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)


Week 2: Introduction I
    Introduction I
Week 3: Introduction II
    Introduction II
Week 4: Graph Visualization
    Graph Visualization
Week 6: Hierarchic Visualization
    Hierarchic Visualization
Week 7: Text Visualization
    Text Visualization
Week 8: GeoVisualization
Week 9: Spatio-Temporal Visualization
    Spatio-Temporal Visualization
Week 10: Scientific Visualization
    Scientific Visualization
Week 11: Medical Visualization
    Medical Visualization
Week 12: High-Dimensional Visualization
    High-Dimensional Visualization
Week 13: Visual Analysis
    Visual Analysis
Week 14: Interaction and Evaluation
    Interaction and Evaluation
Week 15: Big Data Visualization
    Big Data Visualization
Week 16: MultiMedia Visualization
    MultiMedia Visualization
Week 17: AI4VIS | VIS4AI


  1. The Visual Display of Quantitative Information (2nd Edition). E. Tufte. Graphics Press.
  2. Visual Analytics for Data Scientists. Natalia Andrienko, Gennady Andrienko et al. Springer 2020
  3. 数据可视化. 陈为,沈则潜,陶煜波. 电子工业出版社.


  1. Differences and Similarities Between TVCG and VIS papers.

  2. Process and Pitfalls in Writing Information Visualization Research Papers

  3. How to Read a Paper

  4. How to Read a Visualization Research Paper

  5. How to Write a Visualization Research Paper

  6. How to Review HCI/Visualization Papers

  7. Latex Setting (Sublime Text3)



  2. IEEE VIS Conference

  3. EuroGraphics/EuroVis

  4. PacificGraphics/PacificVis


  6. Vis Conferences Acceptance Rates

  7. Paper Collection (ZJU VAG)

Journals (A/B/C)

  1. ACM Transaction on Graphics

  2. IEEE Transaction on Visualization and Computer Graphics

  3. IEEE Transactions on Image Processing


  1. IEEE Transactions on Multimedia

  2. IEEE Transactions on Human-Machine Systems

  3. IEEE Transactions on Intelligent Transportation Systems

  4. Computer Graphics Forum

  5. Graphical Models


  1. Computer Animation and Virtual Worlds

  2. The Visual Computer

  3. Journal of Visual Language and Computer

  4. Information Visualization

  5. Journal of Visualization

Teaching Staff

Instructor: Chenhui Li

To contact me please use E-mail ( This is the fastest way to get a response.


Class Participation (20%)
Paper Reading and Presentation (30%)
Final Project(50%)