cs5984/5764: Information Visualization

Course:

MWF 10:10-11am
McBryde 231
CRN:  95797

Professor:

Dr. Chris North
McBryde 619
Office Hours: MW 1:15-3pm

GTA:

Purvi Saraiya
Office Hours: ???

Text:

• Information Visualization, by Robert Spence, Addison-Wesley.
• Additional papers will be provided on the course web site.

Web site:

• http://infovis.cs.vt.edu/cs5764/

Grading:

50%  Project
30%  Homeworks
15%  Quizzes
5%    Presentation

Format:

This is a research-oriented course. Students survey the state-of-the-art in Information Visualization by reading and critiquing many research papers from the field.  Lectures involve student presentations, class discussion about assigned readings, and videos and live demos of visualization systems. Class participation is important.  Homework assignments require critical thinking about current visualization tools, and creative design of new visualization ideas.  Weekly quizes 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 two types of projects:  Development projects involve the design, implementation, evaluation, and refinement of new visualization tools.  Experimentation projects involve empirical user studies to measure effects of visualizations and develop new theories.  A list of project ideas will be provided, or students can invent new projects.  Students groups also write a conference-quality paper and present their project results to the class.  These projects can provide an excellent starting point for thesis research, and can also result in conference publication.

Learning Objectives:

In this course, students learn how to:

• Examine visualization strategies in the research literature and 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: overviewing, 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: vectorization, 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