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

---

Week 2: Introduction I (2019-09-12)

    Introduction I

Week 3: Introduction II & Visual Attention and Color Model (2019-09-19)

    Introduction II | Visual Attention and Color Model | Visualization Tools

Week 4: Graph Visualization (2019-09-26)

    Graph Visualization

Week 6: Hierarchic Visualization (2019-10-10)

    Hierarchic Visualization

Week 7: Text Visualization (2019-10-17)

    Text Visualization

Week 8: GeoVisualization (2019-10-24)

    GeoVisualization

Week 9: Spatio-Temporal Visualization (2019-10-31)

    Spatio-Temporal Visualization

Week 10: Scientific Visualization (2019-11-07)

    Scientific Visualization

Week 11: Medical Visualization (2019-11-14)

    Medical Visualization

Week 12: High-Dimensional Visualization (2019-11-21)

    High-Dimensional Visualization | Parallel Coordinates| t-SNE

Week 13: Visual Analysis (2019-11-28)

    Visual Analysis

Week 14: Interaction and Evaluation (2019-12-05)

    Interaction and Evaluation

Week 15: Big Data Visualization (2019-12-12)

    Big Data Visualization | Points | Huge Points | Points Visualization | Tencent Map

Week 16: Cross-Media Visualization (2019-12-19)

    Cross-Media Visualization | Flowing | Symmetrical Art | Triangulator | Geopattern

Week 17: Deep Learning Visualization | Final Presentation, 7 Mins/Group (2019-12-26)

    18:00-18:40     Deep Learning Visualization & Paper Presentation
    18:50-19:40     Final Presentation (Section 1: G01, G02, G03, G04, G05, G06)
    19:50-20:40     Final Presentation (Section 2: G07, G08, G09, G10, G11, G12, G13)
    20:40-20:50     Discussion & Conclusion

Textbooks

---

1. The Visual Display of Quantitative Information (2nd Edition). E. Tufte. Graphics Press.
2. 数据可视化. 陈为，沈则潜，陶煜波. 电子工业出版社.

Resources

---

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)

Conferences

1. ACM SIGGRAPH/SIGGRAPH ASIA

2. IEEE VIS Conference

3. EuroGraphics/EuroVis

4. PacificGraphics/PacificVis

5. CGI/CASA

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 (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%)