CS 725/825 - Information Visualization and Visual Analytics
Spring 2021: Tues/Thurs, 11am-12:15pm, online/Zoom

Home (Syllabus)


  • Dr. Michele Weigle
  • mweigle at cs.odu.edu
  • Office Hours:
    Tues 4:30-6pm
    Thurs 3-4:30pm
    via Zoom


Resources at GitHub


  See previous course projects in the gallery

Course Overview

Catalog Description: This course covers the theory and application of information visualization and of visual analytics, the science of combining interactive visual interfaces and information visualization techniques with automatic algorithms to support analytical reasoning through human-computer interaction. Research on visual perception, cognition, interactive visual interfaces, and visual analytics will be covered. Practical techniques for the display of complex multivariate data will be addressed. Course projects will require the development of interactive web-based interfaces to analyze and visualize real-world datasets.

Main Activities: During the semester, students will develop interactive visualizations using D3.js, read academic papers from IEEE VIS and other top visualization conferences, give class presentations on current topics in information visualization and visual analytics, and gain hands-on experience in visualizing real-world datasets. Time will be reserved in the semester to cover special topics selected by the class.

Prerequisite: CS 625 (Data Visualization)

This is course is different than previous offerings of CS 725/825, which were offered before CS 625 was developed. CS 625 covers basic concepts in visualization, and this course is a natural followup. Because of this, CS 625, or significant comparable experience, is a required prerequisite. If you do not have this prerequisite, you must contact the instructor before registering for this course.

Course Delivery Method

All sections of this course will be delivered via Zoom web conferencing. Course materials, including the link to the Zoom class session, will be made available via Blackboard.

Class meetings will be held synchronously TR 11-12:15pm via Zoom. Attendance of the Zoom session during class meeting times is encouraged, but is not required. Recordings of the Zoom session will be available. All deadlines are based on the local timezone in Norfolk, VA.

CS 725 (MS) sections:

  • CRN 32303 - WEB2 (in Hampton Roads or in Virginia)
  • CRN 32302 - WEB7 (in the US, but outside of Virginia)

CS 825 (PhD) sections:

  • CRN 32305 - WEB2 (in Hampton Roads or in Virginia)
  • CRN 32304 - WEB7 (in the US, but outside of Virginia)

Instructor Contact and Office Hours

Dr. Michele Weigle: mweigle at cs.odu.edu, https://www.cs.odu.edu/~mweigle/

My office hours will be Tuesdays 4:30-6pm, Thursdays 3-4:30pm, or by appointment.

All office hours will be held via Zoom (see Blackboard for the link to the Zoom meeting room). Students may be placed into the waiting room until I am available. If you cannot attend during regular office hours, please contact me to set up an alternate appointment time.

Textbook and Materials

There is no required textbook, but Tamara Munzner's Visualization Analysis and Design (textbook from CS 625) is highly recommended if you don't already have it.

Other materials will include papers published via IEEE Xplore digital library (link here is via ODU libraries).

You will be required to write clearly about your visualization designs and design process. For writing help, I always suggest two inexpensive books:

  • Writing for Computer Science by Justin Zobel
  • The Elements of Style by Strunk and White

In addition, see the online writing resources collected on the ODU-CS New Student Resources page.


This will be a project and presentation based course, so no exams will be given. Grades will be based largely on visualization implementations and class presentations. More information will be provided before the semester begins.

Grading Scale

The grading scale is as follows:

% letter grade
94-100 A
90-93 A-
87-89 B+
84-86 B
80-83 B-
78-79 C+
74-77 C
70-73 C-
0-69 F

There is no separate grading scale for PhD students, but PhD students will typically be held to a higher standard.

Late Assignments

Any assignment submitted after its deadline is considered late. Late assignments lose 1 point for every 24 hours they are late. Submissions over 72 hours late are not accepted. This time limit includes weekends -- they are counted just like weekdays. I reserve the right to specify that late submissions will not be accepted for particular assignments.

  • 0-24 hours late: -1 point
  • 25-48 hours late: -2 points
  • 49-72 hours late: -3 points
  • over 72 hours late: not accepted

Summary Schedule

Note: This is a tentative schedule and may be updated during the semester. The complete schedule with assignments and due dates is posted on Blackboard.

