CS 171: Visualization (New!)

Spring 2008 (January 30, 2008 through May 16, 2008)
Undergraduates and Graduates

Lectures: M and W, 1:00-2:30 PM, 1 Story St., Room 304
Sections: F, 1:00-2:30 PM, 1 Story St., Room 304 (not mandatory, only when announced)

Instructor: Hanspeter Pfister (pfister@seas.harvard.edu)
TF: Miriah Meyer (miriah@seas.harvard.edu) Office hours by appointment only

This class is also offered as through the Harvard Extension School as distance education course CSCI E-64. All lectures will be recorded on video and put online.

Quick links:   Course Info   Requirements  Schedule & Lectures   Videos   Homeworks   Projects  Resources  

Announcements

Course Info

Description: The amount and complexity of information produced in science, engineering, business, and everyday human activity is increasing at staggering rates. We must increasingly rely on computational approaches to generate abstractions that help us to gain insights into large collections of data. The field of visualization seeks to answer questions about science and humanity by developing methods that transform data into meaningful, perceptually intuitive representations. Good visualizations not only present a visual interpretation of data, but do so by improving comprehension, communication, and decision making.

The goal of this course is to expose students to visualization methods and techniques that increase the understanding of complex data. The course will cover how the human visual system processes and perceives images, good design practices for visualization, tools for visualization of data from a variety of fields, and programming of interactive visualization systems. The course is targeted both towards students interested in using visualization in their own work, and students interested in building better visualization tools and systems.

Topics: (subject to change)

• 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

Grading: Students will be graded on participation (in-class and/or online), four homework assignments, a mid-term examination, and a final team project and presentation. The final grade will be composed as follows:

Class Participation................................................................ 10%
Homeworks......................................................................... 40%
Mid-Term Exam................................................................... 20%
Final Project........................................................................ 30%

Mailing List and Message Board: Students need to subscribe to the class message board on Google groups. This is mainly your forum: use it to ask questions, discuss problems, and help each other out.
To subscribe: http://groups.google.com/group/cs171 We will send an invitation to join the group by email. If you already have a Google account we recommend that you ignore this invitation and use your Google account to apply for a membership.
To post a message: cs171@googlegroups.com
For help go here.

Live & Archived Video Feeds: The class will be recorded and broadcast with live video feeds to better support our distance education students. Here is the link to the live video feed - it will work only while the lecture is being recorded. One of the instructors will be online in a Skype chat room with the account name cs-171 so that distance students can ask questions during class (see below for more details). The archived videos of the lectures are available about two days later.

Skype Chat Room: If you are a distance ed student, you can participate in class via the Skype chat room. Download and install the Skype software on your computer. When you first launch Skype, it will prompt you to create a new Skype account if you don't already have one. Skype accounts are free. Once you're logged in, add the user cs-171 to your contact list. During class hours, we will add you to a public chat room where you can type your questions and comments.

Homework Late Day Policy: Each student is given two "late days" at the beginning of the semester. You can use a late day to submit any regular homework assignment up to 24 hours after the due date without penalty. Late days are intended to give you flexibility: you can use them for any reason (e.g., if you are sick, out of town, or have a particularly busy week). You can either choose to use two late days on a single homework (allowing you to submit up to 48 hours after the original due date without penalty), or one late day each on two different homeworks. However, you only get two late days for the whole semester, so please use them wisely! You don't get any bonus points for not using your late days. Also, you can't use late days for your final project (i.e., the final project deadline is absolute). Homework submissions will not be accepted after Noon EST on the Wednesday following the deadline.

Academic Honesty: You absolutely must acknowledge any source code that was not written by you by mentioning the original author(s) directly in your source code (comment or header). You can also acknowledge sources in a README.txt file if you used whole classes or libraries. Do not remove any original copyright notices and headers. Without prior written approval by the instructor you may not submit the same material to two courses. Plagiarism, cheating, and other forms of academic dishonesty will be reported to the office of the Dean and can have very serious consequences. For more information see the SEAS and Harvard Extension School academic guidelines.
 

Requirements

Prerequisites: You will get the most out of this course if you:

• have some programming experience (e.g., CS 50 or QR 20)
• have taken an introductory math course (e.g., Math 1a or Math 1b)

Exceptions by permission of the instructor.

Books: The required textbooks for the course are:

	Show Me the Numbers, by Stephen Few, Analytics Press, ISBN: 0970601999 Few does a great job of explaining the design concepts of good graphs and charts. The book is easy to read and full of examples.
	Visualizing Data by Ben Fry, O'Reilly (2007), ISBN: 0596514557 Using Processing, a free programming environment developed by the author, Visualizing Data demonstrates visualization methods for the Web and elsewhere, complete with user interaction and animation.

We recommend (but do not require) the following books:

• Processing: A Programming Handbook for Visual Designers and Artists,
  by Casey Reas and Ben Fry (The MIT Press, ISBN 0262182629)
• The Visual Display of Quantitative Information, 2nd ed., by Edward Tufte (Graphics Press, ISBN 0961392142)
• Envisioning Information, by Edward Tufte (Graphics Press, ISBN 0961392118)

Required Software: Registered students will be provided with all the required software in the course, including educational licenses for some commercial visualization tools.

Schedule

Note that the following schedule is subject to change.

Lectures

Homeworks

Homework 2 (due Wednesday, March 12 at noon EST)

Homework 3 (due Wednesday, April 2 at noon EST)

Homework 4 (due Wednesday, April 23 at noon EST)

Final Projects

Final Projects (due Friday, May 9 at noon EST)

Final Project Presentations (due Sunday, May 11 at noon EST)

Final Project Presentation schedule (with screencasts)

Project Web Pages

Resources

Here are some good online references:

• OpenGL.org (OpenGL shading language, OpenGL 2.0 specification)
• The OpenGL Programming Guide (Red Book): This online version of the classic OpenGL tutorial/reference covers version 1.1 of GL. This isn't the latest version of GL, but it has all the information you need to learn/review GL basics, such as transformations, lighting, and texture mapping.
• OpenGL command reference: these online man pages are very handy when you need to look up a particular GL command. (Do you really remember all the arguments for glTexImage2D??)

• Processing: The open source programming language and environment.
• vtk: The Visualization Toolkit
• itk: The Insight Toolkit for segmentation and registration
• blender: Open source 3D modeling tool
• GLUT (for Windows): the OpenGL Utility Toolkit (GLUT) for building user interfaces
• G3D: a commercial-grade 3D Engine available as Open Source (BSD License)
• Python download
• Regular Expression Checker
• Introduction to Python & Regular Expressions
• Beautiful Soup documentation

Acknowledgments

• Maneesh Agrawala, UC Berkeley
• Pat Hanrahan, Stanford
• Tamara Munzner, University of British Columbia, Canada
• Penny Rheingans, University of Maryland Baltimore County
• Ben Shneiderman, University of Maryland
• John Stasko, Georgia Tech
• Lynn Stein, Olin College of Engineering
• Maureen Stone & Polle Zellweger, University of Washington
• Roger Crawfis, Ohio State University