CSCI339001 Visualization

Data can capture a snapshot of the world and allow us to understand ourselves and our communities better. With ever-increasing amounts of data, the ability to understand and communicate data is becoming essential for everyone. Visualization leverages our visual perception to provide a powerful yet accessible way to make sense of large and complex data. It has been widely adopted across disciplines, from science and engineering to business and journalism, to combat the overabundance of information in our society.

In this course, students will learn to acquire foundational knowledge about how to design effective visualizations for analysis and presentation based on theories and principles from graphic design, perceptual psychology, and cognitive science. Students will also learn practical skills about how to rapidly explore and communicate data using Tableau and build interactive visualization products (e.g., articles, tools, and systems) using web-based frameworks including D3.js and Vega-Lite.

Time: TuTh 12:00-1:15 pm
Location: Merkert Center 130
Submission: Canvas
Q & A: Piazza

Prerequisites
There are no official prerequisites for this course, but students are expected to have programming experience. Having experience in web development (i.e., Javascript, HTML, and CSS) is a plus, but not required.

Textbooks
There is no required textbook. Readings will be provided and available online through Boston College Libraries

Teaching Staff

Instructor: Nam Wook Kim
Email: nam.wook.kim at bc.edu
Office: St. Mary's Hall S256
Office Hour: Th 1:30-3:30 pm, reserve a 10 Min Slot

Teaching Assistant: Pedro De Almeida Rosa Guimaraes
Email: dealmeip at bc.edu
Office Hour: Mo 7:00-9:00 pm at Computer Science Lab - Fulton 160

Learning Objectives

By the end of this course, students will be able to D.A.B:

  1. Design effective visualizations that are readable, engaging, and memorable by considering various factors including data types, questions, audiences, and messages
  2. Articulate design choices for their visualizations and benefits & pitfalls of existing visualizations they encounter in the wild
  3. Build interactive visualizations that can address real-world needs, ranging from supporting exploratory analysis to communicating messages about data

Schedule

All
Next
Lectures
Labs

Logistics


Lectures

The class holds a lecture per week on Tuesday. Lectures introduce fundamental knowledge about designing effective visualizations and articulating design rationales. Some lectures feature short in-class activities that may require pen & paper and laptops.

Labs

The class holds a lab on Thursday. Labs offer hands-on training for building interactive visualizations for the web. Labs are self-guided with written instruction. Students submit individually but are encouraged to help each other to complete the labs.

Readings

Each lecture and lab require pre-class readings. Students are required make commentaries before each class.

Homework

There are three homework assignments as below:

  1. Visualization critique & redesign (Out: 09/03, Due: 09/17)
  2. Exploratory and explanatory analysis with Tableau (Out: 09/17, Due:10/01)
  3. Interactive visualization using D3.js (Out: 10/01, Due: 10/23)

Final Project

The culmination of this course is the final project in which students build creative visualization products of their own interests. Students are required to present their work in the class and write up a final report in a conference abstract format. An exceptional project will be encouraged to submit to the Late-Breaking Works track in ACM CHI. Please find more information about the final project here.

  1. Project proposal (Out: 10/22, Due: 10/30)
  2. Low-fidelity prototype (data & sketches) (Out: 10/30, Due: 11/06)
  3. High-fidelity prototype (working interface) (Out: 11/06, Due: 11/20)
  4. Final Deliverables (showcase video & final report) (Out: 11/20, Due: 12/04)

Grading

A student’s grade will be based on:

A letter grade is assigned based on the following guideline (A is excellent; B is good; C is satisfactory; D is passing but unsatisfactory; F is failure):

In-class activities and minute papers are part of participation, which is meant to help you attain a better grade.

Policies & Practices


Course Policy

Laptop policy
Students may not use laptops, tablets, phones or other electronic devices during the lectures except when explicitly asked to do so. There is plenty of evidence that multitasking incurs a high cognitive cost in memory and attention (ref), students who take notes on laptops may learn less than those who take notes on paper (ref), laptops adversely impact not only the people using them, but also those around them (ref).

Mandatory attendance
A lot of learning in this course happens through various activities in both lectures and labs. Not only attending but also being on time is crucial.

Late submission
Lab, homework, and project submissions after respective deadlines are not accepted. Under special circumstances such as medical conditions, family issues, or job interviews, we will allow lab submissions without penalty. Please contact the instructor or TA for such situations. We may require proof of evidence.

Regrade policy
Fair and transparent grading is important. Please contact us know if you think there is an error or unreasonable deduction in your assignment. Only regrading requests within 7 days after the initial grade are accepted.

Accessibility

If you have a disability and will be requesting accommodations for this course, please register with either Dr. Kathy Duggan (dugganka@bc.edu), Associate Director, Connors Family Learning Center (learning disabilities or AHD) or Dean Rory Stein, (rory.stein@bc.edu), Assistant Dean for students with disabilities, (all other disabilities). Advance notice and appropriate documentation are required for accommodations.

Academic Policy

Students are required to adhere to the academic policy of Boston College.

Commitment to Inclusion

It is our intention that students from all diverse backgrounds and perspectives be well-served by this course, that students’ learning needs be addressed both in and out of class, and that the diversity that students bring to this class be viewed as a resource, strength and benefit. It is our intent to present materials and activities that are respectful of diversity: gender, sexuality, disability, age, socio-economic status, ethnicity, race, and culture. Your suggestions are encouraged and appreciated. Please let me know ways to improve the effectiveness of the course for you personally or for other students or student groups.

Code of Conduct

We follow ACM Code of Ethics, focusing on the following:

  • Demonstrate professionalism (e.g., being on time and respect in teamworks)
  • Promote fair, inclusive, and collaborative learning environment
  • Reject behavior that strays into any form of harassments

Hall of Fame

🏆: Best project     🏅: Honorable mention

2019

🏆 Do you think the world sucks?
Chun-An Wang, John Abreu, Peixuan Huang
🏅 Gun Violence in America
Brenna Griesser, Ashley Oh, Catriona Sullivan, Liwen Wong
🏅 A Brief Introduction to Cryptocurrency
Linda Chen, Edward Cramer, Helen Nazarenko, Michelle Youn

Credits

The course material is based on courses taught by Hanspeter Pfister at Harvard, Jeffrey Heer at the University of Washington, Maneesh Agrawala at Stanford University, Alexander Lex at the University of Utah, and Tamara Munzner at the University of British Columbia.