Crafting Visual Stories with Data
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Crafting Visual Stories with Data

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Data visualization has enabled us to compress data and express them visually in many interesting new ways. It is often cited that we are trying to tell stories through them. Is that really the......

Data visualization has enabled us to compress data and express them visually in many interesting new ways. It is often cited that we are trying to tell stories through them. Is that really the case? How can we ensure that the audience is able to retain, recall and retell our data-driven stories.

Using examples and videos learning from different storytelling mediums, I walk through why stories are important and what we can learn about how stories work from these mediums. I then detail out a framework built on the See the data | Show the Visual | Tell the Story | Engage the Audience paradigm to convert the data in to a data-visual-story.

This slide deck was used in Bangalore Meetup - Crafting Visual Stories with Data - in March 2014 @ InMobi's Bangalore Office.

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Transcript

  • 1. Crafting Visual Stories with Data
  • 2. How many 5’s can you find? 142536789251364789245369178 419356728495126783149356728 245369178145672893145672938 495126783149356728423698517 359164782145672938451672938 465132978423698517459163782 145762938451672938359164782 431567298459163782431567298
  • 3. Proximity 142 5 367892 5 136478924 5 369178 4193 5 672849 5 1267831493 5 6728 24 5 36917814 5 67289314 5 672938 49 5 1267831493 5 6728423698 5 17 3 5 916478214 5 6729384 5 1672938 46 5 132978423698 5 174 5 9163782 14 5 7629384 5 16729383 5 9164782 431 5 672984 5 9163782431 5 67298
  • 4. Alignment 555 142367892136478924369178 555 419367284912678314936728 555 243691781467289314672938 555 491267831493672842369817 555 391647821467293841672938 555 461329784236981749163782 555 147629384167293839164782 555 431672984916378243167298
  • 5. Repetition 123456789 123456789 123456789 123456789 123456789 123456789 123456789 123456789 123456789 123456789 123456789 123456789 123456789 123456789 123456789 123456789 123456789 123456789 123456789 123456789 123456789 123456789 123456789 123456789
  • 6. Contrast 142536789251364789245369178 419356728495126783149356728 245369178145672893145672938 495126783149356728423698517 359164782145672938451672938 465132978423698517459163782 145762938451672938359164782 431567298459163782431567298
  • 7. Subtraction 142536789251364789245369178 419356728495126783149356728 245369178145672893145672938 495126783149356728423698517 359164782145672938451672938 465132978423698517459163782 145762938451672938359164782 431567298459163782431567298
  • 8. One Frame Counts Source: The Cutting Edge
  • 9. War Stories & Killer Charts
  • 10. Quote I think people have begun to forget how powerful human stories are, exchanging their sense of empathy for a fetishistic fascination with data, networks, patterns, and total information... Really, the data is just part of the story. The human stuff is the main stuff, and the data should enrich it. - Jonathan Harris
  • 11. Content Why Stories?
  • 12. Emotion & Empathy I am blind
  • 13. Emotion & Empathy It is spring & I am blind
  • 14. Speakers’ Corner
  • 15. Rhetoric
  • 16. Joshua Bell Source: Aristotle and Joshua Bell on Persuasion
  • 17. Persuasion
  • 18. logos reason ethos pathos credible emotional | | | Persuasion
  • 19. Data-Story-Visual Data Story Visual Graph Art Tale *
  • 20. analysis SYNTHESIS numbers argument VISUALISE STORY | | | Synthesis -Visualise-Story
  • 21. logic | EMPATHY
  • 22. Data & Stories The focus of stories is on individual people rather than averages, on motives rather than movements, on point of view rather than the view from nowhere, context rather than raw data. Moreover, stories are open-ended and metaphorical rather than determinate and literal.
  • 23. Body Mass Index (BMI) BMI = mass (kg) [ height (m) ]2h m
  • 24. Living on the edge 5’ 1 6’ 5 5’ 7 5’ 5 5’ 3 6’ 3 6’ 1 5’ 11 5’ 9 6’ 7 Obese Over Normal Under 18 25 30 mass (in kg) height (in ft)
  • 25. The Story Mindset In listening to stories we tend to suspend disbelief in order to be entertained, whereas in evaluating statistics we generally have an opposite inclination to suspend belief in order not to be beguiled. - John Allen Paulos
  • 26. Stories are emotional Stories are Stories are memorable impactful | | | Why Stories?
  • 27. Content How do stories work?
  • 28. People tell stories Words Pictures tell stories tell stories | | | Synthesis -Visualise-Story Comics tell stories| Movies tell stories|
  • 29. Dual Coding Aural Visual
  • 30. ˌvɪʒʊəlaɪˈzeɪʃən (noun) Derived from the Latin verb videre, "to look, to see" The act or instance to form a mental image or picture (without an object) Visualization The act or instance to make visible or visual (with an object)
