CS 7250 — Information Visualization: Theory and Applications

Spring 2021 Syllabus

Instructor: Prof. Cody Dunne
Homepage: c.dunne.dev/cs7250s21/ (make sure to log in to Canvas)
Time and location: T/F 3:25 pm – 5:05 pm Eastern online.

See the Online Learning Instructions for more important details on taking CS 7250 online.

Zoom: c.dunne.dev/cs7250s21/zoom
See the links on your Canvas Calendar or the "Zoom Meetings" item in the menu. Let us know if any of these options do not work for you, and try one of the others.
Microsoft Teams: c.dunne.dev/cs7250s21/teams
Persistent text notes and live troubleshooting will be in the Lectures channel.

Welcome to CS 7250! Perhaps you are taking this course to fulfill a requirement, or maybe you’re simply interested in the *magical* world of data visualization. Either way, CS 7250 provides students with not only theoretical knowledge about data visualization best practices, but a chance to get their hands dirty and create their very own visualizations.

Silly xkcd visualizations.
Image credit: xkcd.

Office Hours and Contact Info

Post general questions as a Canvas discussion 💬; send personal questions by email to codydunne-and-tas@ccs.neu.edu 📧. We will likely not answer questions posted in Teams outside of class or office hours.

🔗Make sure to include links to your Canvas submission, GitHub repo, or anything else relevant! It's hard to debug code without seeing it.

We encourage you to ask questions early and often when things are unclear.

A Google Calendar showing the office hours each week is available here. Office hours will be conducted via Khoury Office Hours and using Teams for one-on-one video calls. Please see the student instructions and demo video for an introduction.

Instructor: Prof. Cody Dunne
Email: codydunne-and-tas@ccs.neu.edu (cody.g.dunne@gmail.com only if your email is confidential.)
I will make my best effort to respond within 24 hours, excluding Thurs./Sat./Sun. or hours outside 9:15 am – 6:00 pm.
Office hours: F 5:05 – 6:05 pm Eastern on Khoury Office Hours.
Fun fact: I like pretty pictures that tell you something about data!
Teaching Assistant 1 (Primary): Girik Malik, PhD student in CS
Email: codydunne-and-tas@ccs.neu.edu (malik.gi@northeastern.edu)
Office hours: M 10:00 – 11:00 am Eastern on Khoury Office Hours.
Fun fact: My final project from this course ended up in a formal meeting where they made decisions using our visualizations!
Teaching Assistant 2: Sara Di Bartolomeo, PhD student in CS
Email: codydunne-and-tas@ccs.neu.edu (dibartolomeo.s@northeastern.edu)
Office hours: T 1:15 – 2:15 pm Eastern on Khoury Office Hours.
Fun fact: I actually like JavaScript.
Teaching Assistant 3: David Saffo, PhD student in CS
Email: codydunne-and-tas@ccs.neu.edu (saffo.d@northeastern.edu)
Office hours: R 2:00 – 3:00 pm Eastern on Khoury Office Hours.
Fun fact: During lockdown, I became a middling pizzaiolo.
Service-Learning TA: Sophia Gunzburg, BS student in Behavioral Neuroscience
Email: codydunne-and-tas@ccs.neu.edu (gunzburg.s@northeastern.edu)
Office hours: By appointment only (email to set up).
Fun fact: I know how to code in R!
Library Visualization Specialist: Kate Kryder, Research Data Analyst
Email: k.kryder@northeastern.edu
Office hours: In Zoom by appointment (schedule here).
Kate is happy to help with D3 debugging.
Fun fact: Students who visit me often refer to the D3 Reusable Chart Model as the "Cody code."

Course Description

This course:

Covers foundational as well as contemporary topics of interest in data visualization to enable the effective representation of data across disciplines.
Includes examples drawn from computer science, physical sciences, biomedical sciences, humanities, and economics.
Topics include data visualization theory and methodology, visualization design and evaluation, visual perception and cognition, interaction principles, and data encoding and representation techniques.

Students will create visualizations in Tableau, as well as using Python and open web-based authoring libraries. The course requires programming in Python, JavaScript, HTML, and CSS, as well as extensive writing, including documentation, explanations, and discussions of the findings from the data analyses and visualizations.

