With the increasing amount of data in the big-data era, how to help people understand complex data is becoming increasingly challenging. Data visualization techniques bridge the data and human cognition, allowing people to understand data with a reduced mental burden. Today, data visualization is becoming an independent and popular research domain.
The goal of this course is to prepare students with the skills necessary to perform data visualization research. We will cover a wide range of commonly used data visualization techniques and commonly accepted data visualization principles. We will introduce the full process of designing a visualization tool, including the process of understanding people, understanding the data, the visualization tasks, implementation, and evaluation. We will mainly use d3.js to implement the visualization tools.
Students are encouraged to bring their domain specific problems that require understanding a large amount of data. This course will be project-oriented. We will have NO midterm or final exams. Every student (or a 2-student group) will complete a "design study" research project during this course. Eventually, each group will finish a paper that meets the IEEEVis Short Paper quality.
<aside> 👨🏫 Yifan Sun
Please call me Yifan without "Professor". If you send me an email, please start with "Hi Yifan" or the message body directly.
Email: [email protected]
Website: syifan.github.io
Office:
McGlothlin-Streen Hall 117
Office Hour:
Monday 3:30 pm - 4:30 pm First office hour is on 1/31/2022 Last office hour is on 5/2/2022
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<aside> 📗 Visualization Analysis and Design (AK Peters Visualization Series) 1st Edition ISBN-13: 978-1466508910 ISBN-10: 9781466508910
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<aside> 👩🏼🏫 by Tamara Munzner
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<aside> 👉 The text book is required. Online access is made available by the William & Mary Library. You can search the book title on the website of the W&M library.
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<aside> 📅 Last day to add/drop: February 4, 2022 Last day to withdraw: March 28, 2022
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Lectures will be primarily in-person, unless otherwise noticed.
<aside> 🕑 Time: Monday, Wednesday 2:00 pm - 3:20 pm
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<aside> 📍 Location: McGlothlin-Street Hall Room 002
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However, given the COVID-19 situation, for medical-related reasons, students can join the lectures through the Zoom link on the right.
Join our Cloud HD Video Meeting
We will be using Slack for the class communication. Please join the workspace for my research lab using the link on the right, and then, join the #csci780-s22-data-vis channel. I will send announcements in this channel.
Please try to send questions/comments/replies to this public channel, rather than private messages. We try to keep the communication transparent.
Please check the table below for the schedule for the semester. If there is a small document icon on the left or a row (see image 1 on the right), the row has more information that is not visible in this table. Hover your mouse on the date and you can see an OPEN button (see image 2 on the right). Click on the button to see the information behind the entry.
All assignments due at 5:00 PM on the specific days.
| Item | Weight |
|---|---|
| Class Participation | 10% |
| Help Provided to Other Groups | 10% |
| Assignments | 50% |
| Project Paper | 30% |
There is no final exam for this course.