COMP4462 (L1) - Data Visualization

Fall 2022  Lecture Notes Lab Schedule Course Projects   Announcements 

 

Instructor:

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

 

TA:

-Haotian LI (haotian.li@connect.ust.hk)

-Linping Yuan (lyuanaa@connect.ust.hk)

 

Time and Venues:

Lectures:
Wed, Fri 01:30PM - 02:50PM Rm 2503 (near Lift 25-26), Acad Concourse

Labs:
Mon 04:30PM - 05:20PM (online)
Note: The first lab will be on Sep 19, 2022.

 

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

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: Nov 2  In-person @ Rm 2503   Close book, close note   (80 min) 1:30pm - 2:50pm 
 Midterm II: Nov 30  In-person @ Rm 2503   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.