Learning Outcomes

Data visualization is useful in a multitude of fields, from business to science to media. Hopefully, you will be able to take what you learned in this course and apply it to future jobs and projects.

After completion of the course students should be able to:

Assess the quality and effectiveness of a visualization heuristically as well as through standard evaluation techniques.
Choose appropriate visualization methods for a given data type.
Design an effective visualization by applying design and human perception principles.
Implement a static or interactive visualization.
Implement interactivity functions to enable data exploration and analysis.
Implement web-based visualizations in D3/JavaScript/HTML/CSS.
Create visualizations in Tableau.
Write, present, and be knowledgeable about contemporary visualization topics.

Prerequisites

There are no prerequisite courses. Familiarity with topics such as Human-Computer Interaction (HCI), web development, databases, and data mining is very useful for the course but not a required prerequisite.

Don’t worry if you have no prior experience with programming languages like JavaScript (i.e., D3) and Python, tools like Tableau, or web design in general. Assignments, projects, and lectures throughout the semester should get you acquainted. However, students should be comfortable with learning new programming languages independently — and asking for help early.

Textbooks

Required

Exciting news: This course utilizes one free textbook that covers basic visualization theory and methodology.

Visualization Analysis and Design by Tamara Munzner (** Free PDF online via Northeastern).

Recommended

Although not required, the following books are recommended as additional references to help expand on the visualization theory and skills discussed in class. These books may be cited and referred to during lecture as appropriate to help direct the students to the appropriate resource.

Design for Information by Isabel Meirelles
The Functional Art: An introduction to information graphics and visualization by Alberto Cairo
Information Visualization: Perception for Design by Colin Ware
Interactive Data Visualization for the Web (2nd edition) (website) by Scott Murray. Note that Scott uses D3 v.4, which is out of date.
The Visual Display of Quantitative Information by Edward Tufte

Required Supplies

We will do a lot of visualization sketching and design iteration in this course. Always have the basics, so you can participate effectively:

At least five different colors of pens—e.g., Pilot G2 packs 31128 and 34405—or pencils (with sharpener).
Plenty of white or near-white drawing paper. E.g., Strathmore 25-005 or 400-2 drawing notebooks, heavyweight white index cards, or even 8.5x11" printer paper.

We specify paper, rather than digital tools, for design sketching, as we have found that digital drawing tools tend to limit the breadth of student creativity and slow down design iteration.

We will also do programming and writing activities. You should always have:

A laptop suitable for programming and its charger. For the few days we are using Tableau in class, you will need Windows or OSX to run it. Be prepared to borrow a laptop or run one of those in a VM.

If you do not have the required supplies when they are needed your participation grade for the day will be marked as 0.

Course Components

For any class, you should plan to spend approximately three hours outside of class for every hour of class time (i.e., 10 hours per week).

Lectures

Most classes will be split into two parts: lecture and in-class activity. The lecture component will cover foundational topics, and the remainder of the class will be devoted to an in-class activity to further explore topics and skills relevant to the course topics. Activities will include programming tutorials, design critiques, journal paper discussions, in-class programming and data analysis, and student-led final project presentations. Lecture slides are available here, generally within a few days after class.

Class Participation

Students are expected to participate both in-class as well as online through the course’s discussion group. A student’s overall participation grade (see Final Grade below) will be composed of their in-class participation and reading quiz grades (see Readings below). As the course is based heavily on in-class discussions and activities, student participation is essential to the course. Plus, when we all participate, it makes our time together that much more interesting.

Class attendance is required due to the heavy emphasis on in-class activities, and a student’s participation grade will be negatively affected by absences and tardiness. Absences may be excused by the instructor with advance notice. Absences will only be approved after the fact in cases of medical necessity.

Readings

Assigned reading will be given to read in advance of each class, and will also be part of some assignments. Readings will be listed in the Course Schedule online. They will be drawn from the required textbook as well as other freely available online material.

Reading Quizzes

To ensure students complete the assigned reading and retain the key concepts required to fully participate in-class, short reading quizzes will be given at the start of many classes. Quiz grades will count toward each student's Participation grade. Quizzes will be given near the start of class and will not be available to tardy students. You will not know in advance when quizzes will happen or how many quizzes there will be total.

