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

Data Types

• Items

• Attributes

• Links

• Positions

• Grids

Dataset Types

• Tables

• Networks

• Fields

• Geometry

Attribute Types

• Categorical

• Ordered

• Ordinal

• Quantitative

Semantics

• Key

• Flat Tables

• Multidimensional Tables

• Values

• Fields

• Scalar

• Vector

• Tensor

Why: Task Abstraction

Actions

• Analyze

• Produce

• Search

• Query

Targets

Analysis: Four Levels for Validation

• Algorithm

• Visual Encoding and Interaction Idiom

• Task and Data Abstraction

• Domain Situation

Marks and Channels

• Mark Types

• Channel Types

Rules of Thumb

• No Unjustified 3D

• No Unjustified 2D

Arrange Tables

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

• Geometry

• Scalar Fields

• Vector Fields

• Tensor Fields

Arrange Networks and Trees

• Connection

• Matrix

Map Color and Other Channels

Color Theory

Color Maps

• Categorical ColorMaps

• Ordered ColorMaps

• Bivariate ColorMaps

Color Channels

• Size

• Angle

• Curvature

• Shape

• Motion

• Texure

Manipulate View

• change time

• select elements

• change viewpoint

• reduce attributes

Facet into Multiple Views

• juxtapose and coordinate views

• partition into views

• superimpose layers

Reduce Items and Attributes

• Filter

• Aggregate

Embed: Focus + Context

• Elide

• Superimpose

• Distort

Analysis Case Studies

附件

Visualization Analysis and Design.xmind