CS-5630 / CS-6630 Visualization for Data Science Design Guidelines - - PowerPoint PPT Presentation

cs 5630 cs 6630 visualization for data science design
SMART_READER_LITE
LIVE PREVIEW

CS-5630 / CS-6630 Visualization for Data Science Design Guidelines - - PowerPoint PPT Presentation

CS-5630 / CS-6630 Visualization for Data Science Design Guidelines Alexander Lex alex@sci.utah.edu [xkcd] Next Week Tuesday: D3 Maps Thursday: Interaction Mandatory Reading Heer, J., & Shneiderman, B. (2012). Interactive dynamics for


slide-1
SLIDE 1

CS-5630 / CS-6630 Visualization for Data Science Design Guidelines

Alexander Lex alex@sci.utah.edu

[xkcd]

slide-2
SLIDE 2

Next Week

Tuesday: D3 Maps Thursday: Interaction

Mandatory Reading

Heer, J., & Shneiderman, B. (2012). Interactive dynamics for visual analysis. https://doi.org/ 10.1145/2133806.2133821

slide-3
SLIDE 3

Next Homework

slide-4
SLIDE 4

Today’s Reading

slide-5
SLIDE 5

Design Guidelines

slide-6
SLIDE 6

Rule #1: Use the Best Visual Channel Available for the Most Important Aspect of your Data

slide-7
SLIDE 7

Rule #2: The visualization should show all of the data, and only the data

slide-8
SLIDE 8

Book Recommendation

Great book with simple design guidelines Not a “Visualization” book, but a “charting” book

slide-9
SLIDE 9

Edward Tufte

graphical integrity and excellence

slide-10
SLIDE 10

Design Excellence

“Well-designed presentations of interesting data are a matter of substance, of statistics, and of design.”

slide-11
SLIDE 11

Tufte: SparklinesTM

http://www.nytimes.com/interactive/2016/upshot/presidential-polls-forecast.html#recent-state-changes

slide-12
SLIDE 12
slide-13
SLIDE 13

Tufte’s Integrity Principles

Show data variation, not design variation Clear, detailed, and thorough labeling and appropriate scales Size of the graphic effect should be directly proportional to the numerical quantities (“lie factor”)

slide-14
SLIDE 14

The Lie Factor

Size of effect shown in graphic Size of effect in data

slide-15
SLIDE 15

Lie Factor - Graphical Integrity

Magnitude in data must correspond to magnitude of mark

Flowing Data

Effect in Data: factor 1.14 Effect in Graphic: factor 5 Lie Factor: 5/1.14 = 4.38

slide-16
SLIDE 16

Scale Distortions

Flowing Data

slide-17
SLIDE 17

What’s wrong?

slide-18
SLIDE 18

What’s wrong?

slide-19
SLIDE 19

What’s wrong?

slide-20
SLIDE 20
slide-21
SLIDE 21

Start Scales at 0?

  • A. Kriebel,

VizWiz

slide-22
SLIDE 22

Use a baseline that shows the data, not the zero-point.

  • E. Tufte

Think about: what is a meaningful baseline?

slide-23
SLIDE 23

Scales at 0

slide-24
SLIDE 24

Framing

Vis can be used to lie

just as language or statistics

When showing something, make sure that you’re faithful to the data

slide-25
SLIDE 25

Global Warming?

The Daily Mail, UK, Jan 2012

slide-26
SLIDE 26

Global Warming?

Mother Jones

slide-27
SLIDE 27

Global Warming - Frame the Data

Mother Jones

Also see: USA Temperature: can I sucker you?

slide-28
SLIDE 28

What’s wrong?

slide-29
SLIDE 29

Scale Distortions in Temporal Data

slide-30
SLIDE 30

Scale Distortions in Temporal Data

slide-31
SLIDE 31

What’s wrong?

slide-32
SLIDE 32

Height of the Bar encodes mean of a distribution Which value is more likely to belong to the distribution? 
 A or B?

http://www.tandfonline.com/doi/full/10.1080/00031305.2016.1141706

slide-33
SLIDE 33

Biases

We can plot the data faithfully, but still perceive it wrongly!

slide-34
SLIDE 34

What about now?

B

slide-35
SLIDE 35

Within the Bar Bias

Experimental Conditions Results

Christopher S. Pentoney & Dale E. Berger (2016) Confidence Intervals and the Within-the-Bar Bias, The American Statistician, 70:2, 215-220

slide-36
SLIDE 36

Careful when designing aggregated charts

slide-37
SLIDE 37

What’s the Trendline?

slide-38
SLIDE 38

Regression by eye

http://idl.cs.washington.edu/files/2017-RegressionByEye-CHI.pdf [Corell & Heer, 2017]

We’re good at spotting trends But the wrong vis technique can deceive us

slide-39
SLIDE 39

Death to Pie Charts

Cole Nussbaumer www.storytellingwithdata.com/2011/07/death-to-pie-charts.html

“I hate pie charts. I mean, really hate them.”