Homework

There will be regular homework assignments. Each assignment will require the student to apply the concepts discussed in the readings and in-class lectures to both programming assignments for the actual building and implementation of static and interactive visualizations as well as short writing assignments (e.g., design critiques). The homework assignments are an individual assessment and should not be completed in groups.

Experiential Learning Final Project

Over the course of the semester, students in the class will work together with real users to analyze and visualize their data. There will be mandatory project deadlines and associated assignments throughout the semester. Some of the project assignments will be done individually, and others in small groups. The required project milestones and deliverables will be incorporated into, or sometimes replace, the weekly homework assignment.

The experiential learning project will give students exposure to real data, interaction with real users, and provide the opportunity to conduct novel data analysis and visualization. Students will be required to produce an interactive web-based visualization and associated website to host the visualization, a demo video, presentation, research paper, and other project deliverables.

Students will identify and propose their own experiential learning partners, which means you get to pick a topic tailored to your own interests. More instructions will be provided in the initial project assignments.

See more details of the project in the Project Overview.

Final Grade

Grades will be posted on Canvas with a running total grade weighted by assignment type as detailed on Canvas at the bottom or side of the Course Schedule. Final letter grades will be based on this weighted total using this scheme:

Name:	Range:
A	100%	to	93%
A-	< 93%	to	90%
B+	< 90%	to	87%
B	< 87%	to	83%
B-	< 83%	to	80%
C+	< 80%	to	77%
C	< 77%	to	73%
C-	< 73%	to	70%
F	< 70%	to	0%

There will be no rounding. E.g., 92.999% is still less than 93% and thus an A-. This is to encourage fair grading by reducing the effect of emotional appeals to the instructor, which not all students would feel comfortable making.

In general, the term "reduction of one letter grade" refers only to the letter and not the +/-. E.g., an A would become a B and not an A-. Likewise for reductions of more than one letter grade.

Changes to the final course grade must be requested in an email to the instructor within one week of receiving the grade. The request should contain a technical explanation of why re-grading is necessary. If the instructor approves the request, all work including assignments, participation, and the project will be re-graded to determine the new grade. The new grade can potentially be lower than the original grade.

There will be no pass/fail grading this Spring, even if Northeastern switches to entirely online instruction!

For details about individual assignment grading, rather than the final course grade, see Course Policies below.

Course Policies

Late Policy

All homework and project related due dates are final and provided in the course schedule. No assignments will be accepted for credit after the deadline. Homework and project assignments are usually due at 11:59 pm Eastern Time on Thursdays. The late policy is implemented automatically by Canvas, so 11:59:01 pm would still be considered late.

If you have a verifiable medical condition or other special circumstances that interfere with your coursework, please email the instructor as soon as possible to discuss your options.

If you have a major conference/journal paper deadline or conference presentation that interferes with your coursework, email the instructor at least three weeks in advance to discuss your options. We will not provide late policy waivers for such cases with less notice.

Assignment Submission Instructions

On all assignments you are expected to follow the instructions exactly. If you don't, you may miss out on the associated learning targets and lose points accordingly.

On any assignment where you must submit a link or file on Canvas, please ensure you submit the correct one. Some examples of incorrect submissions in the past: (1) We ask for a GitHub repository link and you give us a GitHub Page. (2) We ask for a link to a GitHub Classroom-generated repository in our organization and you give us a personal repository. (3) We ask for a link to a PDF and are given a link to a Google Drive folder. If you do not submit the correct link or file, we will not search for the correct one and you will receive a 0.

This is unfortunately necessary to ensure we have as much time as possible to provide feedback on assignments. Accepting assignments in varied forms adds grading challenges and reduces the time and thought we have for providing higher-level feedback on content to you and to other students. Just recently we spent 15 minutes tracking down correct links and comparing two repositories for a single student's submission, which does not scale. Also, permitting variances sets unrealistic expectations for you for future courses and for the real world where following seemingly pointless instructions often does in fact matter.

