Original link: http://vis.pku.edu.cn/blog/visclass/
In the era of big data, the amount of various types of information data increases exponentially, and efficient and intuitive technical methods are urgently needed for the analysis and processing of massive and complex data. Visualization and visual analysis technology is based on the laws of human perception and cognition, and effectively combines human cognitive ability with the powerful computing power of machines. It is a powerful tool for analyzing and understanding complex data, and a bridge and link connecting users and data. Times are getting more and more attention. Mastering visual analysis capabilities, learning to analyze and understand data through visual interfaces and interactive methods, efficient communication, and intelligent decision-making are necessary capabilities in the era of digital intelligence.
Course number: 04835020 (3 credits, blended classroom)
Class time: 7-8 classes every Wednesday
teacher
Researcher Yuan Xiaoru
School of Intelligence, Key Laboratory of Machine Perception and Intelligence, Ministry of Education, Visualization and Visual Analysis Laboratory, Peking Universityxiaoru.yuan[at]pku.edu.cn
http://vis.pku.edu.cn/wiki/
Course targets
This course is a basic practice course of visualization and visual analysis for undergraduates of Peking University. The course will comprehensively and systematically explain the basic principles, important methods, key technologies and method tools in the field of visualization, and cultivate students’ ability to realize basic visualization programming. Through open visual task attempts, learn to master the whole-process problem analysis and solution capabilities in the field of visualization and visual analysis from data analysis, design requirements analysis, task decomposition, program design, system implementation to narrative expression.
This course is a pilot project of blended classroom reconstruction at Peking University. The course will be taught through a combination of online video learning and offline classroom learning and discussion. It will be taught through a learning paradigm, emphasizing communication, initiative and creativity, combining real data with different Disciplinary perspective, while teaching professional knowledge, improve data analysis ability and literacy. The course also focuses on the development of interdisciplinary learning and research practice, involving the exploration of data visualization in the fields of science engineering, humanities and social sciences, and related design arts.
Teaching object
The course is open to the whole school, and students from all majors who are interested in the research of visual chemistry and the use of visualization to carry out interdisciplinary applications are welcome to choose courses. Middle and senior undergraduates (junior and senior) or second-year students with strong programming ability from the School of Information Science and Technology and other related departments are welcome; students with a certain programming foundation from other departments are welcome. In the spring of 2023, the school-wide elective course “Visualizing China” will be offered. Students who choose this course can continue to take this course to further develop interdisciplinary practice. Part of the related programming content will be learned in the course. If there is no relevant programming background, but the students who have a strong interest can contact the teacher to discuss individually.
Inspection method
The course is mainly evaluated through course design work, but also combines course participation, homework, and inspection. Students who have active discussions in the classroom and on the wiki and have novel ideas will be rewarded with grades. The course is designed to work in groups to complete the visualization work and make a defense report at the end of the term.
Course design for previous years
Course design cases from previous years
https://vis.pku.edu.cn/course/visclass_f22/example.html
More visualization cases
Twitter visualization
The Twitter visualization project is based on Twitter tweets and supports interactive analysis of time periods and entities (keywords, prompted users, retweeted users, event tags) of interest to users. The filtered tweet data is visualized with a Contour Map, which helps analyze the unique behavioral patterns of users in social media.
Tweet Visual Analysis System
Distribution of newly elected academicians of the Chinese Academy of Sciences and the Chinese Academy of Engineering in 2021
As the course design of the summer school, this project is widely used in different data sets, such as ChinaVis2020 registration information distribution, CSIG-VIS activity distribution visualization, etc. The project has good compatibility and helps to visualize many event categories.
Distribution of newly elected academicians of the Chinese Academy of Sciences and the Chinese Academy of Engineering in 2021
http://vis.pku.edu.cn/academician2021/#/
Grand Canal Stream Domain Pedestrian Trail
With the help of the interactive timeline and map, users can watch the overview view of the movement of ancient celebrities in the Grand Canal Basin, and can also focus on the specific trajectories of celebrities who have passed through the canal, so as to understand the cultural chapters written by the Millennium Canal. This work was selected into the “Epic of the Earth – China’s Grand Canal Theme Art Exhibition” hosted by Zhejiang Art Museum.
The Migration of People in the Grand Canal Basin, The Epic of the Earth – China Grand Canal Art Exhibition, Zhejiang Art Museum, 2022/8/11 – 10/11
http://vis.pku.edu.cn/grand_canal_migration/
Students who are interested in visualization-related work, are interested in the research and application of visualization, or use visualization to explore their own discipline or work content and improve visualization skills are welcome to choose courses.
Course homepage: https://vis.pku.edu.cn/course/visclass_f22/
If you have any related questions, please consult: xiaoru.yuan[at]pku.edu.cn.
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