User:Infografica/VisMaterial
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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