 41. Solutions https://www.kaggle.com/harriken/storytelling-the-2018-kaggle-survey#cohorts
  42. 42. Solutions https://www.kaggle.com/harriken/storytelling-the-2018-kaggle-survey#cohorts
  43. 43. Solutions https://www.kaggle.com/harriken/storytelling-the-2018-kaggle-survey#cohorts
  44. 44. 12 Data scientist by country #HMW more meaning?
  45. 45. hint!
  46. 46. Solutions
  47. 47. hint!
  48. 48. Solutions
  49. 49. Recap part 1
  50. 50. Schedule 13:30 Intro 13:40 (1) Making sense of data 14:10 break 14:20 (2) Communicating w/ charts 14:50 break 15:00 (3) Strategy Mapping
  51. 51. 12 Cultural locales • color meaning by country • color awarenes by gender • color awarenss by profession • sexism awareness by country • Right to left languages
  52. 52. 13 Storytelling patterns Patterns of succesful storytelling • A/B (testing, advertising) • What is... What could be (duarte) • Aha moment! (Welch) • Heroes journey (duarte)
  53. 53. 14 Storytelling patterns in charts: symbolic charts 1. Winners 2. Visualizing ALL OR NOTHING relationships 3. Expressing Enormity 4. Empathy & Personas 5. Log vs. Volumetric charts
  54. 54. 15 Most popular viz libs HMW make meaning?
  55. 55. hint!
  56. 56. Solutions
  57. 57. 16 Visualizing ALL OR NOTHING relationships. Exercise! HMW viz this?
  58. 58. Solutions
  59. 59. 17 Expressing enormity. Exercise! How would you express the follwowing.. • # of chart in the universe 102,023,342,012 • # of those charts which are great 9,993
  60. 60. Expressing enormity Solutions
  61. 61. Expressing enormity
  62. 62. Expressing enormity
  63. 63. 18 Gender distribution in data scientist. HMW empathise this chart?
  64. 64. Solutions
  65. 65. 19 Age bias in arrests in USA. Exercise! HMW empathise this chart? https://www.kaggle.com/harriken/police-dogs-and-grey-hair-will-save-you-from-jail
  66. 66. Solutions
  67. 67. 19 Gender & Violence in in arrests in USA. Exercise! HMW empathise this chart? https://www.kaggle.com/harriken/police-dogs-and-grey-hair-will-save-you-from-jail
  68. 68. Solutions
  69. 69. 20 Log vs. Volumetric charts. Exercise! HMW viz this? $ bn All 83000 Stocks 66000 Physical 31000 Gold 8200 USD 1500 Apple 730 Amzn 400 Crypto 100 Bill 96 Page 41 BTC 41
  70. 70. 20 Log vs. Volumetric charts
  71. 71. Schedule 13:30 Intro 13:40 (1) Making sense of data 14:10 break 14:20 (2) Communicating w/ charts 14:50 break 15:00 (3) Strategy Mapping
  72. 72. Wardley Maps – atool to map strategy for visual ppl
  73. 73. thank you
  74. 74. [1] https://www.aauw.org/research/solving-the-equation/ [2] https://www.theverge.com/2018/11/2/18057716/google-walkout-20-thousand-employees-ceo-sundar-pichai-meeting [3] https://www.forbes.com/sites/womensmedia/2017/08/03/breaking-down-the-gender-gap-in-data-science/#129d1bb74287 [4] https://www.kaggle.com/paultimothymooney/2018-kaggle-machine-learning-data-science-survey [5] https://en.wikipedia.org/wiki/Generations_in_the_workforce [6] Sinton, E (2011). ‘Baby boomers are very privileged human beings’ https://www.telegraph.co.uk/finance/personalfinance/pensions/8840963/Baby- boomers-are-very-privileged-human-beings.html retrieved October 23, 2013 from www.telegraph.co.uk [7] Ken Blanchard Companies. (2009). Next Generation of workers. http://www.kenblanchard.com/img/pub/Blanchard_Next_Generation_of_Workers.pdf Retrieved October 14, 2013, from kenblanchard.com [8] Adecco Group UK and Ireland. (n.d.). Managing the modern workforce. http://www.adeccogroupuk.co.uk/SiteCollectionDocuments/Adecco-Group- Workplace-Revolution.pdf Retrieved October 13, 2013, from www.Adeccouk.co.uk ref. needed [10] https://en.wikipedia.org/wiki/Affluence_in_the_United_States [11] https://www.epi.org/blog/top-1-0-percent-reaches-highest-wages-ever-up-157-percent-since-1979/ [12] J. Berengueres, Sketch thinking. 2016 [13] https://en.wikipedia.org/wiki/Marimekko#Marimekko_chart [14] ref. needed [15] https://www.kaggle.com/ash316/kaggle-journey-2017-2018 [16] https://en.wikipedia.org/wiki/BRICS [17] https://www.kaggle.com/harriken/brics-growth [18] See primary vs. secondary color in https://material.io/design/color/the-color-system.html#color-theme-creation [19] Dutta, S., Reynoso, R.E., Garanasvili, A., Saxena, K., Lanvin, B., Wunsch-Vincent, S., León, L.R. and Guadagno, F., 2018. THE GLOBAL INNOVATION INDEX 2018: ENERGIZING THE WORLD WITH INNOVATION. GLOBAL INNOVATION INDEX 2018, p.1. [20] CSV file global innovation in https://www.globalinnovationindex.org/analysis-indicator [21] World Bank, https://data.worldbank.org/indicator/SP.POP.TOTL [22] https://en.wikipedia.org/wiki/Kendall_rank_correlation_coefficient [23] https://www.pinterest.com/pin/281615782925970581/?lp=true [24] https://en.wikipedia.org/wiki/Regression_toward_the_mean [25] https://www.kaggle.com/harriken/residuals-fig8b-test [26] https://www.kaggle.com/harriken/police-dogs-and-grey-hair-will-save-you-from-jail References

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