Assignment Regrading Policy

Re-grading requests must be made by an email to codydunne-and-tas@ccs.neu.edu 📧 within one week of receiving the grade. The request must include:

A link to your Submission Details page for the assignment (Canvas documentation on how to get to it).
The details on what aspect you're requesting to be regraded.
A short (1-2 sentences) explanation of why re-grading is necessary.

The new grade can potentially be lower than the original grade.

Changes to the Syllabus, Schedule, and Grading

The course syllabus, schedule, grading schemes, and grading rubrics are working documents that are subject to change throughout the entirety of the semester. Refer back to the "Home" page at any time for the most up to date document. We will make our best efforts to communicate any meaningful changes promptly. In general, we'll ask ourselves "could this change create an unpleasant surprise for a student who read the syllabus?" If so, we'll announce the change.

🐛 Bonus Points for Bug Bounties 🐛

If you identify problems or points of confusion with the course assignments, you may receive bonus points! In order to get the bonus you must:

Report the bug at least 4 days prior to the due date of the assignment by email to the instructor.
The email must:
- Have the subject line prefixed by "CS 7250 S21 — Bug Bounty".
- Provide a hyperlink to the assignment/web page/repo/document/file in question.
- Include the problematic excerpt, detailed information about what is missing, or other problem details.
- If applicable, suggest a fix including replacement text.

Points will be awarded by degree of severity as determined by the instructor. Generally expect:

- As intended — issues we will not fix: +0 points
- Minor — spelling/grammar/simple writing issues: +1 point
- Major — points of moderate confusion that students could work around with some effort: +2 points
- Severe — bugs that would block a large portion of students from completing the assignment: +3 points

Bonus amounts will vary at the instructors discretion. If multiple students report the bug, the student submitting the first report and the student submitting the most complete fix will get the most points.

Bonus points can increase the score of an assignment above the maximum and not just compensate for lost points.

We will never intentionally introduce bugs into the course materials.

Other Bonus Points

Some assignments will include other options for bonus points.

Communication Policy

Students can reach us by creating a new Canvas Discussion or sending an email. Emails are only appropriate for individual questions — e.g., medical leaves, regrading requests, meeting requests — or when otherwise directed. When emailing, copy the instructor and all TAs, unless there are extenuating reasons to not include the TAs. All general course and assignment questions should be posted as a Canvas Discussion so all students can comment and see the answers. Students that email on issues obviously of general interest will be referred to make a post on Canvas instead.

Help us help you! Always include the relevant links. If you’re emailing about a particular assignment, please include the URL of any relevant materials for us to help you. I.e., before submission send us a link to your GitHub repo — it's hard to debug code without seeing it — or other draft submission. After submission send us a link to your Submission Details page for the assignment (Canvas documentation on how to get to it). If you are asking a project-related question and already have a group, give us your group number too.

We will make our best efforts to respond within 24 hours, excluding weekends. See the teaching staff list above for more detail.

Classroom Electronics Policy

Students will be required to bring a laptop to class (see above). However, students are prohibited from using electronics during class except when specifically instructed for in-class activities. (Not applicable during online learning.)

Students are prohibited from using electronics for non-class purposes during class due to their distracting nature for the student as well as others. Example prohibitions include browsing Facebook, doing work for other courses, messaging friends, and watching sports.

Students are prohibited from using electronics during class for class-related purposes which are not relevant to the in-class activity. E.g., no working on out-of-class assignments during class.

Students who are observed violating the electronics policy will be asked to leave for the day and will be marked as absent. Any quiz or in-class assignment scores for the day will be 0.

Any exceptions to the electronics policy, e.g., for medical monitoring, must be approved by the instructor in advance and in writing.

Recording Privacy Policy

We will not be recording the course sessions in general — it will be conducted synchronously.

In rare cases, this course, or parts of this course, may be recorded for educational purposes. These recordings will be made available only to students enrolled in the course, the instructor, and any teaching assistants assigned to the course. The instructor will announce any recordings when they begin. Any student may opt-out of being recorded by informing the instructor audibly or in the Zoom chat. Any questions or comments the student makes for the remainder of the class session should also be conducted in the Zoom chat, so the student isn't recorded.

