490KN

From GSLISWiki

[edit] Visualizing Knowledge Networks

Identical To

ECE 498NA

CS 498AT

LIS 490KNU

LIS 490KNG

Last Taught

Spring 2005

Instructor

Professor Mike Twidale

Professor Narendra Ahuja

Professor Noshir Contractor

Has Taken

Cameron Jones

[edit] Course Description

[edit] Spring 2005 Version

Time: 5-7:50pm Tuesdays

Location: Beckman Institute Rm 2269

Hours: 3 (or 4 with extra work)

This course is being offered by instructors from two different departments:

Michael Twidale

Graduate School of Library & Information Science

URL: http://alexia.lis.uiuc.edu/~twidale/

Narendra Ahuja

Department of Electrical and Computer Engineering

Computer Vision & Robotics Laboratory

Beckman Institute for Advanced Science & Technology

URL: http://vision.ai.uiuc.edu/index.html

It is a revised version of a course originally taught in Spring 2003 by the two instructors along with Prof. Noshir Contractor of the Department of Speech Communication (on study leave in Spring 2005), and developed with funding from the campus-wide Silicon Carbon Culture Initiative.

The course itself is an exercise in multidisciplinary collaboration, and like the instructors, students taking the course will be expected to work alongside those with different academic backgrounds in order to solve interesting and challenging problems.

What is the course about?

A growing number of researchers from many different intellectual traditions are realizing that networks are all around us, and that gaining an understanding of those networks will help in understanding bigger problems in the world.

Examples of networks include:

• The World Wide Web, where a web page links to other pages
• Scholarly publishing, where a research paper cites other papers
• Who knows what and who knows who in an organization
• Buddy lists in Instant Messaging services
• see http://www.cybergeography.org/atlas/ for more examples

But how can we understand the way a network works? How can we help it operate better if it is something we want to encourage (like sharing information across organizations), or weaken it if it is something we want to attack (like a terrorist network)?

As with many other problems, drawing a picture of the network can help in understanding what is going on, and help in spotting interesting aspects to understand in more detail. We could just draw diagrams on paper, or we could use computers to generate diagrams for us. With more advanced computing we are not even restricted to simple two dimensional visualizations on a regular computer monitor. We could create three dimensional visualizations using the techniques of virtual reality. We could use the CAVE (http://cavescheduler.ncsa.uiuc.edu/) to project these visualizations on the walls. We could use sound as well. That leads us to ask questions like:

• What would help people in visualizing networks?
• What would it feel like to literally “walk” around inside the data?
• Does it help to be able to move data around on a big screen, perhaps like in the science fiction movie ‘Minority Report’?

We don’t know the answers to those questions, but by working together through the semester, we will try and understand more about how to create new kinds of information visualization.

How will the course operate?

• We will read about relevant models and approaches from network analysis, human computer interaction and computer graphics.
• We will examine the state of the art in information visualization, knowledge representation, experimenting with and evaluating software designed for use with regular PCs, large 2D (wall) displays, and the 3D CAVE.
• We will create interdisciplinary student design teams, each of which will work on a project involving visualizing a specific network. The teams will analyze the information issues of their chosen network data, the kinds of things that people might want to be able to do with that data to aid understanding, and then prototype and test new tools for visualization and knowledge navigation.

Who can take the course?

You can take the course if you have some familiarity with one or more of the following (or related) subject areas: social network analysis, programming methodologies, graphic design, human perception and cognition, statistics, computer vision, computer speech analysis, computer graphics, or human computer interaction.

Given the nature of the work and the technology that we will be using, places are strictly limited. We wish to create a multidisciplinary group of students so that together they can draw on their different skills to solve new problems of visualization.

In order to create a good skill mix, admission to the course is by permission of the instructors. Please send an email to one of the instructors including brief details of your background, interests and relevant skills. A resume that you already have to hand is perfectly acceptable, as is a set of web pages you have created that describe some work you have done or reveal your design skills. Just make sure you clearly note your analysis, design and other skills as outlined above.

For more details, email one of the instructors.