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Whats the Difference?: Evaluating Variants of Multi-Series Bar Charts for Visual Comparison Tasks Arjun Srinivasan Matthew Brehmer Bongshin Lee Steven M. Drucker Whats changed? Year over Year sales Production in Region 1 vs.

  1. What’s the Difference?: Evaluating Variants of Multi-Series Bar Charts for Visual Comparison Tasks Arjun Srinivasan Matthew Brehmer Bongshin Lee Steven M. Drucker

  4. “ What’s changed? ” Year over Year sales Production in Region 1 vs. Production in Region 2 …

  9. How can we facilitate visual comparison in multi-series bar charts ?

  10. Interviews & + Survey Exploration of design alternatives Extremes- Target Extremes- Source Constant Max. Change Evaluation Value Difference Varying Old Categories New Categories Applications & Extensions

  11. Interviews & + Survey Exploration of design alternatives Extremes- Target Extremes- Source Constant Max. Change Evaluation Value Difference Varying Old Categories New Categories Applications

  13. Bar charts were the most common visualizations Ordinal x Quantitative (e.g., monthly sales) [ constant ] Nominal x Quantitative (e.g., individual employee sales) [ varying ]

  14. Design considerations: • Show raw values Q1 Q2 Q3 Q4 Q3 Q1 Q2 Q4 Q1 Q2 Q3 Q4 Q1 Q2 Q3 Q4

  15. Design considerations: • Show raw values • Do not occupy additional space Q3 Q1 Q2 Q3 Q4 Q1 Q2 Q4 Q1 Q2 Q3 Q4 Q1 Q2 Q3 Q4

  16. Design considerations: • Show raw values • Do not occupy additional space • Maintain visualization type 1 P1 2 P2 P1 P2 P3 P4 P3 3 P4 4 Year1 Year2 P1 P2 P3 P4

  17. Design considerations: • Show raw values • Do not occupy additional space • Maintain visualization type • Account for varying vs. constant data conditions • Make it easier to measure differences

  22. • Show raw values • Do not occupy additional space • Maintain visualization type

  24. • Show raw values • Do not occupy additional space • Maintain visualization type • Account for data conditions • Make it easier to measure difference

  26. • Show raw values • Do not occupy additional space • Maintain visualization type • Account for data conditions • Make it easier to measure difference

  27. • Show raw values • Show raw values • Do not occupy additional space • Do not occupy additional space • Maintain visualization type • Maintain visualization type • Account for variations in data • Account for variations in data • Make it easier to measure difference • Make it easier to measure difference ??? • Show raw values • Do not occupy additional space • Maintain visualization type • Account for variations in data • Make it easier to measure difference

  28. Interviews & + Survey Exploration of design alternatives Extremes- Target Extremes- Source Constant Max. Change Evaluation Value Difference Varying Old Categories New Categories Applications

  29. Juxtaposition Explicit Encoding Superimposition M Gleicher et al. 2011

  30. Juxtaposition Explicit Encoding Superimposition

  31. BarTender Juxtaposition Explicit Encoding Superimposition

  32. BarTender Juxtaposition Explicit Encoding Superimposition

  33. BarTender Juxtaposition Explicit Encoding Superimposition

  34. BarTender Juxtaposition Explicit Encoding Superimposition

  35. BarTender Juxtaposition + Explicit Encoding + Superimposition

  36. BarTender Juxtaposition + Explicit Encoding + Superimposition

  37. BarTender Juxtaposition Explicit Encoding + Superimposition

  39. Grouped Bar Chart Difference Chart

  40. Grouped Bar Chart Single Bar Chart w/ difference overlay w/ difference overlay

  41. Grouped Bar Chart Single Bar Chart w/ difference overlay w/ difference overlay • Show raw values • Do not occupy additional space • Maintain visualization type • Account for variations in data • Make it easier to measure difference

  42. Interviews & + Survey Exploration of design alternatives Extremes- Target Extremes- Source Constant Max. Change Evaluation Value Difference Varying Old Categories New Categories Applications

  43. Extremes- Target Extremes- Source Max. Change Constant Value Difference Varying Old Categories New Categories 74 Participants 6 Tasks 2 Data Conditions

  44. Tasks Extremes- Target Extremes- Source Max. Change Value Difference Old Categories New Categories

  45. Tasks Extremes- Target Value interpretation Extremes- Source Max. Change Value Difference Old Categories New Categories

  46. Tasks Extremes- Target Extremes- Source Max. Change Value Difference Old Categories New Categories

  47. Tasks Extremes- Target Extremes- Source Max. Change Difference-based Value Difference Old Categories New Categories

  48. Tasks Extremes- Target Extremes- Source Max. Change Value Difference Old Categories New Categories

  49. Tasks Extremes- Target Extremes- Source Max. Change Value Difference Old Categories Varying data conditions New Categories

  50. Tasks Extremes- Target Extremes- Source Max. Change Value Difference Old Categories New Categories

  51. Design Data Type 1 Training Testing Data Type 2 Training Testing Introduction Introduction Phase Phase Introduction Phase Phase

  52. Design Data Type 1 Training Testing Data Type 2 Training Testing Introduction Introduction Phase Phase Introduction Phase Phase

  53. Design Data Type 1 Training Testing Data Type 2 Training Testing Introduction Introduction Phase Phase Introduction Phase Phase

  54. Design Data Type 1 Training Testing Data Type 2 Training Testing Introduction Introduction Phase Phase Introduction Phase Phase

  55. Design Data Type 1 Training Testing Data Type 2 Training Testing Introduction Introduction Phase Phase Introduction Phase Phase

  56. Design Data Type 1 Training Testing Data Type 2 Training Testing Introduction Introduction Phase Phase Introduction Phase Phase 4 visualizations 87 trials (28 training, 56 testing, 3 guess checking) (time) (error) (subjective preferences)

  57. Results • Comparable for value interpretation and varying data condition tasks. • Performance with hybrid designs was better for difference-based tasks. vs

  58. Results • Comparable for difference-based tasks . vs

  59. Results Which of the four chart designs did you prefer most ?

  60. Results Which of the four chart designs did you prefer least ?

  61. Interviews & + Survey Exploration of design alternatives Extremes- Target Extremes- Source Constant Max. Change Evaluation Value Difference Varying Old Categories New Categories Applications & Extensions

  62. Revealing changes in narrative visualizations

  63. Complementing overlays with annotations for missing values

  64. Summary • Visual comparison is an important task in dashboards • Hybrid visualizations combining design strategies afford more tasks while performing comparably on individual tasks .

  65. Summary • Visual comparison is an important task in dashboards • Hybrid visualizations combining design strategies afford more tasks while performing comparably on individual tasks . vs vs

  66. Thank You Arjun Srinivasan Matthew Brehmer http://arjun010.github.io/ Bongshin Lee Steven M. Drucker

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