COMP4462 (L1) - Data Visualization
Fall 2023 Lecture Notes Lab Schedule Course Projects Announcements
Instructor:
Xiaojuan Ma
Office hours (in Room 3507 near Lift 25-26): by email appointment.
TA:
- Qian Zhu (qzhual@connect.ust.hk)
- Xiaofu Jin (xjinao@connect.ust.hk)
Time and Venues:
Lectures:
Monday: 01:30PM - 02:50PM; Friday: 09:00AM - 10:20AM @ Rm 2504 (near Lift 25-26), Acad Concourse
Labs:
Thursday 09:00AM - 09:50AM (LT-E)
Note: The first lab will be on Sep 21, 2023.
Grading Scheme:
In-Class Exercise and Participation (10%) (Example: In-Class Exercise)
Lab Activities and Exercise (10%) (Example: Lab)
Top Vis Competition and Essay (10%) (Example: topvis_2020spring.pdf, Essay)
Final project (30%) (Example: Project)
Two In-Class Midterms (40%) (Example: Exam, Exam2a, Exam2b)
Course Description:
This course will introduce visualization techniques for data from everyday life, social media, business, scientific computing, medical imaging, etc. The topics include human visual system and perception, visual design principles, open-source visualization tools and systems, visualization techniques for CT/MRI data, computational fluid dynamics, graphs and networks, time-series data, text and documents, Twitter data, and spatio-temporal data. The labs and the course project will give students hands-on experience to turn their favorite data into beautiful visualizations.
References:
- Visualization Analysis and Design by Tamara Munzner: Visualization Analysis and Design
- Interactive Data Visualization: Foundations, Techniques, and Applications by Matthew Ward, Georges Grinstein, and Daniel Keim: Interactive Data Visualization
- The visualization handbook
- Information visualization: perception for design
- The visual display of quantitative information
- Envisioning information
- Visual explanations: images and quantities, evidence and narrative
Similar Courses:
Data Visualization from University of Washington
Information Visualization from University of British Columbia
Links:
Resources:
visualcomplexity.com | A visual exploration on mapping complex networks
information aesthetics - Information Visualization & Visual Communication
Conferences and Journals:
IEEE VIS Conferences
IEEE Transactions on Visualization and Computer Graphics
IEEE Xplore (Proceedings of IEEE visualization, infovis; TVCG)
Exam Scheduling:
Date | Venue | Format | Length |
Midterm I: Oct 27 | In-person @ Rm 2504 | Close book, close note | (80 min) 9:00am - 10:20am |
Midterm II: Nov 20 | In-person @ Rm 2504 | Close book, close note | (80 min) 1:30pm - 2:50pm |
Note1: the midterm exams will cover both materials presented in the lectures and labs.
Note2: things to bring to the exam include student ID, pens/pencils, ruler, and erasers.
Note3: only students with official "NIHK" label could apply for online exam.
Intellectual Honesty & Plagiarism
- Students are expected to follow the HKUST Academic Honor Code
- All work submitted for grading, e.g., assignments, must be your own
- You are permitted to discuss problems with other students but you must write up all solutions by yourself, in your own words.
- If you got the main idea for a solution from another student or a website you must acknowledge that source in your submission.
- Submission of non-acknowledged material will be considered as plagiarism and dealt with under the university policy for cheating.