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Paul Derby, PhD 
Michael Crites, MA 
Visualization Data for People: 
A Human Factors Perspective
Topics on Paul’s agenda: 
Who is this Paul guy? 
What is Human Factors? 
Human Factors and data visualization 
1 
2 
3
PhD + MA, Experimental Psychology (Human Factors) 
Texas Tech University 
EDUCATION 
Senior Experience Designer 
Honeywell...
What Paul does for Honeywell 
Designs Experiences 
Lead end-to-end UX strategy + design for data visualization solutions
What Paul does for Honeywell 
Designs Experiences 
Lead end-to-end UX strategy + design for data visualization solutions
What Paul does for Honeywell 
Designs Experiences 
Lead end-to-end UX strategy + design for data visualization solutions 
...
What Paul does for Honeywell 
Designs Experiences 
Lead end-to-end UX strategy + design for data visualization solutions 
...
What Paul does for Honeywell 
Designs Experiences 
Lead end-to-end UX strategy + design for data visualization solutions 
...
What Paul does for Honeywell 
Designs Experiences 
Lead end-to-end UX strategy + design for data visualization solutions 
...
What Paul does for Honeywell 
Leads Human Factors Research 
Principal Investigator: Abnormal Situation Management Consorti...
Human Factors + Experience 
Cognitive 
Perceptual 
Physical 
Social 
Experience
Information dashboard
What is a dashboard? 
A visual display of the most important information needed to achieve one or more objectives, consoli...
What is a dashboard? 
In other words: 
It’s a high-level description of the things I care about – except I only really car...
Psychological nerdy talk 
Cognition 
Sensation 
The process of sensing our environment through touch, taste, sight, sound,...
Psychological nerdy talk 
Cognition 
retina 
memory 
attention 
situation awareness 
Sensation
Retina 
light-sensitive layer of tissue lining the inner surface of the eye
Retina
Retina 
Retina
Retina 
Retina
Retina 
Retina
Retina 
Rods 
Cones
Retina 
photoreceptor density 
cones 
rods 
fovea 
Motion + low light 
Motion + low light 
detail + color 
high light 
160...
Retina 
photoreceptor density 
cones 
rods 
Short 
Medium 
Long 
(Acuity) 
fovea
1 
2 
3 
4 
5 
6 
7 
8 
Retina 
10 colors 
(Healey, 1996)
Retina
Retina 
photoreceptor density 
cones 
rods 
Medium 
Long 
Acuity 
Short
Retina 
photoreceptor density 
cones 
rods 
Short 
Medium 
Long 
Acuity
Retina 
photoreceptor density 
cones 
rods 
Short 
Medium 
Long 
Acuity
Retina
Designing to support how we see color 
Color 
We are most sensitive to red/yellow. They should be reserved for important i...
Psychological nerdy talk 
Sensation 
Cognition 
retina 
memory 
attention 
situation awareness
Attention 
Ability to selectively process some information while ignoring others 
(Johnston & Dark, 1986)
Attention 
photoreceptor density 
cones 
rods 
Acuity
Attention
Attention
Attention
Attention
Attention 
Target 
Non-target
Attention 
Noise!
Attention 
Shape
Attention 
Color
Attention 
Size
Attention 
Movement / Pulse 
(Flashing)
Attention 
Distractions
Attention 
Many Distractions
Designing to support attention 
Redundant coding 
Use purposeful color and shape/motion to draw attention 
Avoid clutter 
...
Designing to support attention
Designing to support attention
Psychological nerdy talk 
Sensation 
Cognition 
retina 
working 
memory 
attention 
situation awareness
Ability to actively maintain task-relevant information in the service of a cognitive task (Baddeley & Hitch, 1974) 
Workin...
Working memory 
Central 
Executive 
Visuospatial 
sketchpad 
Phonological 
loop 
Long term Memory
Working memory 
Central 
Executive 
Visuospatial 
sketchpad 
(visual) 
Phonological 
loop 
(verbal) 
Long term Memory
Working memory
Working memory 
How many rows of ?
Working memory (task #1) 
0 
50 
200
Working memory (task #1) 
Raise left hand 
If number is greater than 50 
Raise right hand 
If number is less than 50
50 - 1
48 + 3
150 / 4
46.322 + 3.81
1200 - 3 /100 +7
(1200 – (3 /100)) +7
Easy? Difficult?
