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Value-Suppressing Uncertainty Palettes Michael Correll Dominik Moritz Jeffrey Heer 1 Value-Suppressing Uncertainty Palettes Michael Correll Dominik Moritz Jeffrey Heer 2 Outline What We Did Why We Did It Why We Think It Works 3


  1. Value-Suppressing Uncertainty Palettes Michael Correll Dominik Moritz Jeffrey Heer 1

  2. Value-Suppressing Uncertainty Palettes Michael Correll Dominik Moritz Jeffrey Heer 2

  3. Outline What We Did Why We Did It Why We Think It Works 3

  4. Outline What We Did Why We Did It Why We Think It Works 4

  5. 2016 Election 5

  6. 2016 U.S. Election 6

  7. 2016 U.S. Election Clinton is only 1.6 margins of error away! (p>0.05) 7

  8. 2016 U.S. Election Clinton is only 1.6 margins of error away! (p>0.05) How to convey uncertainty? 8

  9. 2016 U.S. Election Clinton is only 1.6 margins of error away! (p>0.05) How to convey uncertainty? How to encourage people from refraining from deciding? 9

  10. Value-Suppressing Uncertainty Palette 10

  11. Value-Suppressing Uncertainty Palette 11

  12. Value-Suppressing Uncertainty Palette 12

  13. Value-Suppressing Uncertainty Palettes Traditional Bivariate Map 13

  14. Value-Suppressing Uncertainty Palettes Traditional Bivariate Map VSUP 14

  15. Value-Suppressing Uncertainty Palettes Traditional Bivariate Map VSUP 15

  16. Value-Suppressing Uncertainty Palettes Traditional Bivariate Map VSUP 16

  17. Value-Suppressing Uncertainty Palettes Traditional Bivariate Map VSUP 17

  18. VSUP 18

  19. Tree-Quantization 19

  20. Tree-Quantization 20

  21. Tree-Quantization 21

  22. 22

  23. Outline What We Did Why We Did It Why We Think It Works 23

  24. Uncertainty In Maps 24

  25. Uncertainty In Maps Data Map 25

  26. Uncertainty In Maps Data Map Uncertainty Map 26

  27. Uncertainty In Maps Data Map Uncertainty Map 27

  28. Uncertainty In Maps Data Map Uncertainty Map 28

  29. Uncertainty In Maps Data Map Uncertainty Map 29

  30. Uncertainty In Maps Data Map Uncertainty Map 30

  31. Juxtaposition Data Map Uncertainty Map 31

  32. Data Map 32

  33. Juxtaposed Uncertainty 33

  34. Why This Is Bad 2x Space Requirements 34

  35. Why This Is Bad 2x Space Requirements Requires Searching 35

  36. Why This Is Bad 2x Space Requirements Requires Searching Ignorable 36

  37. Superposition 37

  38. Bivariate Map 1928 38

  39. Bivariate Map 1928 1874 39

  40. 40

  41. VSUP 41

  42. VSUP VSUPs are a bivariate mapping of data and uncertainty that allow fine-grain comparisons when data are more certain, and coarser comparisons when data are less certain. 42

  43. Outline What We Did Why We Did It Why We Think It Works 43

  44. Will This Work? 44

  45. Will This Work? 45

  46. Bivariate Maps Are Hard! “[R]eading Two-Variable Color Maps at the elementary, intermediate, or superior level is at the very least difficult, and may be impossible.” -Wainer & Francolini, 1980 46

  47. Discrete Color Maps Are Inaccurate! “[W]ith possible rare exceptions, continuous color scales represent the data more effectively than binned color scales, so we should stick with them.” -Few, 2017 47

  48. Evaluating VSUPs 48

  49. Evaluating VSUPs 49

  50. Evaluating VSUPs 50

  51. Alternative Designs 51

  52. Alternative Designs 52

  53. Alternative Designs 53

  54. Alternative Designs 54

  55. Alternative Designs 55

  56. Alternative Designs 56

  57. Methods 2 MTurk Experiments: Identification Task Prediction Task 48 Participants (w/o CVD) 2112 Trials 57

  58. Identification Task 58

  59. Value of 0.45, Uncertainty of 0.1 59

  60. Value of 0.45 60

  61. Value of 0.45 61

  62. Uncertainty of 0.1 62

  63. Uncertainty of 0.1 63

  64. Uncertainty of 0.1 64

  65. Identification Task 65

  66. Value of 0.7, Uncertainty of 0.4 66

  67. Uncertainty of 0.4 67

  68. Uncertainty of 0.4 68

  69. Value of 0.7 69

  70. Value of 0.7 70

  71. Value of 0.7 71

  72. Results 72

  73. Results 73

  74. Value of 0.7, Uncertainty of 0.4 74

  75. Value of 0.7, Uncertainty of 0.4 75

  76. Results 76

  77. Results 77

  78. Results 78

  79. Results Interference disrupts Continuous Maps Search disrupts Juxtaposed Maps 79

  80. Prediction Task How can we induce and compare risk-averse behavior in heatmaps? 80

  81. Prediction Task 81

  82. Prediction Task 82

  83. Prediction Task 83

  84. Prediction Task 84

  85. Prediction Task Could be Dangerous! Definitely Safe. 85

  86. Placing Ships 86

  87. Where To Put The Last Ships? 87

  88. Where To Put The Last Ships? 88

  89. Where To Put The Last Ship? 89

  90. Where To Put The Last Ships? 90

  91. Where To Put The Last Ships? 91

  92. Results Bivariate Maps encourage risk seeking VSUP Maps encourage risk aversion 92

  93. VSUPs are an unignorable way of integrating data and uncertainty. VSUPs make people more cautious in their decision-making. 93

  94. Thanks! This work was supported by a Moore Foundation Data-Driven Discovery Investigator award. Study materials available at: https://github.com/uwdata/papers-vsup Make your own VSUPs at: https://github.com/uwdata/vsup 94

  95. Extra Slides 95

  96. 96

  97. Flight Delay 97

  98. Flight Delay 98

  99. Flight Delay 99

  100. 100

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