Visualization Analysis and Design

Tamara Munzner

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December 1, 2014 by A K Peters/CRC Press
Reference - 428 Pages - 189 Color Illustrations
ISBN 9781466508910 - CAT# K14708
Series: AK Peters Visualization Series

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Table of Contents

What's Vis, and Why Do It?
The Big Picture
Why Have A Human in the Loop?
Why Have A Computer in the Loop?
Why Use An External Representation?
Why Depend on Vision?
Why Show The Data In Detail?
Why Use Interactivity?
Why Is the Vis Idiom Design Space Huge?
Why Focus on Tasks?
Why Focus on Effectiveness?
Why Are Most Designs Ineffective?
Why Is Validation Difficult?
Why Are There Resource Limitations?
Why Analyze?

What: Data Abstraction
The Big Picture
Why Do Data Semantics and Types Matter?
Data Types
Dataset Types
Attribute Types

Why: Task Abstraction
The Big Picture
Why Analyze Tasks Abstractly?
Who: Designer or User
How: A Preview
Analyzing and Deriving: Examples

Analysis: Four Levels for Validation
The Big Picture
Why Validate?
Four Levels of Design
Angles of Attack
Threats and Validation Approaches
Validation Examples

Marks and Channels
The Big Picture
Why Marks and Channels?
Defining Marks and Channels
Using Marks and Channels
Channel Effectiveness
Relative vs. Absolute Judgments

Rules of Thumb
The Big Picture
Why and When to Follow Rules of Thumb?
No Unjustified 3D
No Unjustified 2D
Eyes Beat Memory
Resolution over Immersion
Overview First, Zoom and Filter, Details on Demand
Responsiveness Is Required
Get It Right in Black and White
Function First, Form Next

Arrange Tables
The Big Picture
Why Arrange?
Classifying Arrangements by Keys and Values
Express: Quantitative Values
Separate, Order, and Align: Categorical Regions
Spatial Axis Orientation
Spatial Layout Density

Arrange Spatial Data
The Big Picture
Why Use Given?
Scalar Fields: 1 Value
Vector Fields: Multiple Values
Tensor Fields: Many Values

Arrange Networks and Trees
The Big Picture
Connection: Link Marks
Matrix Views
Costs and Benefits: Connection vs. Matrix
Containment: Hierarchy

Map Color and Other Channels
The Big Picture
Color Theory
Other Channels

Manipulate View
The Big Picture
Why Change?
Change View over Time
Select Elements
Navigate: Changing Viewpoint
Navigate: Reducing Attributes

Facet into Multiple Views
The Big Picture
Why Facet?
Juxtapose and Coordinate Views
Partition into Views
Superimpose Layers

Reduce Items and Attributes
The Big Picture
Why Reduce?

Embed: Focus+Context
The Big Picture
Why Embed?
Costs and Benefits: Distortion

Analysis Case Studies
Graph-Theoretic Scagnostics
Hierarchical Clustering Explorer


Further Reading appears at the end of each chapter.