  • 31. Two Little Fishes
  • 32. Transfer of Imagery
  • 33. Teller Story Listener Storytelling Triangle
  • 34. Transfer of Imagery Source: The Visitor - Learning the Djembe
  • 35. Visual Aural Kinesthetic Conceptual
  • 36. Cognitive Flow Start Frame it as a Journey Finish
  • 37. /ˈnærətiv / (noun) A narrative (or story) is any account of connected events, presented to a reader or listener in a sequence of written or spoken words, or in a sequence of (moving) pictures. Derived from the Latin verb narrare, "to tell" Narrative
  • 38. A man walks into a store...
  • 39. Narrative Structure
  • 40. Journalistic - Kabob Anecdote Anecdote Meat Meat Meat Nut graf
  • 41. Outline the Story 1 2 3 4 5
  • 42. Making Comics
  • 43. “I can take any empty space and call it a bare stage. A man walks across this empty space whilst someone else is watching him, and this is all that is needed for an act of theatre to be engaged. “ - Peter Brook, The Empty Space Simplicity
  • 44. Content How to craft Data-Stories?
  • 45. Data Art for visual expression, delight (and impact) e.g. Infographics Exhibition | Expression
  • 46. Source: Aaron Koblin Exhibition
  • 47. Data Tool for engagement, exploration and discovery Exploration | Interactive
  • 48. Source: Gramener Exploration
  • 49. Data Stories for telling a specific and (linear) visual narrative Explanatory | Narrative
  • 50. Source: Hans Rosling | Joy of Stats Explanatory
  • 51. Word Writer Note Frame Musician Film Maker | | | Basic Element Data Artist|Datum
  • 52. ??? ??? ??? ??? Datum Data-Stories
  • 53. 1 6 11 16 21 2 7 12 17 22 3 8 13 18 23 4 9 14 19 24 5 10 15 20 25
  • 54. 4 16 1 13 6 11 21 2 7 12 17 22 3 8 18 23 9 14 19 24 5 10 15 20 25
  • 55. See the Data Show the Visual Tell the Story Engage the Audience Datum Data-Stories
  • 56. See the Data Pattern Deviation Outlier Trend Data Abstraction
  • 57. Anscombe’s Quartet x1 y1 x2 y2 x3 y3 x4 y4 10.0 8.04 10.0 9.14 10.0 7.46 8.0 6.58 8.0 6.95 8.0 8.14 8.0 6.77 8.0 5.76 13.0 7.58 13.0 8.74 13.0 12.74 8.0 7.71 9.0 8.81 9.0 8.77 9.0 7.11 8.0 8.84 11.0 8.33 11.0 9.26 11.0 7.81 8.0 8.47 14.0 9.96 14.0 8.10 14.0 8.84 8.0 7.04 6.0 7.24 6.0 6.13 6.0 6.08 8.0 5.25 4.0 4.26 4.0 3.10 4.0 5.39 19.0 12.50 12.0 10.84 12.0 9.13 12.0 8.15 8.0 5.56 7.0 4.82 7.0 7.26 7.0 6.42 8.0 7.91
  • 58. Anscombe’s Quartet x(mean) = 9 y(mean) = 7.5 x(var) = 11 y(var) = 4.12 y = 3.00 + 0.500 x
  • 59. Anscombe’s Quartet
  • 60. Building Ability to See Hypothesis-driven Approach a.k.a Educated guesses based on experience, knowledge & intuition
  • 61. See the Data Pattern Deviation Outlier Trend Data Abstraction
  • 62. Show the Visual Framing Transition Visual Representation
  • 63. Visual Perception
  • 64. Visual Perception Iconic Pre-attentive <1s Fast Temporary Unconscious In-device Working Attentive <1-3s Medium Temporary Conscious RAM Long-term Attentive Long Permanent Deliberate SSD
  • 65. Length Size Orientation Hue Width EnclosureShape PositionIntensity
  • 66. How big is the 2nd circle?
  • 67. Source: WTF Visualizations Avoid Chart Junk
  • 68. Representation Matters Source: South China Post
  • 69. Single Frame Dominates Source: Walmart & Target Store Expansion
  • 70. Establish & Focus Source: OECD Better Life Consistent Visual Framework
  • 71. Establish & Focus Source: OECD Better Life
  • 72. See the Data Pattern Deviation Outlier Trend Data Abstraction
  • 73. Show the Visual Framing Transition Visual Representation
  • 74. Tell the Story Ordering & Structure Messaging (Verbal & Text) Point of View Relatability TRF JQL VWX DFR RGT DEF ZEF LXR
  • 75. Integrate Text & Graphics
  • 76. Stories through Annotation Source: Napolean’s Campaign
  • 77. Linear Narrative Source: Pitch Interactive
  • 78. Source: Hans Rosling | Joy of Stats Power of Verbal Messaging
  • 79. Idea-driven Mileu-driven Character-driven Event-driven
  • 80. See the Data Pattern Deviation Outlier Trend Data Abstraction
  • 81. Show the Visual Framing Transition Visual Representation
  • 82. Tell the Story Ordering & Structure Messaging (Verbal & Text) Point of View Relatability TRF JQL VWX DFR RGT DEF ZEF LXR
  • 83. Engage the Audience TRF JQL VWX DFR RGT DEF ZEF LXR Emotion Takeaway Interactivity
  • 84. Source: Working Capital Profiler Build your own story
  • 85. Source: Wealth Inequality Emotions are key
  • 86. Source: Libor Scandal Emotions
  • 87. “I think the trick with knowledge is to “acquire it, and forget all except the perfume” —  because it is noisy and sometimes drowns out one’s own “brain voices”. The perfume part is important because it will help find the knowledge again to help get to the destinations the inner urges pick. ” — Alan Kay’s advice to Bret Victor Create your own Path
  • 88. Amit Kapoor @amitkaps Partner, narrativeVIZ Consulting amit@narrativeviz.com