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Creating data visualisations that don't suck

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Slides from a presentation given at uxcambridge 2017. This presentation explores the different types of data visualisation that UX designers are likely to encounter and their characteristics. Then it analyses the problems specific to designing for the digital world - we know the type of data we will collect, but not the actual story that the user will see - and how we as designers can make good choices to help users find the stories that exist in their data.

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Creating data visualisations that don't suck

  1. 1. Creating data visualisations that don’t suck
  2. 2. @mcolebourne www.martincolebourne.com Martin Colebourne @tobias_tobias www.tobiasandtobias.com
  3. 3. Data visualisation sucks
  4. 4. medium.com
  5. 5. medium.com So what?
  6. 6. http://www.christiantate.co.uk/?p=646
  7. 7. http://www.christiantate.co.uk/?p=646 Wow, but..
  8. 8. No!
  9. 9. 1: History 2: Types 3: Digital
  10. 10. It’s 2017 - haven’t we solved this already?
  11. 11. Dataviz used to be
  12. 12. Dataviz has changed
  13. 13. New Landscape Applications, online articles and on social media, as well as traditional print. New features like rollovers, interactivity and animation.
  14. 14. 1: History 2: Types 3: Takeaways
  15. 15. Suppose someone offered you a set of “Guidelines for Vehicle Design”
  16. 16. There are lot of different types of vehicles - one set of guidelines could never cover them all
  17. 17. Data Visualisation The same is true for data visualisation
  18. 18. Communication Monitoring ReviewAnalysis Art There are multiple kinds
  19. 19. Communication Monitoring Review Analysis Art
  20. 20. Aims Illustrate Inform Persuade Contexts Print Media Shared via Social Media Webpage Style Static PDF Limited interactivity Communication Monitoring Review Analysis Art
  21. 21. Communication Monitoring Review Analysis Art
  22. 22. Communication Monitoring Review Analysis Art Context Low High Interaction Low High User Knowledge & Experience Low High Real-Time Low High Customisation Low High
  23. 23. Communication Monitoring Review Analysis Art Focus on the story Stay simple - show only what is needed Use visuals to engage, but not get in the way Use a fixed layout so that you can fully control the appearance
  24. 24. Communication Monitoring Review Analysis Art Aims Spot problems React Control Contexts Workstation Big screen ‘Dashboard’ Style Real-time Application Drill-down to see more
  25. 25. Communication Monitoring Review Analysis Art
  26. 26. Communication Monitoring Review Analysis Art
  27. 27. Communication Monitoring Review Analysis Art Context Low High Interaction Low High Experience and Training Low High Real-Time Low High Customisation Low High
  28. 28. Communication Monitoring Review Analysis Art Design to spot anomalies Customisation may be appropriate Can afford to be complex Fixed layout - users learn the physical location of data Should you be building a custom UI for this, or using an off-the-shelf tool?
  29. 29. Communication Monitoring Review Analysis Art But there is a problem: Everybody seems to want a ‘Real-time Dashboard’ But few cases really require real-time monitoring
  30. 30. Communication Monitoring Review Analysis Art Update and Control rate This is a good example: data changes fast and reactions have an immediate effect
  31. 31. Communication Monitoring Review Analysis Art In a business context, numbers don’t change fast enough to see and reactions will take months to have an effect.
  32. 32. Communication Monitoring Review Analysis Art If we don’t need Monitoring, what is the alternative? That brings us on to the next category: Periodic review once a week, or once a month…
  33. 33. Communication Monitoring Review Analysis Art Aims Spot trends Consider & take action Manage Contexts Web portal Email Style Little interaction Sometimes off-line Configured
  34. 34. Communication Monitoring Review Analysis Art
  35. 35. Communication Monitoring Review Analysis Art Experience and Training Low High Customisation Low High Context Low High Real-Time Low High Interaction Low High
  36. 36. Communication Monitoring Review Analysis Art Design for clarity and simplicity Could be online, but might work better as an automated PDF via email What you are aiming for is something more like Communication, but generated automatically on a regular cycle. Ideally needs a data specialist to design each report and add commentary
