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Andy Kirk's Webinar for Tableau (July 2016)

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These are the slides from the talk given by Andy Kirk (@visualisingdata) on a webinar hosted by Tableau Software on 20th July 2016. The title is 'Bringing Method to the Madness' and concerns a demonstration of a data visualisation design workflow.

Published in: Design

Andy Kirk's Webinar for Tableau (July 2016)

  1. 1. BRINGING METHOD TO THE MADNESS Andy Kirk www.visualisingdata.com @visualisingdata
  2. 2. New book! ‘Data Visualisation: A Handbook for Data Driven Design’
  3. 3. PART A: Foundations Ch 1. Definingdata visualisation Ch 2. Visualisation workflow PART B: The Hidden Thinking Ch 3. Formulating your brief Ch 4. Working with data Ch 5. Establishingeditorialthinking PART C: Developing your Design Solution Ch 6. Data representation Ch 7. Interactivity Ch 8. Annotation Ch 9. Colour Ch 10. Composition PART D: Developing your Capabilities Ch 11. Visualisation literacy Book structure and contents
  4. 4. FINISHSTART Visualisation is a game of decisions DECISIONS
  5. 5. To make the best decisions you need to be familiar with all your options and aware of the things that will influence your choices. GOOD visualisation is about making GOOD decisions THINGS YOU COULD DO THINGS YOU WILL DO
  6. 6. 1. Formulating your brief 2. Working with data 3. Establishing your editorial thinking Workflow: Effective decisions, efficiently made, clearly informed 4. Developing your design solution
  7. 7. 1. Formulating your brief 2. Working with data 3. Establishing your editorial thinking Workflow: Effective decisions, efficiently made, clearly informed TRUSTWORTHY 4. Developing your design solution
  8. 8. Good data visualisations are TRUSTWORTHY Lots of different ways of ‘lying’,intentionally or otherwise
  9. 9. “Communicatingwith numbers is, in many ways, just like communicatingwith words. You make decisions about what to emphasize and what to downplay, and about how to convey a full understanding of the subject at hand.” Christopher Ingraham,The Washington Post Quote from: https://www.washingtonpost.com/news/wonk/wp/2016/04/11/the-dirty-little-secret-that-data-journalists-arent-telling-you/ | Visualisation by FT https://twitter.com/sampoaxelsson/status/742617156060348416 Good data visualisations are TRUSTWORTHY Numbers carry a veneer of authority and objectivity
  10. 10. 1. Formulating your brief 2. Working with data 3. Establishing your editorial thinking Workflow: Effective decisions, efficiently made, clearly informed TRUSTWORTHY ACCESSIBLE 4. Developing your design solution
  11. 11. Visualisations from http://www.wsj.com/articles/who-wins-the-stanley-cup-of-playoff-beards-1431899011 Good data visualisations are ACCESSIBLE Some subjects/analysis/techniques are simple...
  12. 12. Good data visualisations are ACCESSIBLE Some subjects/analysis/techniques are complex... Visualisation by FT https://twitter.com/theboysmithy/status/705323516711804928
  13. 13. 1. Formulating your brief 2. Working with data 3. Establishing your editorial thinking Workflow: Effective decisions, efficiently made, clearly informed TRUSTWORTHY ACCESSIBLE ELEGANT 4. Developing your design solution
  14. 14. Good data visualisations are ELEGANT You noticeelegance morewhen it is missing
  15. 15. Visualisation by Hyperakt http://hyperakt.com/work-detail/338 Good data visualisations are ELEGANT Visual harmony through good editing and holistic thinking
  16. 16. CASE STUDY: ‘FILMOGRAPHICS’ filmographics.visualisingdata.com
  17. 17. Criteria: (1) New project (2) Non-client work (3) Neutral subject
  18. 18. The visualisation design workflow: Stage 1 1. Formulating your brief 2. Working with data 3. Establishing your editorial thinking 4. Developing your design solution