Working memory (task #2) 
Which store sold the most oranges in June?
April 
May 
June 
July 
Bananas 
94 
84 
93 
52 
Strawberries 
51 
67 
84 
85 
Oranges 
7 
10 
23 
35 
Kiwi 
55 
64 
66 
7...
April 
May 
June 
July 
Bananas 
58 
68 
23 
11 
Strawberries 
72 
61 
37 
12 
Oranges 
48 
72 
65 
51 
Kiwi 
45 
22 
70 
...
April 
May 
June 
July 
Bananas 
60 
3 
20 
35 
Strawberries 
81 
60 
57 
98 
Oranges 
64 
88 
55 
61 
Kiwi 
7 
54 
50 
98...
April 
May 
June 
July 
Bananas 
1 
67 
26 
77 
Strawberries 
70 
89 
1 
53 
Oranges 
88 
13 
61 
93 
Kiwi 
43 
15 
84 
44...
April 
May 
June 
July 
Bananas 
2 
47 
91 
65 
Strawberries 
74 
84 
68 
100 
Oranges 
76 
42 
12 
84 
Kiwi 
26 
86 
92 
...
Working memory (task #2) 
Which store sold the most oranges in June?
Designing to support working memory 
Increase proximity 
Place related information in close proximity 
Avoid interpretatio...
Designing to support working memory
Psychological nerdy talk 
Sensation 
Cognition 
retina 
working 
memory 
attention 
situation awareness
Comprehension, or understanding, of a dynamic environment 
(Durso, Rawson, & Girotto, 2007) 
Situation awareness
Situation awareness 
Perception 
Comprehension 
Projection
Situation awareness 
Perception 
Comprehension 
Projection 
Perception of elements in time and/or space 
Bananas Sold 
45 ...
Situation awareness 
Perception 
Comprehension 
Projection 
Comprehension of its meaning 
Apples Sold 
98 
100 
50 
0 
(co...
Situation awareness 
Perception 
Comprehension 
Projection 
Projection of their future state 
Dec 
Jan 
Feb 
Mar 
Apr 
May...
Situation awareness 
Perception 
Comprehension 
Projection 
Projection of their future state 
Dec 
Jan 
Feb 
Mar 
Apr 
May...
BYERLY’S 
Bananas 
Strawberries 
Oranges 
Kiwi 
Apples 
Pineapples 
Coconuts 
94 
51 
7 
55 
87 
59 
87 
Count 
YTD 
LUNDS...
Designing to support situation awareness 
Single screen 
Remain within the boundaries of a single screen 
Context 
Show wh...
Wait.. what was that again?
Designing to support color vision 
Color 
We are most sensitive to red/yellow. They should be reserved for important infor...
Designing to support attention 
Redundant coding 
Use purposeful color and shape/motion to draw attention 
Avoid clutter 
...
Designing to support working memory 
Proximity 
Put related information in close proximity 
Avoid interpretation 
Express ...
Designing to support situation awareness 
Single screen 
Remain within the boundaries of a single screen 
Context 
Show wh...
Guiding principles of dashboard design
AND I’m done. 
Thanks :)
August 2014 | Visualizing Data for People: A Human Factors Perspective
August 2014 | Visualizing Data for People: A Human Factors Perspective
August 2014 | Visualizing Data for People: A Human Factors Perspective
August 2014 | Visualizing Data for People: A Human Factors Perspective
August 2014 | Visualizing Data for People: A Human Factors Perspective
August 2014 | Visualizing Data for People: A Human Factors Perspective
August 2014 | Visualizing Data for People: A Human Factors Perspective
August 2014 | Visualizing Data for People: A Human Factors Perspective
August 2014 | Visualizing Data for People: A Human Factors Perspective
August 2014 | Visualizing Data for People: A Human Factors Perspective
August 2014 | Visualizing Data for People: A Human Factors Perspective
August 2014 | Visualizing Data for People: A Human Factors Perspective
August 2014 | Visualizing Data for People: A Human Factors Perspective
August 2014 | Visualizing Data for People: A Human Factors Perspective
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August 2014 | Visualizing Data for People: A Human Factors Perspective

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There are a variety of helpful resources for designers (e.g., books, blogs) that describe best practices for data visualization. While these resources often provide useful recommendations, they sometimes fail to offer explanations about how these visual representations support human cognition and perception. For example, why should we provide time-series trends, limit the use of color, and strive for visual interpretations of values? What is it about human attention, memory, and situation awareness that make some data visualization techniques more effective than others? This presentation will give an overview of some best practices of data visualization and will provide a discussion of why they benefit human perception and performance.

