User:Infografica/VisMaterial

I'm gathering material on visualization. It's a complicated topic, with different people having different perspectives... but my goal is to put together enough reference material from the top academics that areas of consensus will appear.

definitions

examples

From John Stasko's 2004 course on information visualization:

"Information visualization is a new research area that focuses on the use of visualization techniques to help people understand and analyze data. While fields such as scientific visualization involve the presention of data that has some physical or geometric correspondence, information visualization focuses on abstract data without such correspondences such as symbolic, tabular, networked, hierarchical, or textual information sources."

From Tamara Munzner's "Guest Editor's Introduction" to the CG&A InfoVis issue, Jan/Feb 2002: "information visualization hinges on finding a spatial mapping of data that is not inherently spatial, whereas scientific visualization uses a spatial layout that's implicit in the data."

From Colin Ware's book Information Visualization (2004): "The use of interactive visual representations of abstract data to amplify cognition"

Colin Ware likely based this on Card, Mackinlay, and Shneiderman's 1999 book, "Readings in Information Visualization: Using Vision to Think." They define:

"Visualization: The use of computer-supported, interactive, visual representations of data to amplify cognition"

and

"Information visualization: The use of computer-supported, interactive, visual representations of abstract data to amplify cognition".

(the distinction here is the word "abstract". Note that given Shneiderman's syllabus below, and the emphasis on high-dimensional data in the IEEE InfoVis conference, "abstract" apparently can include numerical data without a natural physical or 3D interpretation.).

summary

Here's my summary...

Information visualization is the use of graphical techniques to help people understand and analyze data. In contrast with scientific visualization, information visualization focuses on abstract data sets, such as unstructured text or points in high-dimensional space, that do not have an inherent 2D or 3D geometrical structure.^[1]^[2]^[3]

^ Card, Mackinlay, and Shneiderman, "Readings in Information Visualization: Using Vision to Think," 1999.
^ Tamara Munzner, Guest Editor's Introduction IEEE Computer Graphics and Applications Special Issue on Information Visualization, Jan/Feb 2002
^ John Stasko, syllabus for CS7450, "Information Visualization." http://www.cc.gatech.edu/classes/AY2004/cs7450_spring/

syllabus material: general "visualization" courses

Example 1: CS 171, Harvard

Hanspeter Pfister taught a course titled "Visualization" in the Harvard CS department, spring 2008. The list of topics covered:

Data and Image Models
Visual Perception & Cognitive Principles
Color Encoding
Visualization Software Design
Designing 2D Graphs
Maps & Google Earth
Higher-dimensional Data
Unstructured Text and Document Collections
Trees and Networks
Scientific Visualization
Medical Visualization
Scientific Photography
Animation
Interaction Techniques
Social Visualization
Visualization & The Arts

Example 2: CS 294-10, Berkeley

Maneesh Agrawala taught a course titled "Visualization" in the Berkeley CS department, fall 07.

The Purpose of Visualization
Data and Image Models
Discussion of Good and Bad Visualizations
Introduction to Visualization Software
Perception
Perception II
Authoring Visualizations and Prefuse
Using Space Effectively: 2D
Graphs and Trees
Using Space Effectively: 2D II
Collaborative Visualization
Tag Clouds
Spatial Layout
Identifying Design Principles
Color

information visualization courses

Example 3: CMSC 838S, U. Maryland

Ben Shneiderman taught a course titled "Information Visualization" at U. Maryland, spring 2007. Topics:

7 types of data (1-, 2-, 3-, multi-dimensional, temporal, tree, and network data)
7 tasks (overview, zoom, filter, details-on-demand, relate, history, and extract)
Direct manipulation (visual representation of the objects and actions of interest and rapid, incremental, and reversible operations)
Dynamic queries (HomeFinder, Dynamap, Spotfire)
Visual Info Seeking mantra: Overview First, Zoom and Filter, then Details-on-Demand
Evaluation methods (controlled experiments, observations, case studies)

Example 4: CS 7450, Georgia Tech

John Stasko taught a couse titled "Information Visualization" at George Tech, spring 2004. Topics:

Multivariate Data & Representations
Multivariate visualization tools
Visual Perception
Visual Design
Interaction & Dynamic Queries
Time Series Data
Focus & Context
Zooming Details
Hierarchies & Trees
Graphs Details
WWW and Internet
Text & Documents
Software Visualization
Vis for Information Security
Social Visualization
Ambient InfoVis
Automating Design

[1] Card, Mackinlay, and Shneiderman, "Readings in Information Visualization: Using Vision to Think," 1999.

[2] Tamara Munzner, Guest Editor's Introduction IEEE Computer Graphics and Applications Special Issue on Information Visualization, Jan/Feb 2002

[3] John Stasko, syllabus for CS7450, "Information Visualization." http://www.cc.gatech.edu/classes/AY2004/cs7450_spring/

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