CS-GY 6313: Information Visualization
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  • Introduction
  • Defining Information Visualization
  • Why Use Visualization?
  • Popular Visualization Sources and Tools
  • Why Use a Graphical Representation?
  • The Problem with Statistics
  • Why Use a Computer to Visualize Data?
  • Why Use Interaction?
  • Assessing the Quality of a Visualization
  • Data Abstraction
    • Types of Datasets
    • Types of Attributes
    • Attribute Semantics
    • Data Abstraction to Visualization
    • Data Profiling
  • Fundamental Graphs
    • Alternate Representations
    • Visualizing More Than 2 Attributes
    • Faceting
  • Data Transformation
  • Graphical Components and Mapping Strategies
    • Marks
    • Channels
    • Graphical Decoding
    • Evaluating the Quality of a Visual Encoding
    • Contextual Components
  • Color
    • Color Perception
    • Color Specification
    • Color Use
      • Quantitative Color Scales
      • Categorical Color Scales
      • Diverging Color Scales
      • Highlighting
    • Perceptual Issues with Color
  • Geo Visualization
    • When to Use Maps
    • Geo Visualization Techniques
      • Dot Maps
      • Heat Maps
      • Hexbin Maps
      • Choropleth Maps
      • Graduated Symbol Maps
      • Summary of Map Types
    • Issues with Maps
    • Visualizing Geo Data with Time
  • Visualizing Temporal Data
    • Time Structures
    • Visualization Methods
    • Increasing Visual Scalability
    • Beyond Using Position
  • Networks and Trees
    • Visualizing Network Data
      • Node-Link Diagrams
        • Clutter Reduction
      • Matrices
    • Visualizing Trees
      • Node-Link Diagrams
      • Special Kinds of Trees
      • Space-Partitioning and Containment
        • Sunburst and Icicle Plots
  • Interaction and Multiple Views
    • Single and Multiple View Methods
      • Single View Methods
      • Multiple (Linked) Views Methods
    • Common Scenarios
  • Exploring Data
  • Animation, Pacing and Exposition
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  • Position
  • Size
  • Angle and Slope
  • Color
  • Shape and Texture

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  1. Graphical Components and Mapping Strategies

Channels

Channels are the visual encoding for data attributes.

There are various types of channels, including:

  • position

  • size (length, width, area)

  • angle and slope

  • color (intensity and hue)

  • shape and texture

Position

Position is one of the most commonly used channels. Almost every visualization uses position.

For example, in a scatter plot, the position of a point denotes the values of two attributes.

In bar charts, the position of a bar identifies a category.

In a network diagram, the positions of the nodes and links is also meaningful.

Size

Size can be 1D (length and width) or 2D (area).

In a bar chart, the length of a bar denotes a quantity.

In a line chart or a network diagram, the width of a line may denote a quantity.

In scatter plots and symbol maps, the areas of the symbols denote quantities.

Angle and Slope

In a line chart, if the x-axis denotes time, the slope of the line denotes the rate of change of a quantity.

In pie charts, the angles denote proportions associated with the values in he corresponding segments.

Color

Color is not a single channel; it is actually 3 channels. Here, we discuss 2 channels: hue and intensity.

Hue is the name of the color i.e. red, green, blue etc. It is used to encode categorical information.

Intensity refers to the brightness of a color. It is used to encode quantitative information. (In other terms, luminance is the amount of light emitted by a color and saturation is the vividness of the color).

Shape and Texture

In a scatter plot, different categorical data items can be identified using different shapes.

In a bar chart, bars can be given different textures, to identify different categories.

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