Paul Derby is a Senior Experience Designer within the Honeywell User Experience design studio. Paul has a PhD in experimental psychology (human factors) from Texas Tech University. At Honeywell, Paul focuses on UX research and design within the process industry (e.g., oil/gas, petrochemical, etc.). Currently, Paul is leading multiple UX efforts to improve data visualization products within this domain.

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August 2014 | Visualizing Data for People: A Human Factors Perspective

  1. 1. Paul Derby, PhD Michael Crites, MA Visualization Data for People: A Human Factors Perspective
  2. 2. Topics on Paul’s agenda: Who is this Paul guy? What is Human Factors? Human Factors and data visualization 1 2 3
  3. 3. PhD + MA, Experimental Psychology (Human Factors) Texas Tech University EDUCATION Senior Experience Designer Honeywell User Experience CAREER BA, Psychology California State University, Long Beach 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 Education + mentoring Service Design UX for small businesses INTERESTS
  4. 4. What Paul does for Honeywell Designs Experiences Lead end-to-end UX strategy + design for data visualization solutions
  5. 5. What Paul does for Honeywell Designs Experiences Lead end-to-end UX strategy + design for data visualization solutions
  6. 6. What Paul does for Honeywell Designs Experiences Lead end-to-end UX strategy + design for data visualization solutions Engage Sell Install Use Support Upgrade Website Demos Purchase License Software Physical Web Phone Updates Versions Add-on
  7. 7. What Paul does for Honeywell Designs Experiences Lead end-to-end UX strategy + design for data visualization solutions Discover Define Develop Deliver
  8. 8. What Paul does for Honeywell Designs Experiences Lead end-to-end UX strategy + design for data visualization solutions Marketing Engineering Designers Leaders Users Marcom
  9. 9. What Paul does for Honeywell Designs Experiences Lead end-to-end UX strategy + design for data visualization solutions Marketing Engineering Designers Training Leaders Users Marcom Sales Operations Installers Tech support Accounts ePresence Tech Writers QA IT
  10. 10. What Paul does for Honeywell Leads Human Factors Research Principal Investigator: Abnormal Situation Management Consortium
  11. 11. Human Factors + Experience Cognitive Perceptual Physical Social Experience
  12. 12. Information dashboard
  13. 13. What is a dashboard? A visual display of the most important information needed to achieve one or more objectives, consolidated and arranged on a single screen so the information can be monitored at a glance (Few, 2013).
  14. 14. What is a dashboard? In other words: It’s a high-level description of the things I care about – except I only really care about what’s wrong… and I don’t want to spend time looking at it. Clearly, I have more important things to do.
  15. 15. Psychological nerdy talk Cognition Sensation The process of sensing our environment through touch, taste, sight, sound, and smell. The process of receiving, processing, storing, and using information.
  16. 16. Psychological nerdy talk Cognition retina memory attention situation awareness Sensation
  17. 17. Retina light-sensitive layer of tissue lining the inner surface of the eye
  18. 18. Retina
  19. 19. Retina Retina
  20. 20. Retina Retina
  21. 21. Retina Retina
  22. 22. Retina Rods Cones
  23. 23. Retina photoreceptor density cones rods fovea Motion + low light Motion + low light detail + color high light 160k/mm2
  24. 24. Retina photoreceptor density cones rods Short Medium Long (Acuity) fovea
  25. 25. 1 2 3 4 5 6 7 8 Retina 10 colors (Healey, 1996)
  26. 26. Retina
  27. 27. Retina photoreceptor density cones rods Medium Long Acuity Short
  28. 28. Retina photoreceptor density cones rods Short Medium Long Acuity
  29. 29. Retina photoreceptor density cones rods Short Medium Long Acuity
  30. 30. Retina
  31. 31. Designing to support how we see color Color We are most sensitive to red/yellow. They should be reserved for important information. Color #2 We are least sensitive to blue/violet. They should be reserved for non-critical information. Color deficiency Don’t rely specifically on color to convey a message. Rather, use color as a redundant backup. Design in monochrome first.