  37. 37. Communication Monitoring Review Analysis Art Aims Understand Investigate Discover Contexts Web Specialist software Programming languages Style Highly interactive Custom Iterative
  38. 38. Communication Monitoring Review Analysis Art Lightweight Analysis Heavyweight Analysis http://fastml.com/interactive-in-browser-3d-visualization-of-datasets/www.strava.com
  39. 39. http://fastml.com/interactive-in-browser-3d-visualization-of-datasets/ Lightweight AnalysisCommunication Monitoring Review Analysis Art
  40. 40. Heavyweight AnalysisCommunication Monitoring Review Analysis Art
  41. 41. But why is visualisation important for Analysis?
  42. 42. Communication Monitoring Review Analysis Art Can you see anything in these four data sets? I II III IV x y x y x y x y 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 5.0 5.68 5.0 4.74 5.0 5.73 8.0 6.89
  43. 43. Communication Monitoring Review Analysis Art Before we plot the actual data points, let’s see what story summary statistics would tell…
  44. 44. Communication Monitoring Review Analysis Art Averages for x-axis value 3 5 7 9 11 13 3 5 7 9 11 13 15 17 19 3 5 7 9 11 13 3 5 7 9 11 13 15 17 19 3 5 7 9 11 13 3 5 7 9 11 13 15 17 19 3 5 7 9 11 13 3 5 7 9 11 13 15 17 19
  45. 45. Communication Monitoring Review Analysis Art Averages for y-axis values 3 5 7 9 11 13 3 5 7 9 11 13 15 17 19 3 5 7 9 11 13 3 5 7 9 11 13 15 17 19 3 5 7 9 11 13 3 5 7 9 11 13 15 17 19 3 5 7 9 11 13 3 5 7 9 11 13 15 17 19
  46. 46. Communication Monitoring Review Analysis Art Adding linear regressions 3 5 7 9 11 13 3 5 7 9 11 13 15 17 19 3 5 7 9 11 13 3 5 7 9 11 13 15 17 19 3 5 7 9 11 13 3 5 7 9 11 13 15 17 19 3 5 7 9 11 13 3 5 7 9 11 13 15 17 19
  47. 47. Communication Monitoring Review Analysis Art But when we see the actual points… 3 5 7 9 11 13 3 5 7 9 11 13 15 17 19 3 5 7 9 11 13 3 5 7 9 11 13 15 17 19 3 5 7 9 11 13 3 5 7 9 11 13 15 17 19 3 5 7 9 11 13 3 5 7 9 11 13 15 17 19
  48. 48. Communication Monitoring Review Analysis Art Experience and Training Low High Interaction Low High Context Low High Real-Time Low High Customisation Low High Lightweight Lightweight Heavyweight Heavyweight Heavyweight Heavyweight Lightweight Lightweight
  49. 49. Communication Monitoring Review Analysis Art Lightweight Analysis Design with clarity and simplicity Multiple devices, responsive Pick visualisations to help users find insight - this requires lots of expertise from designers
  50. 50. Communication Monitoring Review Analysis Art Heavyweight Analysis Design tools, not specific visualisations Designers need to have deep understanding of data Installed applications, online tools, programming languages But there are heavyweight tools that do this - why aren’t you using one of those?
  51. 51. Communication Monitoring Review Analysis Art Aims Excite Delight Intrigue Contexts Social media Web Gallery Style Complex Little interaction Colour, animation
  52. 52. Communication Monitoring Review Analysis Art
  53. 53. Communication Monitoring Review Analysis Art Anything goes! But don’t oversell it - this is entertainment, not data analysis
  54. 54. 1: History 2: Types 3: Digital
  55. 55. The digital challenge
  56. 56. Communication Monitoring Review Analysis Art
  57. 57. Communication Monitoring Review Analysis Art
  58. 58. In the past we could look at the data and hone the design to tell the story.
  59. 59. For digital design, we know the type of data that will be collected, but not the specific stories that the data will tell.
  60. 60. Temptations: 1. Just chart the data. 2. Give the user lots of customisation.
  61. 61. We need to design visualisations that help users to find the stories in the data.
  62. 62. What questions are the users trying to answer? Is it rising or falling? Is it good or bad? How does it compare to…? Why is this happening?
  63. 63. History Noise Comparison Composition
  64. 64. What is the story?
  65. 65. Does it look different now?
  66. 66. Now what’s the story?
  67. 67. What does this pie chart tell us?
  68. 68. What might it hide from us?
  69. 69. History Noise Comparison Composition
  70. 70. Hard to spot the overall trend
  71. 71. A moving average makes things simpler
  72. 72. A regression line makes the trend clear
  73. 73. History Noise Comparison Composition
  74. 74. What’s the story?
  75. 75. What’s the story now?
  76. 76. History Noise Comparison Composition
  77. 77. Not much going on?
  78. 78. What do you think now?
  79. 79. Summary Show an appropriate amount of history. Smooth out unhelpful noise and include regressions or moving averages to highlight the trends. Show well—chosen comparisons. Consider showing what might be hidden inside the figures.
  80. 80. Thanks

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