COMP4462 (L1) - Data Visualization

Fall 2024  Lecture Notes Lab Schedule Course Projects Top Vis Competition   Announcements 

 

Instructor:

Xiaojuan Ma
Office hours (in Room 3507 near Lift 25-26): by email appointment.

 

TA:

- Ziqi Pan (zpanar@connect.ust.hk)

- Chang Chen (cchenda@connect.ust.hk)

 

Time and Venues:

Lectures:
Mon 01:30PM - 02:50PM, Fri 09:00AM - 10:20AM; Rm 1527 (Lift 22), Acad Concourse

Labs:
Fri 03:00PM - 03:50PM (Multi-function Room, LG4, LIB)
Note: The first lab will be on Sep 20, 2024.

 

Grading Scheme:

In-Class Exercise and Participation (10%) (Link: In-Class Exercise)
Lab Activities and Exercise (10%) (Link: Lab)
Top Vis Competition and Two Essays (10%) (Example: topvis_2020spring.pdf; Instruction: Self-Assessment Essay)
Final project (30%) (Link: Project; Instruction: Self-Assessment Essay)
Two In-Class Midterms (40%) (Example: Exam, Exam2a, Exam2b)

Note*: Each student can have up to 1 late day for the in-class exercises and 1 late day for the lab exercises. Students must submit the request to the TA(s) before the deadline to claim the use of X hours of the late day to avoid penalty.

 

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

Visualization from Harvard

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 21  In-person @ Rm 1527  Close book, close note   (80 min) 1:30pm - 2:50pm 
 Midterm II: Nov 22  In-person @ Rm 1527  Close book, close note,
 1 A4 self-prepared  cheatsheet allowed 		  (80 min) 9:00am - 10:20am 

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.