  19. 19. Curiosity #1: What makes a big movie? Looking at different measurements that shape the notion of a movie’s size Curiosity #2: Anatomy of a movie’s costs? Comparing the anatomy of costs for prominent movies through time Curiosity #3: What is the shape of different movie star careers? Comparing the ebb and flow of success/failure CONTEXT: Curiosity, Purpose & Circumstances
  20. 20. CONTEXT: Curiosity, Purpose & Circumstances “What is the pattern of success or failure in the movie careers of a range of notable actors?”
  21. 21. CONTEXT: Curiosity, Purpose & Circumstances “To enlighten movie fans by showing them new insights about the different career patterns of notable actors.”
  22. 22. PEOPLE Stakeholders: Who is ultimate customer? Who are the influencers, interferers? Audience: Informed or layperson? Captivated or indifferent? CONSTRAINTS Pressures: Timescales? Financial? Marketinfluence – emulate/distinguish? Rules: Requirements about layout/size, style (colour,type, logo), technical compatibility? CONSUMPTION Frequency: One-off or replicable? Live or regular? Setting: Rapid or prolonged? Remote or live? DELIVERABLES Size: How much work, how many things? Format: Outputfor (1) print, (2) web, presentation, video, tool, physical? All? RESOURCES Creators: (1) Individual or (2) team? What capabilities? Technical: What software, hardware, infrastructureis available? CONTEXT: Curiosity, Purpose & Circumstances
  23. 23. CONTEXT: Curiosity, Purpose & Circumstances Image from: https://www.kickstarter.com/projects/geniscarreras/philographics-big-ideas-in-simple-shapes 1 2
  24. 24. VISION: Purpose map, Ideas
  25. 25. VISION: Purpose map, Ideas
  26. 26. VISION: Purpose map, Ideas
  27. 27. VISION: Purpose map, Ideas
  28. 28. VISION: Purpose map, Ideas Visualisations from: http://www.gavi.org/data-vis/, http://infobawards.s3.amazonaws.com/SPOTLIGHT-ON-PROFITABILITY_Krisztina-Szucs.png and http://graphics-info.blogspot.co.uk/2013/03/picassos-paintings.html
  29. 29. 1. Formulating your brief 2. Working with data 3. Establishing your editorial thinking 4. Developing your design solution The visualisation design workflow: Stage 2
  30. 30. Actor name Gender Actor DOB Movie title Movie release date (US) Movie genre Movie score/rating (critics and audiences) Movie finances (budget, gross, US domestic and worldwide) Awards ACQUISITION: Shopping list
  31. 31. ACQUISITION: Research (sources)
  32. 32. ACQUISITION: Research (sources)
  33. 33. ACQUISITION: Research (actors) Contemporary – Male (5) Contemporary - Female (5) 2000s - Male (5) 2000s - Female (5) 1990s - Male (5) 1990s - Female (5) 1980s - Male (5) 1980s - Female (5) Veterans - Male (5) Veterans - Female (5) Assorted - Directors (5) Assorted - Comedy (5)
  34. 34. ACQUISITION: Collection method
  35. 35. EXAMINATION: Physical properties
  36. 36. TRANSFORMATION: Cleaning, creating, converting, consolidating
  37. 37. TRANSFORMATION: Cleaning, creating, converting, consolidating
  38. 38. EXPLORATION: Exploratory visual analysis
  39. 39. EXPLORATION: Exploratory visual analysis
  40. 40. EXPLORATION: Exploratory visual analysis
  41. 41. EXPLORATION: Exploratory visual analysis
  42. 42. EXPLORATION: Exploratory visual analysis
  43. 43. 1. Formulating your brief 2. Working with data 3. Establishing your editorial thinking 4. Developing your design solution The visualisation design workflow: Stage 3