Share of coverage

  • n TechCrunch
slide-40
SLIDE 40

Redesign

slide-41
SLIDE 41

Can you spot the differences?

slide-42
SLIDE 42

Can you spot the differences?

slide-43
SLIDE 43

My favorite pie chart

slide-44
SLIDE 44

My second favorite pie chart

slide-45
SLIDE 45

https://twitter.com/K_Graves/status/1118927857214873600

slide-46
SLIDE 46

So, what to use instead?

http://www.storytellingwithdata.com/blog/2014/06/alternatives-to-pies

imagine you just completed a pilot summer learning program on science aimed at improving perceptions of the field among 2nd and 3rd grade elementary children

slide-47
SLIDE 47

Alternative #1: Show the Number(s) Directly

slide-48
SLIDE 48

Alternative #2: Simple Bar Graph

slide-49
SLIDE 49

Alternative #3: 100% Stacked Horizontal Bar Graph

slide-50
SLIDE 50

Alternative #4: Slopegraph

slide-51
SLIDE 51

Design Critique / Redesign

slide-52
SLIDE 52

Sunday Star Times, 2012

https://goo.gl/lHWp4x

slide-53
SLIDE 53
  • R. Cunliffe, Stats Chat

Quantity encoded by diameter, not area! Fixing that:

slide-54
SLIDE 54
  • R. Cunliffe, Stats Chat

But is this visual encoding appropriate in the first place?

slide-55
SLIDE 55

Visualization Design Principles

slide-56
SLIDE 56

Maximize Data-Ink Ratio

0-$24,999 $25,000+ 0-$24,999 $25,000+

slide-57
SLIDE 57

Maximize Data-Ink Ratio

175 350 525 700 Males Females

0-$24,999 $25,000+ 0-$24,999 $25,000+

slide-58
SLIDE 58

Avoid Chart Junk

  • ngoing, Tim Brey

Extraneous visual elements that distract from the message

slide-59
SLIDE 59

Avoid Chart Junk

  • ngoing, Tim Brey
slide-60
SLIDE 60

Avoid Chart Junk

  • ngoing, Tim Brey
slide-61
SLIDE 61

Avoid Chart Junk

  • ngoing, Tim Brey
slide-62
SLIDE 62

Avoid Chart Junk

  • ngoing, Tim Brey
slide-63
SLIDE 63

Avoid Chart Junk

  • ngoing, Tim Brey
slide-64
SLIDE 64

Which is better?

[Bateman et al. 2010]

slide-65
SLIDE 65

Which is better?

https://eagereyes.org/criticism/chart-junk-considered-useful-after-all

[Bateman et al. 2010]

slide-66
SLIDE 66
slide-67
SLIDE 67

EXPERIMENTAL RESULTS

  • 1. No difference for interpretation accuracy
  • 2. No difference in recall accuracy after a five-minute gap
  • 3. Significantly better recall for Holmes charts of both the chart topic

and the details (categories and trend) after long-term gap (2-3 weeks).

  • 4. Participants saw value messages in the Holmes charts significantly

more often than in the plain charts.

  • 5. Participants found the Holmes charts more attractive, most enjoyed

them, and found that they were easiest and fastest to remember.

slide-68
SLIDE 68

PROS persuasion memorability engagement CONS biased analysis trustworthiness interpretability space efficiency effort

Use Chart Junk? It depends!

slide-69
SLIDE 69

Alignment Matters

https://twitter.com/infowetrust/status/760521739092627457 http://www.visualisingdata.com/2016/08/little-visualisation-design-part-21/

slide-70
SLIDE 70

No Unjustified 3D

Depth judgment is bad

N = 0.67 Sensation=Intensity^N

Occlusion Perspective Distortion Color: Lighting / Shadows / 
 Shading Tilted Text illegible

slide-71
SLIDE 71

Don’t

matplotlib gallery

Excel Charts Blog
slide-72
SLIDE 72

Don’t

https://www.vice.com/en_uk/read/foi-uk-drug-conviction-ethnicity-282

slide-73
SLIDE 73

3D Design Alternatives

http://interactions.acm.org/archive/view/july-august-2018/the-good-the-bad-and-the-biased

slide-74
SLIDE 74

3D Design Alternatives

http://interactions.acm.org/archive/view/july-august-2018/the-good-the-bad-and-the-biased

slide-75
SLIDE 75

Example: Hierarchy Visualization

[F. van Ham ; J.J. van Wijk, 2002]

slide-76
SLIDE 76

Eyes Beat Memory

Don’t make people memorize: Show them

http://www.randalolson.com/2015/08/23/small-multiples-vs-animated-gifs-for-showing-changes-in-fertility-rates-over-time/

slide-77
SLIDE 77

What can we do differently?

slide-78
SLIDE 78

Eyes Beat Memory: Small Multiples

A lot of charts Do we need all of them?

slide-79
SLIDE 79

Eyes Beat Memory: Small Multiples

slide-80
SLIDE 80

Simplify!

slide-81
SLIDE 81

Small Multiple Design Alternatives

http://interactions.acm.org/archive/view/july-august-2018/the-good-the-bad-and-the-biased