Chapter 28

Information Visualization

Stuart Card
Xerox PARC

 

Outline

Introduction

Example 1: Finding Videos With the FilmFinder

Example 2: Monitoring Stocks With TreeMaps

Example 3: Sensemaking With Permutation Matrices

What Is Information Visualization?

Historical Origins

The Visualization Reference Model

Mapping Data to Visual Form

Data Structures

Visual Structures

Spatial Substrate

Marks

Connection and Enclosure

Retinal Properties

Temporal Encoding

Expressiveness and Effectiveness

Taxonomy of Information Visualization

Simple Visual Structures

One-Variable Visual Displays

Two-Variable Visual Displays

Three-Variables and Information Landscape n-Variables

Trees

Connection

Enclosure

Networks

Composed Visual Structures

Composed Visual Structures

Single-Axis Composition

Double-Axis Composition

Mark Composition and Case Composition

Recursive Composition

Interactive Visual Structures

Dynamic Queries

Magic Lens

Overview + Detail

Linking and Brushing

Extraction and Comparison

Attribute Explorer

Focus + Context Attention-reactive abstractions

Data-based Methods

Filtering

Selective Aggregation

View Based Methods

Micro-macro Readings

Highlighting

Visual Transfer Functions

Perspective Distortion

Alternate Geometries

Sensemaking with Visualization

Knowledge Crystallization

Acquire Information

Make Sense of It

Create Something New

Act on it

Levels for Applying Information Visualization

Acknowledgements

References

 

Figures

Figure 28.1: FilmFinder overview scattergraph. Courtesy of University of Maryland.) Online version not available

Figure 28.2: FilmFinder scattergraph zoom-in. (Courtesy of University of Maryland.) Online version not available

Figure 28.3: FilmFinder details on demand. (Courtesy of University of Maryland.) Online version not available

Figure 28.4: FilmFinder retrieval by example. (Courtesy of University of Maryland.) Online version not available

Figure 28.5: TreeMap of daily stock prices. (Courtesy of SmartMoney.com.) Online version not available

Figure 28.6: TreeMap of year-to-date stock prices. (Courtesy of SmartMoney.com.) Online version not available

Figure 28.7: Permutation matrix representation of hotel data. (a) Initial matrix of variables. (b) Permuted matrix to group like patterns together. (c) Permutation matrix in simplified form for presentation. Note. From Graphics Constructions and Graphic Information-Processing (pp.24 –31), by J.Bertin,1977/1981,Berlin:Walter De Gruyter Copyright 1977/1981 by Walter De Gruyter. Reprinted with permission. Online version not available

Figure 28.8: Newton’s optics illustration. From his first scientific publication. Note. From The Scientific Image: From Cave to Computer ,by H. Robin, 1992, New York: H. N. Abrams, Inc. Copyright 1992 by H. N. Abrams, Inc. Reprinted with permission. Online version not available

Figure 28.9: Playfair’s chart of English imports and exports. Note. From The Visual Display of Quantitative Information, by E.R.Tufte,1983,Cheshire, CT: Graphics Press. Copyright 1983 by Graphics Press. Reprinted with permission. Online version not available

Figure 28.10: Reference model for visualization (Card et al.,1999).Visualization can be described as the mapping of data to visual form that supports human interaction in a workspace for visual sense making.

Figure 28.11: (Color Version) Types of marks.

Figure 28.12: (Color Version) Retinal properties (Card et al.,1999).The six retinal properties can be grouped by whether they form a scale with a natural zero point (extend) and whether they deal with spatial distance or orientation (spatial).

Figure 28.13: (Color Version) Mapping from data to visual form that violates expressiveness criterion.

Figure 28.14: One-variable visual abstractions. 1D = one-dimensional.

Figure 28.15: Uses of one-variable visual abstractions.

Figure 28.16: Simple Visual Structures.1D = one-dimensional;2D = two-dimensional;3D = three-dimensional.

Figure 28.17: (Color Version) Retinal information topographies.

Figure 28.18: (Color Version) Three-dimensional information surface topographies.

Figure 28.19: Trees.

Figure 28.20: (Color Version) Network methods.

Figure 28.21: (Color Version) Composition types (Partially based on a slide by Jock Mackinlay)

Figure 28.22: (Color Version) Single-axis composition: parallel coordinates (Inselberg,1997).

Figure 28.23: (Color Version) Recursive composition.

Figure 28.24: (Color Version) Interaction techniques.

Figure 28.25: (Color Version) Degree-of-interest calculation for fish-eye visualization. (a) Intrinsic DOI. (b) Distance DOI. (c) DOI = Intrinsic DOI-Distance DOI. (d) After eliding nodes in (c) with a threshold of DOI < -5.

Figure 28.26: Micro-macro reading (Winfree,1987).Courtesy of Scientific American Library. Online version not available

Figure 28.27: (Color Version) Bifocal + transfer function. (a) View of document space. (b) Visual transfer function. (c) First derivative of visual transfer function region.(d) Resulting bifocal view of documents.

Figure 28.28: (Color Version) Attention-reactive visualizations.

Figure 28.29: (Color Version) Levels of use for information visualization (Card et al., 1999).

Figure 28.30: (Color Version) Information visualization applications.