  32. 32. Psychological nerdy talk Sensation Cognition retina memory attention situation awareness
  33. 33. Attention Ability to selectively process some information while ignoring others (Johnston & Dark, 1986)
  34. 34. Attention photoreceptor density cones rods Acuity
  35. 35. Attention
  36. 36. Attention
  37. 37. Attention
  38. 38. Attention
  39. 39. Attention Target Non-target
  40. 40. Attention Noise!
  41. 41. Attention Shape
  42. 42. Attention Color
  43. 43. Attention Size
  44. 44. Attention Movement / Pulse (Flashing)
  45. 45. Attention Distractions
  46. 46. Attention Many Distractions
  47. 47. Designing to support attention Redundant coding Use purposeful color and shape/motion to draw attention Avoid clutter Avoid cluttering with large, meaningless pictures & 3D effects. Increase consistency among objects Support visual scanning through structure Use Gestalt principles to group object for meaningful scanning
  48. 48. Designing to support attention
  49. 49. Designing to support attention
  50. 50. Psychological nerdy talk Sensation Cognition retina working memory attention situation awareness
  51. 51. Ability to actively maintain task-relevant information in the service of a cognitive task (Baddeley & Hitch, 1974) Working memory
  52. 52. Working memory Central Executive Visuospatial sketchpad Phonological loop Long term Memory
  53. 53. Working memory Central Executive Visuospatial sketchpad (visual) Phonological loop (verbal) Long term Memory
  54. 54. Working memory
  55. 55. Working memory How many rows of ?
  56. 56. Working memory (task #1) 0 50 200
  57. 57. Working memory (task #1) Raise left hand If number is greater than 50 Raise right hand If number is less than 50
  58. 58. 50 - 1
  59. 59. 48 + 3
  60. 60. 150 / 4
  61. 61. 46.322 + 3.81
  62. 62. 1200 - 3 /100 +7
  63. 63. (1200 – (3 /100)) +7
  64. 64. Easy? Difficult?
  65. 65. Working memory (task #2) Which store sold the most oranges in June?
  66. 66. April May June July Bananas 94 84 93 52 Strawberries 51 67 84 85 Oranges 7 10 23 35 Kiwi 55 64 66 78 Apples 87 79 60 28 Pineapples 59 61 39 47 Coconuts 87 60 94 74 Total 440 425 459 399 Byerly’s Lunds Cub Rainbow Whole Foods
  67. 67. April May June July Bananas 58 68 23 11 Strawberries 72 61 37 12 Oranges 48 72 65 51 Kiwi 45 22 70 57 Apples 57 60 15 55 Pineapples 96 44 33 23 Coconuts 26 65 52 49 Total 402 392 295 258 Byerly’s Lunds Cub Rainbow Whole Foods
  68. 68. April May June July Bananas 60 3 20 35 Strawberries 81 60 57 98 Oranges 64 88 55 61 Kiwi 7 54 50 98 Apples 26 47 43 43 Pineapples 21 24 91 62 Coconuts 76 40 79 58 Total 335 316 395 455 Byerly’s Lunds Cub Rainbow Whole Foods
  69. 69. April May June July Bananas 1 67 26 77 Strawberries 70 89 1 53 Oranges 88 13 61 93 Kiwi 43 15 84 44 Apples 8 53 84 38 Pineapples 98 11 61 37 Coconuts 92 32 99 89 Total 400 280 416 431 Byerly’s Lunds Cub Rainbow Whole Foods
  70. 70. April May June July Bananas 2 47 91 65 Strawberries 74 84 68 100 Oranges 76 42 12 84 Kiwi 26 86 92 90 Apples 47 96 79 57 Pineapples 75 4 41 52 Coconuts 86 46 59 2 Total 386 405 442 450 Byerly’s Lunds Cub Rainbow Whole Foods
  71. 71. Working memory (task #2) Which store sold the most oranges in June?
