# 视觉可视化分析与设计

# What's Vis, and Why Do it

Computer-based visualization systems provide visual representations of datasets designed to help people carry out tasks more effectively.

# What: Data Abstraction

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# Data Types

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  • Items
  • Attributes
  • Links
  • Positions
  • Grids

# Dataset Types

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  • Tables
  • Networks
  • Fields
  • Geometry

# Attribute Types

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  • Categorical
  • Ordered
    • Ordinal
    • Quantitative

# Semantics

  • Key
    • Flat Tables
    • Multidimensional Tables
  • Values
    • Fields
      • Scalar
      • Vector
      • Tensor

# Why: Task Abstraction

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# Actions

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  • Analyze
  • Produce
  • Search
  • Query

# Targets

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# Analysis: Four Levels for Validation

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  • Algorithm
  • Visual Encoding and Interaction Idiom
  • Task and Data Abstraction
  • Domain Situation

# Marks and Channels

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  • Mark Types
  • Channel Types

# Rules of Thumb

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  • No Unjustified 3D
  • No Unjustified 2D

# Arrange Tables

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# Categorical Regions

  • List Alignment
  • Matrix Alignment
  • Volumetric Grid
  • Recursive Subdivision

# Spatial Axis Orientation

  • Rectilinear Layouts
  • Parallel Layouts
  • Radial Layouts

# Spatial Layout Density

  • Dense
  • Space-Filling

# Arrange Spatial Data

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  • Geometry
  • Scalar Fields
  • Vector Fields
  • Tensor Fields

# Arrange Networks and Trees

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  • Connection
  • Matrix

# Map Color and Other Channels

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# Color Theory

# Color Maps

  • Categorical ColorMaps
  • Ordered ColorMaps
  • Bivariate ColorMaps

# Color Channels

  • Size
  • Angle
  • Curvature
  • Shape
  • Motion
  • Texure

# Manipulate View

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  • change time
  • select elements
  • change viewpoint
  • reduce attributes

# Facet into Multiple Views

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  • juxtapose and coordinate views
  • partition into views
  • superimpose layers

# Reduce Items and Attributes

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  • Filter
  • Aggregate

# Embed: Focus + Context

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  • Elide
  • Superimpose
  • Distort

# Analysis Case Studies