CS 725/825 - Information Visualization
Spring 2015: Tuesdays, 9:30am-12:15pm, E&CS 2120

Print - Admin

Home

Staff

Syllabus

Paper Presentations

Project
  Demo Schedule

Examples

Links


Tableau's data visualization software is provided through the Tableau for Teaching program.

Syllabus

Updates:

  • only top-rated post (or 2-way tie) gets bonus points -MCW 1/29/15
  • all presentations will be individual -MCW 1/14/15
  • adjustments to vis examples notes (subsets of students instead of 10-11, 3-way (or more) tie will result in no extra credit points) -MCW 1/14/15
  • grading section adjusted and filled in with more detail -MCW 12/19/14

Course Overview

"The purpose of visualization is insight, not pictures." -Ben Shneiderman

The main goal of this course is to equip you with the background and tools needed to develop effective visualizations in your own research and future work. Part of developing effective visualizations requires analyzing existing visualizations and visualization problems. One important piece of developing an effective visualization is knowing what not to do. In addition to studying recommended approaches, this course should also prepare you to rule out visualization approaches where there are mismatches in human capabilities or perception or mismatches with the intended task.

In particular, after completing this course, you should be able to do the following:

  • Explain at a high-level the "what-why-how" framework for analyzing visualization use.
  • Given a visualization, identify the actions the vis allows and the targets of those actions.
  • Transform domain-specific tasks into the task abstraction framework.
  • Given an academic paper, identify the presence or absence of the four levels of vis design and validation.
  • Describe the channels of visual encoding and order them from most effective to least effective.
  • Identify a visualization where an inappropriate arrange design choice was made and explain why the choice was inappropriate.
  • Explain the importance choosing an appropriate colormap.
  • Use R, D3, and Tableau to create simple visualizations.
  • Use D3, Tableau, or another toolkit to create an effective interactive web-based visualization of real-world data.

Note that there is a distinction between information visualization and scientific visualization (which we will not study). Scientific visualization focuses on data that has a real, physical representation, such as structures in the human body. Information visualization deals with ways to represent abstract data.

This course will be organized based on the "flipped classroom" model. Students will be assigned readings and homework that will be due before class time. There will be few, if any, lectures by the instructor. Class time will be spent on discussions of the assignments, student presentations, and in-class assignments. It is essential that each student be fully prepared to participate in class discussions each week.

Announcements, assignments, outside-class discussion, and grading will be done on the class Blackboard site.

Requirements

Prerequisites

There are no specific course prerequisites for this course. But, I expect you to be comfortable learning new programming languages/tools/APIs and be familiar with Unix. If you need a refresher, see the CS 252 webpage.

Course Materials

The required textbook for this course is Visualization Analysis and Design by Tamara Munzner.

There are several other useful books that you might want to refer to:

We will also be studying academic papers in the field of information visualization. These papers are typically available through the ACM Digital Library (off-campus) or IEEE Xplore (off-campus). You can also usually append proxy.lib.odu.edu to the host part of an ACM DL or IEEExplore URI to get access off-campus.

Most weeks, we will be doing in-class programming exercises. Each student must bring a laptop or work with other student(s) who have a laptop.

Course Policies

Grading

There are 200 points available for the semester. Your grade in this class will be based on the following components:

  • participation - 50 points
  • homework assignments - 50 points
  • presentation - 40 points
  • project - 60 points

Participation - 50 points

  • in-class discussions - 26 pts
    • based on answering questions in class related to the learning checks, vis examples, and discussion questions
    • be prepared, I'll call on students at random
    • rubric: 0 - absence or no answer, 1 - satisfactory answer, 2 - strong answer
    • semester points = (sum of points / # questions asked) * 13
  • in-class work - 24 pts
    • participation in in-class assignments (requires attendance of class) and completion of in-class assignments after class (12 weeks)
    • rubric: 0 - absence or no work, 1 - work in class, but not completed, 2 - work completed before the next class

Homework Assignments - 50 points

  • submission of learning checks - 26 pts
    • rubric: 0 - not submitted, 1 - answered some questions or answered all but late, 2 - answered all questions
  • submission of visualization examples - 8 pts
    • 4 vis example submissions (subsets of students post each week)
    • can contribute in off weeks for extra credit (at most 4 points of extra credit and only if has submitted in all of assigned weeks)
    • rubric: 0 - not submitted, 1 - example given, but missing URL, image, or explanation, 2 - all components included
    • +2 bonus for top rated post (if there's a 3-way (or more) tie, no one gets the extra points, only assigned students eligible for top-rated bonus) - update: only top-rated post (or 2-way tie) gets bonus points -MCW 1/29/15
  • submission of blog articles - 16 pts
    • 8 blog article submissions (could be done at any time, but no more than 3 in one week)
    • rubric: 0 - not submitted, 1 - article provided, but duplicate or no comment provided, 2 - unique article with brief comment

Presentation - 40 points

  • present an academic paper to class in 15-20 min
  • CS 725 groups of 2, CS 825 individually - update: all students will present individually -MCW 1/14/15

Project - 60 points

  • demo - 40 points
  • paper - 20 points

The grading scale is as follows:

points % letter grade
188-200 94-100 A
180-187 90-93 A-
174-179 87-89 B+
168-173 84-86 B
160-167 80-83 B-
156-159 78-79 C+
148-155 74-77 C
140-147 70-73 C-
0-139 0-69 F

Late Assignments

Any assignment submitted after its deadline is considered late. Submissions over 48 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.

Typical In-Class Agenda

  • Admin, Intro/overview/objectives of topic
  • Discuss learning checks
  • Discuss confusing points (addressed anonymously)
  • Discuss visualization examples
  • Discuss discussion questions
  • Student presentation
  • In-class assignment
  • Wrap-up, Point to next topic

Attendance

Since much of the course is based on class discussion, I expect you to attend class and to arrive on time. Your grade may be affected if you are consistently tardy. If you have to miss a class, you are responsible checking the course website to find any assignments or notes you may have missed. Students may leave after 15 minutes if the instructor or a guest lecturer does not arrive in that time.

Group Work

Some assignments may be done in groups -- consisting of 1 or 2 people. Groups exist solely on the mutual agreement of both parties. At any time, if either member wishes to dissolve the group, the group will be split. No new teams can be formed after the first group assignment is due. Members of the split group will have access to the shared code base.

Email

Students should signup for the class email list. You do not have to use an ODU email address -- sign up with any email address that you would check daily. I will use this list to send out important updates (assignment deadline changes, class cancellations, office hours cancellations, etc.)

Classroom Conduct

Please be respectful of your classmates and instructor by minimizing distractions during class. Cell phones must be turned off during class.

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. A makeup exam may be different (and possibly more difficult) than the regularly scheduled exam.

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.

Seeking Help

The course website and the class Blackboard site should be your first references for questions about the class.

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

I am available via email, but do not expect or rely on an immediate response.

Academic Integrity / Honor Code

By attending Old Dominion University you have accepted the responsibility to abide by the honor code. If you are uncertain about how the honor code applies to any course activity, you should request clarification from the instructor. The honor pledge is as follows:

"I pledge to support the Honor System of Old Dominion University. I will refrain from any form of academic dishonesty or deception, such as cheating or plagiarism. I am aware that as a member of the academic community, it is my responsibility to turn in all suspected violators of the Honor Code. I will report to a hearing if summoned."

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 honor code violation. It is not acceptable to copy source code or written work from any other source (including other students), 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 honor code 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 honor code violations can result in a permanent notation being placed on the student's transcript. 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.