Course Syllabus

MSAN 622 Information Visualization

Spring 2015 • Module II
Tuesday, Thursday • 3:00pm – 4:50pm
Friday • 3:00pm – 3:55pm (Section 1)
Friday • 4:05pm – 5:00pm (Section 2)
101 Howard, Room 529

This course will address basic data visualization techniques and design principles. Students will use R with the ggplot2 and shiny packages D3 to prototype visualizations. Students will obtain practical experience with the visualization of complex data, including multivariate data, geospatial data, textual data, time series, and network data.


Please contact the instructor if you have any questions or concerns regarding the course or projects.

Professor Sophie Engle
Harney Science Center, 5th Floor, Room 531/532
Monday, Wednesday • 1:00pm – 2:00pm

If you are unable to make these office hours, please contact the instructor to setup an appointment.


Please contact the teacher assistant for all homework-related matters.

Wentao (Victor) Du

The teacher assistant is not required to hold office hours.


You must have completed MSAN 501, 593, and 692 with a grade of C or better.


There are no books required for this class. However, the following are recommended:

These books may be available freely online for USF students through the library and Safrai Books Online. Check there before purchasing anything.


Announcements will be posted on the course website in Canvas at:

Canvas has multiple options for automatically notifying you when new announcements are posted. Students are responsible for staying current on all course announcements.


At the end of this course, students should be able to:

  • Understand basic data visualization terminology
  • Understand and create basic charts and plots
  • Design and implement interactive, multivariate, text, and temporal data visualizations
  • Evaluate data visualizations
  • Rapidly prototype visualizations using D3


The following is an estimated list of topics and weekly schedule. Check the course website for the latest schedule.

Week Principles Techniques
1 (03/24) Terminology Environment Setup
2 (03/31) Perception Introduction to D3
3 (04/07) Interactivity Multivariate Data
4 (04/14) Evaluation Temporal Data
5 (04/21) Projections Geospatial Data
6 (04/28) Trees and Graphs Hierarchical Data
7 (05/05) Prototype Evaluation
8 (05/12) Final Project Presentations

A final project will be assigned instead of a final exam. Details will be posted toward the end of the semester.


Lectures will consist of slide presentations, code demonstrations, discussions, and in-class exercises. Students will be required to complete a mix of participation exercises, homework assignments, and projects. The breakdown will be as follows:

20%  Participation
30%  Homework
50%  Project

See the following sections for additional details on each category.


There will be weekly participation assignments. These may include contributing to in-class discussions or exercises, or commenting on prototypes from other students. These exercises are graded on a pass/fail basis.


There will be several programming homework assignments, assigned on a weekly basis. This may include evaluating and reworking existing visualizations, using existing tools to design visualizations, and prototyping custom visualizations.

Homework will be submitted via a combination of GitHub and Canvas.


Students will be assigned a final visualization project. For the final project, students will select a data set and multiple visualization techniques, develop prototypes, and rework the prototypes based on peer evaluations. Students will demonstrate their final projects during a presentation or poster session.


Letter grades will be assigned according to the following scale:

A+  ≥  97%
A  ≥  94%
A–  ≥  90%
B+  ≥  87%
B  ≥  84%
B–  ≥  80%
C+  ≥  77%
C  ≥  74%
C–  ≥  70%
F  <  70%

For example, you will receive a C letter grade if your grade is greater than or equal to 74% and less than 77%. Please note this scale is subject to change.

There is no D letter grade for graduate students. See the Graduate Student Regulations for more information about letter grades and how they are translated into GPA.


Attendance Policy

Students are expected to be on-time to all classes. Attendance is mandatory for all lectures, discussions, exercises, and presentations.

Late Policy

All deadlines are firm. No late assignments will be accepted. Exceptions to this policy are made only in the case of verifiable medical or family emergency. Extensions must be arranged PRIOR to the original deadline unless in case of extreme emergency (such as an emergency room visit).

Academic Honesty

All students are expected to know and adhere to the University of San Francisco's Academic Honor Code. Go to for details. The first violation of the Honor Code will result in an automatic 0 on the offending assignment. Repeat violations will be handled in accordance with the MSAN program policies.

Simply put, do not cheat and do not plagiarize. This includes copying code from the web, copying code from other students, working too closely with other students (all work in this class must be done individually), or having anyone other than yourself write your code. If you produce the same code as anyone else (or posted anywhere else), you are not putting in enough individual effort and independent thought into your the work.

Student Disability Services

If you are a student with a disability or disabling condition, or if you think you may have a disability, please contact Student Disability Services (SDS) within the first week of class to speak with a disability specialist. If you are determined eligible for reasonable accommodations, your disability specialist will send your accommodation letter to the instructor detailing your needs for the course. For more information, please visit or call (415) 422-2613.

Course Summary:

Date Details Due