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)
- 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
- 数据可视化. 陈为，沈则潜，陶煜波. 电子工业出版社.
ACM SIGGRAPH/SIGGRAPH ASIA
ACM Transaction on Graphics
IEEE Transaction on Visualization and Computer Graphics
IEEE Transactions on Image Processing
IEEE Transactions on Multimedia
IEEE Transactions on Human-Machine Systems
IEEE Transactions on Intelligent Transportation Systems
Computer Graphics Forum
Computer Animation and Virtual Worlds
The Visual Computer
Journal of Visual Language and Computer
Journal of Visualization
Instructor: Chenhui Li
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Class Participation (20%)
Paper Reading and Presentation (30%)