Syllabus (brief)

by Mike Gleicher on January 16, 2015

I always thought a “syllabus” was a description of the topics covered in class.

But, it is actually a more general discussion of official information about the class. (see for the university’s definition).

This brief syllabus has the basic info. Really the course web is the syllabus, and most topics here are discussed in more detail somewhere (links provided from this document – although this document is written first, so that the links may appear later). In general, you should look at the “Course Policies” topic (which has lots of articles), the individual postings about readings, and the “Class Schedule.”

Basic Info:

Course Name and Number:

CS638: Data Visualization
CS838: Data Visualization

There are, technically two separate classes that meet together and have overlapping assignments, readings, and activities. Grading will be done separately for each class. Unless otherwise specified, all information applies to both classes.

The course numbers (638, 838) are the “Topics in Computing” – the generic numbers we use for new classes that haven’t gotten their own numbers yet.

Instructional Staff:

Michael Gleicher, Professor, Computer Sciences
Office: 6385 Computer Sciences
Office Hour: Tuesday 2-2:45, Wednesday 11-11:45, or by appointment
Preferred contact is by email: gleicher[at]

Alper Sarikaya, Graduate Student, Computer Sciences
Lab: 1347 Computer Sciences (Graphics Lab)
Office Hour: Monday 11a-12p, Thursday 1p-2p, or by appointment
Preferred contact is by email: sarikaya[at]

Class Meetings:

Tuesday and Thursdays, 11:00 am–12:15 pm
Room 1221, Computer Sciences

Note: this room has tight aisles, and we will be filling most chairs. If you come late, you will be climbing over other students to get to a chair. So please come on time!

Also note: students are required to come to class.

Exam Period:

Monday, May 11, 2015, 5:05 pm–7:05 pm.
We probably won’t have a final exam, but I reserve the right to schedule something in that timeslot.

Main Topics: (see the detailed schedule for more information)

  • Motivations for visualization and the types of visualization
  • Data and Task Abstractions
  • Evaluation, Validation, and Design Process
  • Human Perception, and its impact on Design
  • Encodings and Layout
  • Graphs, Networks, and Multi-Variate Data
  • Clutter and Dimensionality Reduction
  • Experiments and statistics (for visualization, and visualization for)
  • Animation and Motion
  • Scientific Visualization
  • Depicting 3D

Learning Outcomes:

  • Students will understand the potential of effective data visualization.
  • Students will understand the key principles for the design of effective visualizations.
  • Students will be able to design and evaluate data visualizations for a variety of tasks.
  • Students will understand the relevant basics of visual perception and its role in designing.
  • Students will understand some standard visualization methods and their applicability.
  • (838 only) Students will gain exposure and practice with some of the skills required to be a researcher and practitioner inthe field of Visualization.

Things that we will not do (Non- Learning Outcomes):

We will not teach students about implementation of visualization systems.
We will not teach students to use specific visualization systems.

Text and Readings (summary, see the other postings)

There are two textbooks: Munzner’s Visualization Design and Analysis and Ware’s Visual Thinking for Design. Both are available online via the library.

There will be many other readings distributed via the web. There will be a combination of book chapters (provided under terms of academic fair use), research articles, and web pages.

How Students will be evaluated (class activities – see specific postings about types)

  • Participation / In-Class Activities: We will not grade participation in the usual sense (speaking and interacting in class). Participation will be assessed via in-class activities.
  • Reading: There will be a substantial amount of reading for this class. Most readings will have small online assignments that will give you a chance to demonstrate that you have done the readings and learned something from them.
  • Online Discussion: There will be assignments where your job is to participate in an online discussion. Generally, we will break the class into small groups and each group will have a separate discussion.
  • Seek and Find: You will be asked to find an example of a visualization (generally on the web) that satisfied some criteria, and to answer a question or two about it. Generally, the critiques will happen seperately.
  • Design / Re-Design Challenges: You will be asked to make a visualization that solve a problem: either from scratch, or based or to improve an existing visualization.
  • Peer Evaluation: (838 only) students will be required to evaluate their peers (and assessed on their ability to do so).
  • Summative Assessments: I do not plan on having a traditional exam in this class (but I reserve the right to have a take home final). However, we will have an activity that requires you to review what you’ve learned. (the benefit of an exam is that it forces you to review and internalize the material – but hopefully, we can find less painful ways to make that happen).

All activities will be considered in determining the final class grade.


The two sections (638/838) are graded independently.

Grading Standards:

Students who successfully complete most assignments will earn a B. Earning a better grade will requiring doing better than just “succeeding” at the assignments.

We will use a curve at the end of the class. If fewer than 10% of the class does not meet our absolute standard, we will shift grades accordingly. Of course, more than 10% of a class can earn As. If too few people earn As, its the staffs mistake (we didn’t teach well enough). If the entire class earns As, we have an exceptional class (don’t laugh – it has happened!).

Course Infrastructure (summary – see infrastructure posting)

We will use email to the students email address for individual communications.

We will use the university provided class mailing list (to students’ mailing lists) for announcements. However, the class web will be the primary mechanism for announcements.

The class web will be the primary source of information on the class, and students are required for its content. The website provides a facility to send email notifications of new information. You must sign up for this if you prefer this mechanism.

We will use Canvas as the course management system. Students will be required to submit assignments there, as well as to participate in online discussions.

We will provide readings online through a protected reader (web access only to students in the class) to comply with academic fair use standards.

Course Policies (summary – see postings):

Software and Computing:

Students will be expected to be able to use basic computing software (a spreadsheet, a presentation preparation program, …). Using more advanced tools (for software development, data analysis, statstical analysis, etc.) is optional.

For students interested, Tableau has made their software available to the class through the Tableau for Teaching program. Tableau’s data visualization software is provided through the Tableau for Teaching program. Use of this software is optional.

You can use computers in the CS computing labs if you need to. Contact course staff to make arrangements. It’s probably best if you use your own computer (if you have one), or at least one you have more convenient access to.


Print Friendly, PDF & Email

Previous post:

Next post: