Data visualization is viewed by many disciplines as a modern equivalent of visual communication. It involves the creation and study of the visual representation of data. To communicate information clearly and efficiently, data visualization uses statistical graphics, plots, information graphics and other tools. Numerical data may be encoded using dots, lines, or bars, to visually communicate a quantitative message. Effective visualization helps users analyze and reason about data and evidence. It makes complex data more accessible, understandable and usable. Users may have particular analytical tasks, such as making comparisons or understanding causality, and the design principle of the graphic (i.e., showing comparisons or showing causality) follows the task. Tables are generally used where users will look up a specific measurement, while charts of various types are used to show patterns or relationships in the data for one or more variables. (From Wiki)
Schedule
Textbooks
- The Visual Display of Quantitative Information (2nd Edition). E. Tufte. Graphics Press.
- Visual Analytics for Data Scientists. Natalia Andrienko, Gennady Andrienko et al. Springer 2020
- 可视化导论. 陈为等编著. 高等教育出版社.
Resources
Tools
Conferences
ACM Conference on Human Factors in Computing Systems (ACM CHI)
ACM Symposium on User Interface Software and Technology (ACM UIST)
EuroVis
PacificVis
Journals (A/B/C)
ACM Transaction on Graphics
IEEE Transaction on Visualization and Computer Graphics
IEEE Transactions on Multimedia
Computer Graphics Forum
The Visual Computer
Journal of Visualization
Teaching Staff
Instructor: Chenhui Li
To contact me please use E-mail (chli@cs.ecnu.edu.cn). This is the fastest way to get a response.
Requirements
Class Participation (20%)
Paper Reading and Presentation (30%)
Final Project(50%)