introduction to visualization qvw

8/17/2019 Introduction to Visualization Qvw

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Introduction to Visualization

Patrik Lundblad

Visualization Advocate


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Experience

• Visualization Advocate and Product Manager

• NComVA founder, acquired by Qlik in May‘13

• PhD in Visualization and Interaction

• Follow me on Twitter: @visualpatrik

Patrik Lundblad


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Why?


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Why Visualization


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Why Visualization

Data Visualization


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Why Visualization

Data Visualization Information


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“Your brain is a pattern-detecting machine”


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The Visual Mind


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Low-level propertyextraction

• Edges• Color• Texture• Movements

Pattern perception• Contours• Motion

Goal directedprocessing

• Few objects dealt atonce

• Focus on a smallnumber of visualfeatures

Visual Perception

Information Visualization: Perception for Design, Colin Ware


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Pre-Attentive Processing


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Find “3” in this series:

49864118710985767838209492850129742756

75649098357620978840129189864128571742


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Graphical features processed pre-attentively


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Visual Perception


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Patterns


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Background vs. Foreground


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LARGER ELEMENTS TEND TO BEPERCIEVED AS MORE IMPORTANT

Size


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Short Term Memory


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"The magical number 7±2"


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Chunking

H L U N E S A U R O Y I N I I O U T N T

UNLEASH YOUR INTUITION


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Chunking

1 Chunk


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Practical


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Before


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After


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Color


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Color


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Understanding how we perceive colors


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Cones Rods

Cones vs Rods

7M

125M


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31http://visual.ly/common-birthdays


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Cones

Cones

33%

2%

65%

Attribution: Mark Fairchild

Fovea


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Colour Blindness

• About 8% of males, but only 0.5% of females, are colour blind in

some way or another.

16 7 8(but red green colour blind

will see 3!)


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Make Things Obvious

28 116


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Can you order these (low->hi)


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Meaningful Data


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Company branding Viz branding

What colors to use?


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Possible Colour of Sequences

www.colorbrewer2.org


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Best Visualization


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London Tube Map - 2014


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Mapping Data to Visualizations

Data

AttributesVisual

Encoding

Discrete• Nominal

• Ordinal

Continuous

• Interval

• Ratio

Sum to Total

Scale, Units

Has NULLs

• Position

• Length

• Area

• Shape

• Color

• …

Usage

• Comparison

• Relationship

• Composition

• Distribution

• …


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Data Attributes• Ratio

– Cost: $15, $30, $45

– Age: 10 years, 20 years, 30 years

• Interval

• Temperature: -5 °, 10 °, 25°

• Time: 1am, 5am, 9am

• Ordinal

– Size: Small, Medium, Large

– Position: 1st, 2nd, 3rd

• Nominal

– Sex: Male, Female

– Sports: Soccer, American Fotball


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Data Attributes

http://community.qlik.com/blogs/qlikviewdesignblog/2014/09/01/scales-of-measurement


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Visual Encoding


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Ranking of Quantitative Perceptual Tasks

More Accurate

Less Accurate

Position Length Angle Area Volume Color


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NOMINAL ORDINAL INTERVAL / RATIO

More Accurate

Less Accurate


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Data encoding errors

From Education Services


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This isn’t news

• The Eyes Have It: A Task by Data Type Taxonomy for

Information Visualizations. Ben Shneiderman

• How NOT to Lie with Visualization. Bernice E. Rogowitz, Lloyd A.

Treinish

• Graphical Perception: Theory, Experimentation, and

Application to the Development of Graphical Methods. William

S. Cleveland; Robert McGill


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Thank You

introduction to visualization qvw

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