Source: School of Geography and Planning
Written by: Urbanization Institute of Sun Yat-sen University
Edited by: Wang Dongmei
On November 14th, 2015, Shanghai Open Data Apps (SODA), which was funded by Shanghai Economic and Information Committee, Shanghai Transportation Commission and China Industrial Design Institute (CIDI), was held in Huangpu district in Shanghai. There are 836 teams in the first stage, 100 teams in the second stage, and the top 15 teams could access to the final. The awards include SODA grand prix (one), honorable mentions (three), and other individual awards (four). With three months’ endeavor, GO BIKING Team of Urbanization Institute of Sun Yat-sen University (UI-SYSU) successfully passed every stage step by step, and was finally awarded the honorable mention and 100,000
yuan, which could show UI-SYSU’s outstanding capacity of innovation and interdisciplinary researches. The title of GO BIKING Team’s project is “Crowdsourcing your riding life: an implemented APP by crowdsourcing space-time data mining”.
GO BIKING Team of Urbanization Institute of Sun Yat-sen University receives Honorable Mention in SODA 2015.
GO BIKING’s core members include Chen Haohui (part-time research fellow of UI-SYSU), Chen Shili (PhD candidate), as well as Wang Depei, Tian Pinghui and Zheng Jiafen (Master degree candidates). Professor Li Xun is the Team’s tutor. Li Minsheng, Huang Yaofu, Liu Min, Lu Shaoshao, Yang Si, Qin Xiaozhen, Chen Zuoren and other students also give their hands in the whole course.
In 2015, SODA’s dominant theme is “Urban Transportation”. Every team should use the open data offered by the traffic management department and relevant companies, other open internet data are also encouraged. Every team’s results should be APP product/model, as well as their OTO activities. In this way, classical application and solution project on data visualization for improving citizen’s commuting could be easily achieved from all over the world.
"Crowdsourcing your riding life: an implemented APP by crowdsourcing space-time data mining” proposed by GO BIKING Team, is mainly applied to optimize “citizen’s last kilometer commuting”. Based on professional knowledge of human geography and urban planning, GO BIKING Team applies big data technology, brings in crowdsourcing plan and community sharing, and finally put forward a kind of assistant backstage system for decision-making plan. This system also depends on dynamic information collecting skill, data mining technology as well as information visualization skills. There are two achievements for this system: first, an experimental project on citing for bicycle parking cite and distributing for riding lane. Second, a kind of smart-phone APP including three functions: inquiring and navigating dynamic bicycle parking cite, crowdsourcing plan (complaint and greenway crowdsourcing), and bicycle sharing communities.
Instructed by Prof. Li Xun, the students have showed their innovative thinking and exploring spirit in the competition. On the basis of professional knowledge of human geography and urban planning, they combined urban planning, big data and information visualization technology with fantastic ideas such as crowdsourcing plan and community sharing.