  72. 72. Designing to support working memory Increase proximity Place related information in close proximity Avoid interpretation Express important data directly and visually Avoid excessive detail All unnecessary information results in the user having to filter what’s important Current Target 3.4590%
  73. 73. Designing to support working memory
  74. 74. Psychological nerdy talk Sensation Cognition retina working memory attention situation awareness
  75. 75. Comprehension, or understanding, of a dynamic environment (Durso, Rawson, & Girotto, 2007) Situation awareness
  76. 76. Situation awareness Perception Comprehension Projection
  77. 77. Situation awareness Perception Comprehension Projection Perception of elements in time and/or space Bananas Sold 45 Apples Sold 98 Oranges Sold 32
  78. 78. Situation awareness Perception Comprehension Projection Comprehension of its meaning Apples Sold 98 100 50 0 (count) Bananas Sold 45 Oranges Sold 32
  79. 79. Situation awareness Perception Comprehension Projection Projection of their future state Dec Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov 0 25 50 75 100 Count 40 50 60 70 75 90 70 65 60 50 45 45 Bananas Sold
  80. 80. Situation awareness Perception Comprehension Projection Projection of their future state Dec Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov 0 25 50 75 100 Count 40 50 60 70 75 90 70 65 60 50 45 45 Bananas Sold
  81. 81. BYERLY’S Bananas Strawberries Oranges Kiwi Apples Pineapples Coconuts 94 51 7 55 87 59 87 Count YTD LUNDS Bananas Strawberries Oranges Kiwi Apples Pineapples Coconuts 94 51 58 55 7 59 87 Count YTD BYERLY’S Bananas Strawberries Oranges Kiwi Apples Pineapples Coconuts 94 51 7 55 87 59 87 Count YTD RAINBOW Bananas Strawberries Oranges Kiwi Apples Pineapples Coconuts 94 51 7 55 87 59 87 Count YTD WHOLE FOODS Bananas Strawberries Oranges Kiwi Apples Pineapples Coconuts 94 51 7 55 87 59 87 Count YTD TOTAL FRUIT L C R WF B 60 100 0 30
  82. 82. Designing to support situation awareness Single screen Remain within the boundaries of a single screen Context Show where data has been and where it’s going Leading indicators Display information about what will likely happen rather than what already happened 1
  83. 83. Wait.. what was that again?
  84. 84. Designing to support color vision Color We are most sensitive to red/yellow. They should be reserved for important information. Color #2 We are least sensitive to blue/violet. They should be reserved for non-critical information. Color deficiency Don’t rely specifically on color to convey a message. Rather, use color as a redundant backup. Design in monochrome first.
  85. 85. Designing to support attention Redundant coding Use purposeful color and shape/motion to draw attention Avoid clutter Avoid cluttering with large, meaningless pictures & 3D effects. Increase consistency among objects Support visual scanning Use Gestalt principles to group object for meaningful scanning
  86. 86. Designing to support working memory Proximity Put related information in close proximity Avoid interpretation Express important data directly and visually Avoid excessive detail All unnecessary information results in the viewer having to filter what’s important Current Target 3.4590%
  87. 87. Designing to support situation awareness Single screen Remain within the boundaries of a single screen Context Show where data has been and where it’s going Leading indicators Display information about what will likely happen rather than what already happened 1
  88. 88. Guiding principles of dashboard design
  89. 89. AND I’m done. Thanks :)
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There are a variety of helpful resources for designers (e.g., books, blogs) that describe best practices for data visualization. While these resources often provide useful recommendations, they sometimes fail to offer explanations about how these visual representations support human cognition and perception. For example, why should we provide time-series trends, limit the use of color, and strive for visual interpretations of values? What is it about human attention, memory, and situation awareness that make some data visualization techniques more effective than others? This presentation will give an overview of some best practices of data visualization and will provide a discussion of why they benefit human perception and performance. Paul Derby is a Senior Experience Designer within the Honeywell User Experience design studio. Paul has a PhD in experimental psychology (human factors) from Texas Tech University. At Honeywell, Paul focuses on UX research and design within the process industry (e.g., oil/gas, petrochemical, etc.). Currently, Paul is leading multiple UX efforts to improve data visualization products within this domain.

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