Course Information

Harvard College/Graduate School of Arts and Sciences: CS 271 - Topics in Data Visualization
Term: 2022 Spring
Meeting Time: Mon/Wed 3:45-5:00pm
Location: SEC 1.402 (150 Western Ave, Boston)
Instructor: Johanna Beyer jbeyer@g.harvard.edu (pronunciation: yo-haan-nah; pronouns: she/her/hers)
Teaching Fellows: Carolina Nobre, Zhu-tian Chen
Recommended Preparation: CS 171, CS 179, CS 279, or data visualization experience. Please contact course staff if you are unsure about the course pre-requisites.
Office Hours: Always after class, or message me to set up a meeting outside of class times!

Course Description

This course covers advanced topics in data visualization. Over the course of the semester, we will examine seminal works and recent state-of-the-art research in information visualization, scientific visualization, and visual analytics. Students are encouraged to bring in ongoing or related research. Topics covered in this class include interaction, storytelling, evaluation, color, volume rendering, vector field visualization, visualization in sciences, big data visualization, uncertainty visualization, and visualization for machine learning. Students will work on a semester-long visualization research project that will allow them to visualize their own data sets. The goal is to do visualization research, as opposed to just creating a visually pleasing interactive storytelling website. We will take a structured approach on how to read, analyze, present, and discuss research topics. Furthermore, we will employ peer-feedback and formal design critiques to analyze each other’s work.

Learning Outcomes

After completion of the course you will be able to:

  • Read, understand, and disseminate current visualization research results
  • Analyze, discuss, and present visualization research papers to a computer science/engineering audience
  • Critically evaluate visualizations and suggest improvements and refinements
  • Create a stand-alone visualization project, building on previous work and insights gained in visualization research over the last decades
  • Write a short research paper about your visualization project

Course Structure

Classes will meet twice a week for in-class discussion of assigned reading, group-based work (e.g., design critiques), and project feedback. Students will take turns presenting papers and leading class discussion. Active participation and preparation for class is expected and will contribute to your final grade. Each student is supposed to work on a semester-long visualization project that will be defined within the first two weeks of class. Students will disseminate the results of their semester project in a short visualization research paper.

Required Reading

We will be using Tamara Munzner’s book ‘Visualization Analysis & Design’ in this course. You can access the online version of the book via HOLLIS here.

Course Policies

Attendance is mandatory! If you have to miss a class meeting, you have to let the instructor know in advance. Keep in mind that our class is heavily based on interactive discussions. In your absence you will not only miss the discussed material, but you also negatively influence the learning outcome of your peers! You are allowed two excused absences per semester. To receive credit for attendance, you must arrive on time.
Active participation is expected! Active participation and preparation for class are expected and will contribute to your final grade.

Grading

Your course grade will be based on your semester project (30%), visualization paper (20%) and preparation for and participation in class (50%). This includes class participation, teamwork, meeting of deadlines, collaboration acknowledgements, timely arrival to your class, etc.

Academic Integrity

We expect you to adhere to the Harvard Honor Code at all times. Failure to comply with the honor code and our policies may result in serious penalties, up to and including automatic failure in the course, and reference to the ad board.

You may discuss your project and homework with other people, but you are expected to be intellectually honest, transparent, and give credit where credit is due. You may use third-party libraries and example code, so long as the material is available to all students in the class, you give proper attribution, and the general copyright rules are met. Do not remove any original copyright notices and headers.

Diversity and Inclusion

We will work to create a learning environment in our class that is inclusive and respectful of diversity: gender, sexuality, disability, age, socioeconomic status, ethnicity, race, culture, etc. We ask you to engage in discussion with care and empathy for the other members in the classroom. Treat others how you would like to be treated. Aim to disagree without becoming disagreeable. If something was said in class that made you feel uncomfortable, please talk to us about it.

Accommodations for students with disabilities

Students needing academic adjustments or accommodations because of a documented disability must present their Faculty Letter from the Accessible Education Office (AEO) and speak with the professor by the end of the second week of the term. Failure to do so may result in the instructor’s inability to respond in a timely manner. All discussions will remain confidential, although Faculty are invited to contact AEO to discuss appropriate implementation.