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

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

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PhD + MA, Experimental Psychology (Human Factors) Texas Tech University

EDUCATION

Senior Experience Designer Honeywell User Experience

CAREER

BA, Psychology California State University, Long Beach

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Education + mentoring

Service Design

UX for small businesses

INTERESTS

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



Discover Define Develop Deliver



Marketing Engineering Designers

Leaders Users

Marcom



Marketing Engineering Designers

Training Leaders Users

Marcom

Sales

Operations

Installers

Tech support

Accounts

ePresence Tech Writers QA IT


Leads Human Factors Research Principal Investigator: Abnormal Situation Management Consortium

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, consolidated and arranged on

a single screen so the information can be monitored at a

glance (Few, 2013).

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.

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.


Cognition

retina memory

attention situation awareness

Sensation

Retina light-sensitive layer of tissue lining the inner surface of the eye

Retina

Retina

Retina

Retina

Rods

Cones

Retina p

ho

tore

cep

tor

den

sity

cones

rods

fovea

Motion + low light Motion + low light detail + color high light

160k/mm2

Retina

ph

oto

rece

pto

r d

ensi

ty

cones

rods

Short Medium Long

(Acuity)

Wavelength

fovea

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2

3

4

5

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Retina 10 colors (Healey, 1996)

Retina

Retina

ph

oto

rece

pto

r d

ensi

ty

cones

rods

Medium Long

Acuity

Short

Retina

ph

oto

rece

pto

r d

ensi

ty

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 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.


Sensation Cognition

retina

memory


Attention Ability to selectively process some information while ignoring others

(Johnston & Dark, 1986)

Attention

ph

oto

rece

pto

r d

ensi

ty

cones

rods

Acuity

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 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


Sensation Cognition

retina

working

memory


Ability to actively maintain task-relevant information in the service of a cognitive task

(Baddeley & Hitch, 1974)

Working memory

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


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?


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 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

April May June July

Bananas 58 68 23 11


Oranges 48 72 65 51

Kiwi 45 22 70 57

Apples 57 60 15 55



Total 402 392 295 258


April May June July

Bananas 60 3 20 35


Oranges 64 88 55 61

Kiwi 7 54 50 98

Apples 26 47 43 43



Total 335 316 395 455


April May June July

Bananas 1 67 26 77


Oranges 88 13 61 93

Kiwi 43 15 84 44

Apples 8 53 84 38



Total 400 280 416 431


April May June July

Bananas 2 47 91 65


Oranges 76 42 12 84

Kiwi 26 86 92 90

Apples 47 96 79 57


Coconuts 86 46 59 2

Total 386 405 442 450



Which store sold the most oranges in June?

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%


Sensation Cognition

retina

working

memory


Comprehension, or understanding, of a dynamic environment

(Durso, Rawson, & Girotto, 2007)

Situation awareness

Situation awareness

Perception Comprehension Projection

Situation awareness


Perception of elements in time and/or space

Bananas Sold

45 Apples Sold

98 Oranges Sold

32

Situation awareness


Comprehension of its meaning

Apples Sold 98 100 50 0

(count)

Bananas Sold 45

Oranges Sold 32

Situation awareness


Projection of their future state

Dec Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov

0

25

50

75

100

Co

un

t

40 50 60 70 75 90 70 65 60 50 45 45

Bananas Sold

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

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

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Wait.. what was that again?

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.


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


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%

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

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Guiding principles of dashboard design

AND I’m done.

Thanks :)

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

Presentations & Public Speaking

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