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Foundations 1 Basic Concepts DataVis 2020 http://datavis2020.github.io Dr. Benjamin Bach

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Page 1: Foundations 1 Basic Concepts - DataVis 2020 · 2020. 4. 13. · Defining Concepts computer supported Interactive visual representations For Abstract data Helping people to see and

Foundations 1Basic Concepts

DataVis 2020http://datavis2020.github.io

Dr. Benjamin Bach

Page 2: Foundations 1 Basic Concepts - DataVis 2020 · 2020. 4. 13. · Defining Concepts computer supported Interactive visual representations For Abstract data Helping people to see and

What is visualization?

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Anscombe's Quartet

Page 4: Foundations 1 Basic Concepts - DataVis 2020 · 2020. 4. 13. · Defining Concepts computer supported Interactive visual representations For Abstract data Helping people to see and

Anscombe's Quartet

Page 5: Foundations 1 Basic Concepts - DataVis 2020 · 2020. 4. 13. · Defining Concepts computer supported Interactive visual representations For Abstract data Helping people to see and

(Possible) Definitions

"The use of computer-supported, interactive, visual representations of abstract data to amplify cognition"

..an accessible way to see and understand trends, outliers, and patterns in data."

... to help peoplecarry out tasks more effectively

Stuart Card

Tableau

Tamara Munzner

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Defining Concepts

● computer supported● Interactive visual representations● For Abstract data● Helping people ● to see and understand ● trends, outliers, and patterns in data, ● and carry out tasks ● more effectively● Through amplifying cognition

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Data Visualization Information Action

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PerceivingWhat does it show?Where is big, medium, small? How do things compare? What relationships exist?

InterpretingWhat does it mean? What does color mean? Wha does 'up 'mean? What do these patterns show?

ComprehendingWhat does it mean for me?What shall I do now? Is this all true? What do I learn?

RenderingWhat is my medium? monoscopic/stereoscopic? Tangiblity? Print / digical?

Visual Mapping What is my visual representation?Which visual variables am I using? How am I encoding my data?

DataWhat is my data?Which data type? Ordinal / numerical / categorical?

Encoding: designer Decoding: user

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Item

AttributeValue

1. Data

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2. Visual Mapping

A B C D

Data Visual Representation

+

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3. Rendering

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4. Perceiving

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5. Interpretation

Positive Correlation

Negative Correlation

Page 14: Foundations 1 Basic Concepts - DataVis 2020 · 2020. 4. 13. · Defining Concepts computer supported Interactive visual representations For Abstract data Helping people to see and

PerceivingWhat does it show?Where is big, medium, small? How do things compare? What relationships exist?

InterpretingWhat does it mean? What does color mean? Wha does 'up 'mean? What do these patterns show?

ComprehendingWhat does it mean for me?What shall I do now? Is this all true? What do I learn?

RenderingWhat is my medium? monoscopic/stereoscopic? Tangiblity? Print / digical?

Visual Mapping What is my visual representation?Which visual variables am I using? How am I encoding my data?

DataWhat is my data?Which data type? Ordinal / numerical / categorical?

Encoding: designer Decoding: user

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Pre-attentiveness:- "is the subconscious accumulation of

information from the environment"- realizing something before you think

Parallelity: - Perceiving stimuli in parallel

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Preattentiveness

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Gestalt Laws

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Law of Similarity

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Law of Closure

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Law of Proximity

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Law of Enclosure

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Law of Continuity

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Gestalt Laws

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Gestalt Laws

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Continuity for line following

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Visual Patterns

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Visual Patterns

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PerceivingWhat does it show?Where is big, medium, small? How do things compare? What relationships exist?

InterpretingWhat does it mean? What does color mean? Wha does 'up 'mean? What do these patterns show?

ComprehendingWhat does it mean for me?What shall I do now? Is this all true? What do I learn?

RenderingWhat is my medium? monoscopic/stereoscopic? Tangiblity? Print / digical?

Visual Mapping What is my visual representation?Which visual variables am I using? How am I encoding my data?

DataWhat is my data?Which data type? Ordinal / numerical / categorical?

Encoding: designer Decoding: user

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Page 36: Foundations 1 Basic Concepts - DataVis 2020 · 2020. 4. 13. · Defining Concepts computer supported Interactive visual representations For Abstract data Helping people to see and

Data Types

Categorical(Qualitiative)

Ordered Numerical(Quantitative)

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Page 38: Foundations 1 Basic Concepts - DataVis 2020 · 2020. 4. 13. · Defining Concepts computer supported Interactive visual representations For Abstract data Helping people to see and

PerceivingWhat does it show?Where is big, medium, small? How do things compare? What relationships exist?

InterpretingWhat does it mean? What does color mean? Wha does 'up 'mean? What do these patterns show?

ComprehendingWhat does it mean for me?What shall I do now? Is this all true? What do I learn?

RenderingWhat is my medium? monoscopic/stereoscopic? Tangiblity? Print / digical?

Visual Mapping What is my visual representation?Which visual variables am I using? How am I encoding my data?

DataWhat is my data?Which data type? Ordinal / numerical / categorical?

Encoding: designer Decoding: user

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3 4

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Visual Marks

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Visual Variables

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Characteristics of Visual Variables

Selective: Does it make a mark distinguishable?

Associative: Can I group marks?

Quantitative: Can I do maths with it?

Order: Does it imply an order on the marks?

Length: How many values does the variable has?

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http://innovis.cpsc.ucalgary.ca/innovis/uploads/Publications/Publications/Carpendale_visual_variables.pdf

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How to decode bubbles?

a)

b)

c)

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Recommended Reading

● Tamara Munzner: Visualization Analysis and Design○ Chapter 2. What: Data Abstraction○ Chapter 5. Marks and Channels

● Alberto Cairo: The Functional Art○ Chapter 1: Why Visulize: From Information to Visdom○ Chapter 2: Forms and Functions: Visualization as Technology

● Andy Kirk: Data Visualization○ Chapter 1: Defining Data Visualization

● Jaques Bertin: Semiology of Graphics○ II.C: The retinal variables

● Cleveland & MaGill: Graphical Perception: Theory, Experimentation, and Application to the Development of Graphical Methods, 1984