Only students who have arranged an accommodation with the Disability Resource Center may use mechanical or electronic transcribing, recording, or communication devices in the physical or virtual classroom. Students with disabilities who believe they may need such an accommodation may contact the Disabilities Resource Center.

Do not record or otherwise share the classroom video calls yourself.

The Commonwealth of Massachusetts's wiretapping law requires "two-party consent". It is a felony to secretly record a conversation, whether the conversation is in person or taking place by telephone or another electronic medium. [See Mass. Gen. Laws ch.272,§ 99.]

Academic Integrity Policy

A commitment to the principles of academic integrity is essential to the mission of Northeastern University. The promotion of independent and original scholarship ensures that students derive the most from their educational experience and their pursuit of knowledge. Academic dishonesty violates the most fundamental values of an intellectual community and undermines the achievements of the entire University.

In this course you are expected to do each assignment independently unless otherwise instructed.

Plagiarism of any kind will not be tolerated, including but not limited to copying text, source code, images, video, visualization designs, and slides.

We will review your submissions against existing publications, designs, course submissions, and source repositories to ensure academic integrity. We maintain a repository of deliverables from previous instantiations of this and related courses to compare submissions against.

For more information, please refer to the Academic Integrity Web page.

Here are some key points to keep in mind:

Acknowledge where code, text, images, designs, etc. come from.
If you look at code online but are supposed to write something yourself, you can't copy the code, either by copy and paste or by writing manually. Just copying and manually renaming variables is definitely cheating. You can get the idea, but not the code.
Anything copied from bl.ocks.org, Observable, or Stack Overflow must be acknowledged. It is not considered just D3 documentation.
Copying *anything* without proper acknowledgement, even just one sentence or figure, is considered plagiarism.
Paraphrasing text closely without citation is plagiarism!
In your writing, citing the source alone is not enough — you must also surround any copied text with double quotes ("").
- Individual work is just that: individual. No code should be exchanged (via whiteboard, email, or over the phone). You probably shouldn't even discuss the assignment with others (but that isn't a strict rule).
- You have teammates for the group project. Thus you have no reason to collaborate with classmates outside of your team.
- If you are stuck; ask for help. Cheating is never the viable solution.
- Lying about participating in service counts as an academic integrity violation. And they tell us attendance anyway, so why would you?
- Why the heck are you in university if you aren't trying to learn? You don't learn by cheating (and, frankly, it can seriously ruin your career far more than failing a class).
- The minimum consequence for an academic integrity violation is a score of 0 on the assignment, reduction of the final letter grade by one (e.g., A- to B-), and reporting to OSCCR and Khoury College. Repeat violations will result in failing the course.

Regret Clause 🤦. If you commit some act that violates the academic integrity policy but bring it to the attention of the instructor within 72 hours, we may still give you a 0 grade for the relevant work submitted, but will not report the violation to OSCCR or Khoury College (except in cases of repeated violations).

Title IX

Title IX of the Education Amendments of 1972 protects individuals from sex or gender-based discrimination, including discrimination based on gender-identity, in educational programs and activities that receive federal financial assistance.

Northeastern’s Title IX Policy prohibits Prohibited Offenses, which are defined as sexual harassment, sexual assault, relationship or domestic violence, and stalking. The Title IX Policy applies to the entire community, including students, faculty and staff of all gender identities.

If you or someone you know has been a survivor of a Prohibited Offense, confidential support and guidance can be found through University Health and Counseling Services staff and the Center for Spiritual Dialogue and Service clergy members. By law, those employees are not required to report allegations of sex or gender-based discrimination to the University.

Alleged violations can be reported non-confidentially to the Title IX Coordinator within The Office for Gender Equity and Compliance at: titleix@northeastern.edu and/or through NUPD (Emergency 617.373.3333; Non-Emergency 617.373.2121). Reporting Prohibited Offenses to NUPD does NOT commit the victim/affected party to future legal action.

Faculty members are considered "responsible employees" at Northeastern University, meaning they are required to report all allegations of sex or gender-based discrimination to the Title IX Coordinator.

In case of an emergency, please call 911.

Please visit www.northeastern.edu/ouec for a complete list of reporting options and resources both on- and off-campus.