ODU Spring 2021 academic schedule

Week Date Topic
1 Jan 19, 21 Syllabus, Course Intro
Data Vis Overview
2 Jan 26, 28 Visual analytics principles
Vega-Lite intro
3 Feb 2, 4 D3 data principles
D3 vis
4 Feb 9, 11 Handling complexity in data
IEEE VIS conferences, giving presentations
5 Feb 16, 18 Interactivity
Interactivity in Vega-Lite, D3
6 Feb 23, 25 Visualization dashboard design
Network visualization
7 Mar 2, 4 Tue: NO CLASS (Reading Day)
Project discussion
8 Mar 9, 11 Student Presentations
9 Mar 16, 18 Student Presentations
10 Mar 23, 25 Student Presentations
11 Mar 30, Apr 1 Student Presentations
Special Topics
12 Apr 6, 8 NO CLASS (work on projects)
13 Apr 13, 15 Student Project Demos
14 Apr 20, 22 Student Project Demos
15 Apr 27 Student Project Demos (if needed)

Final Schedule

Course Policies


Each student must join the class Piazza site with your ODU email address and check email daily. You should use Piazza to ask and answer general course-related questions. I will also use this to notify you about important updates (assignment deadline changes, class cancellations, office hours cancellations, etc.).


Since this is an online class, it is essential that you regularly stay involved in class activities. This includes attending synchronous class meetings when possible, checking the class website and Piazza for announcements, and submitting assignments on time. Online students who cannot attend synchronously are expected to have watched the posted videos of the week's in-class meetings before the next week's first meeting. However, students are strongly encouraged to watch the videos on the same day they are posted.

If there are days on which the scheduled class meeting time is cancelled, there may still be assignments made and due. A post will be made to Piazza (with an email notification) whenever the class meeting time is cancelled.

Make-up Work

Make-ups for graded activities are possible only with a valid written medical or university excuse. It is the student's responsibility to give the instructor the written excuse and to arrange for any makeup work to be done.

Disability Services

In compliance with PL94-142 and more recent federal legislation affirming the rights of disabled individuals, provisions will be made for students with special needs on an individual basis. The student must have been identified as special needs by the university and an appropriate letter must be provided to the course instructor. Provision will be made based upon written guidelines from the University's Office of Educational Accessibility. All students are expected to fulfill all course requirements.

Students are encouraged to self-disclose disabilities that have been verified by the Office of Educational Accessibility by providing Accommodation Letters to their instructors early in the semester in order to start receiving accommodations. Accommodations will not be made until the Accommodation Letters are provided to instructors each semester.

Seeking Help

Blackboard should be your first reference for questions about the class. If you have questions about course requirements or materials, post and answer questions using the class Piazza site.

The best way to get extra help is to attend office hours. If you cannot make office hours, please send an email to setup an appointment.

Academic Integrity

Old Dominion University is committed to students' personal and academic success. In order to achieve this vision, students, faculty, and staff work together to create an environment that provides the best opportunity for academic inquiry and learning. All students must be honest and forthright in their academic studies. Your work in this course and classroom behavior must align with the expectations outlined in the Code of Student Conduct, which can be found at https://www.odu.edu/oscai.

The following behaviors along with classroom disruptions violate this policy, corrupt the educational process, and will not be tolerated.

  • Cheating: Using unauthorized assistance, materials, study aids, or other information in any academic exercise.
  • Plagiarism: Using someone else's language, ideas, or other original material without acknowledging its source in any academic exercise.
  • Fabrication: Inventing, altering or falsifying any data, citation or information in any academic exercise.
  • Facilitation: Helping another student commit, or attempt to commit, any Academic Integrity violation, or failure to report suspected Academic Integrity violations to a faculty member.

In particular, submitting anything that is not your own work without proper attribution (giving credit to the original author) is plagiarism and is considered to be an academic integrity violation. It is not acceptable to copy source code or written work from any other source (including other students, online resources), unless explicitly allowed in the assignment statement. In cases where using resources such as the Internet is allowed, proper attribution must be given.

Any evidence of an academic integrity violation (cheating) will result in a 0 grade for the assignment/exam, and the incident will be submitted to the Department of Computer Science for further review. Note that academic integrity violations can result in a permanent notation being placed on the student's transcript or even expulsion from the University. Evidence of cheating may include a student being unable to satisfactorily answer questions asked by the instructor about a submitted solution. Cheating includes not only receiving unauthorized assistance, but also giving unauthorized assistance. For class files kept in Unix space, students are expected to use Unix file permission protections (chmod) to keep other students from accessing the files. Failure to adequately protect files may result in a student being held responsible for giving unauthorized assistance, even if not directly aware of it.

Students may still provide legitimate assistance to one another. You are encouraged to form study groups to discuss course topics. Students should avoid discussions of solutions to ongoing assignments and should not, under any circumstances, show or share code solutions for an ongoing assignment.

All students are responsible for knowing the rules. If you are unclear about whether a certain activity is allowed or not, please contact the instructor.

More information on academic integrity is available on the ODU-CS academic integrity page.