  44. 44. Angle (1): How have the quantitativemeasures of success (defined by adjusted global box office takings and criticratings) for each actor changed over time (date of release)? Angle (2): How have the quantitativemeasures of success (defined by adjusted global box office takings and criticratings) for each actor changed over time (age at release)? Angle (3): What is the distribution of movies for a given actor broken down by release year (summarised across 6 interval groups)? EDITORIAL: Defined perspectives(Angle, Framing, Focus) Angle (4): What is the distribution of movies for a given actor broken down by age at release (summarised across 6 interval groups)? Angle (5): What is the distribution ofmovies for a given actor broken down by adjusted worldwide box office takings (summarised across 6 interval groups)? Angle (6): How many Oscar nominationsand awards have each actor achieved?
  45. 45. Framing: The inclusion criteria would be... A hand-picked selection of actors (and some directors) Only movies where credit involved acting/directing/voiceartist roles Only theatrical releases Only movies released from 1965 to the end of 2015 Focus: Emphasise selected movies and linked values in other charts EDITORIAL: Defined perspectives(Angle, Framing, Focus)
  46. 46. 1. Formulating your brief 2. Working with data 3. Establishing your editorial thinking 4. Developing your design solution The visualisation design workflow: Stage 4
  47. 47. DATA REPRESENTATION: Encodings for Angles 1 & 2
  48. 48. DATA REPRESENTATION: Encodings for Angles 3, 4, 5 & 6
  49. 49. DATA REPRESENTATION: Mobile vs. desktop - smallify or simplify?
  50. 50. INTERACTIVITY: Early concept sketch
  51. 51. INTERACTIVITY: Features for ‘Data adjustments’ and ‘Presentation adjustments’
  52. 52. ANNOTATION: Features for ‘Project annotation’ and ‘Chart annotation’
  53. 53. ANNOTATION: Features for ‘Project annotation’ and ‘Chart annotation’
  54. 54. ANNOTATION: Features for ‘Project annotation’ and ‘Chart annotation’
  55. 55. ANNOTATION: Features for ‘Project annotation’ and ‘Chart annotation’
  56. 56. ANNOTATION: Features for ‘Project annotation’ and ‘Chart annotation’
  57. 57. ANNOTATION: Features for ‘Project annotation’ and ‘Chart annotation’
  58. 58. COLOUR: Features of ‘Data legibility’, ‘Editorial salience’ and ‘Functional Harmony’
  59. 59. COLOUR: Features of ‘Data legibility’, ‘Editorial salience’ and ‘Functional Harmony’
  60. 60. COLOUR: Features of ‘Data legibility’, ‘Editorial salience’ and ‘Functional Harmony’
  61. 61. COLOUR: Features of ‘Data legibility’, ‘Editorial salience’ and ‘Functional Harmony’
  62. 62. COLOUR: Features of ‘Data legibility’, ‘Editorial salience’ and ‘Functional Harmony’
  63. 63. COMPOSITION: Features of ‘Project composition’ and ‘Chart composition’
  64. 64. FILMOGRAPHICS INTRODUCTION + more info STATIC GRAPHIC IMAGE FILES (PNG) SIZED AND LOADED IN THIS SPACE, ONE FOR EACH ACTOR 6 CATEGORIES 10 x ACTOR SELETIONS Select Select NEED TITLE, IMAGES FOR CATEGORIES, IMAGES FOR ACTORS IMAGES DEFAULT TO B&W, COLOUR REVEALED ON MOUSEOVER? COMPOSITION: Features of ‘Project composition’ and ‘Chart composition’
  65. 65. COMPOSITION: Features of ‘Project composition’ and ‘Chart composition’
  66. 66. COMPOSITION: Features of ‘Project composition’ and ‘Chart composition’
  67. 67. FINAL WORK: Analysis (The ‘Curiosity Three’)
  68. 68. FINAL WORK: Analysis (The ‘Curiosity Three’)
  69. 69. FINAL WORK: Analysis (The ‘Curiosity Three’)
  70. 70. FINAL WORK: Analysis (Success machines)
  71. 71. FINAL WORK: Analysis (Success machines)
  72. 72. FINAL WORK: Analysis (Extremes)
  73. 73. FINAL WORK: Analysis (Extremes)
  74. 74. FINAL WORK: Analysis (Interesting gaps)
  75. 75. FINAL WORK: Analysis (Interesting gaps)
  76. 76. FINAL WORK: Analysis (Early career success)
  77. 77. FINAL WORK: Analysis (Late career success)
  78. 78. FINAL WORK: Analysis (Give it up, Bobby)
  79. 79. 1. Formulating your brief 2. Working with data 3. Establishing your editorial thinking Workflow: Effective decisions, efficiently made, clearly informed TRUSTWORTHY ACCESSIBLE ELEGANT 4. Developing your design solution
  80. 80. BRINGING METHOD TO THE MADNESS Andy Kirk www.visualisingdata.com @visualisingdata

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