cs5764: Information Visualization

Course:

MW 1:25 - 2:40pm
McBryde 218
CRN:  94992

Professor:

Dr. Chris North
McBryde 619
Office Hours: MW 2:45 - 4:45pm

GTA:

Beth Yost
beyost@vt.edu
Office Hours: ???

Text:

• Information Visualization, by Robert Spence, Addison-Wesley (optional reference).
• Research papers for reading will be provided on the course web site.

Web site:

• http://infovis.cs.vt.edu/cs5764/

Grading:

50%  Project
25%  Quizzes and in-class activities
20%  Homeworks
5%    Paper presentation or review

Format:

This is a research-oriented course. Students survey the state-of-the-art in the field of Information Visualization by reading and discussing many research papers.  Lectures involve student presentations, class discussion about assigned readings, and live demos of visualization systems. Class participation is important.  Short homework assignments require critical thinking about current visualization tools, and creative design of new visualization ideas.  Occasional pop quizzes and in-class activities will reinforce readings and lecture materials.  There are no exams.

Large semester-long projects are the focus of the course.  Students work in small groups on research projects that contribute to the state-of-the-art in the field.  Students choose from three types of projects:  Development projects involve the design, implementation, and evaluation of new visualization tools.  Experimentation projects involve conducting empirical user studies to measure and analyze effects of visualizations.  Theoretical projects survey and analyze the research literature and synthesize new theories or taxonomies.  A list of project ideas will be provided, or students can invent new projects.  Students groups write a conference-quality paper and present their project results to the class.  These projects provide an excellent opportunity for initiating or continuing thesis research, and can result in conference publication.

Learning Objectives:

In this course, students learn how to:

• Examine visualization strategies in the research literature and in tools from the trade;
• Design information visualizations for given data, users, and tasks;
• Prototype and implement visualizations and supporting algorithms and data structures;
• Evaluate visualizations with empirical user studies.

Topics:

• Design Principles: HCI metrics, scale, tasks, data mapping, overviewing, direct manipulation, data density, graphic properties, data types
• Interaction Strategies: overviews, multiple views, focus + context, filtering and querying, lens, data flow, information-centric, end-user construction, automatic construction
• Multi-dimensional visualization: axis arrangements, single item arrangements, nested arrangements, tables, filtering and querying
• 1D: timelines, text, sliders, walls, books, music
• 2D: zoom & pan, overview & detail, space-scale, lens, bifocal, distortion
• 3D: navigation, volumes
• Hierarchies: node & link, space filling, fisheye
• Networks and Web: node & link
• Document collections: vector representations, clustering, maps and layouts, interrelationships
• Workspaces: task management, infosphere, window management
• Evaluation: empirical user studies, usability
• Theory: info foraging, taxonomies, navigation, spatial visualization ability
• Miscellaneous: implementation, systems, data formats, application areas, 2D vs 3D, multiple views vs distortion