An MOE Major Project Completed and Rated as “Excellent”

Author:Geng Mengyu, Wei Xingfei, Niu Chunhua Translator:Yin Yanqing, Yan Xuefei Source:Research Center for Emergency Management Reviewer:Zhao Yanhai View: Updated:2022.09.16 Font Size:T T T

The MOE Philosophy and Social Sciences major project “Research on Urban Public Security Risk Driven by Big Data” (hereafter as the Project), chaired by Prof. Sha Yongzhong from Research Center for Emergency Management, was successfully completed last year and rated as “excellent” recently. According to the “Measures of the Ministry of Education for the Evaluation of the Achievements of the Major Projects of Philosophy and Social Sciences”, the highest level of project evaluation is excellent, which refers to “outstanding completion of project research tasks; significant innovations in research results, high academic value, application value or social impact; 4/5 of the evaluation team consent for “excellent”, and the average score was higher than 90.”

The Project, as a topic proposal firstly submitted by Prof. Sha Yongzhong to MOE, was included in the selection guide for the 2016 MOE’s major research projects on philosophy and social sciences. By attaining the approval on November 15, 2016 with a total funding of 800,000 yuan, it is the first national major project of LUSM in the field of humanities and social sciences. The Project focuses on the big data-driven urban public security risk governance, aiming to explore and answer a series of key scientific issues driven by big data when meeting the actual needs of the country. In detail, the Project has drawn valuable research findings and relevant policy recommendations, and taken a series of effective measures to facilitate the practice of public security risk governance driven by big data, and realize the transformation of theoretical experience into practical application, such as: Take environmental health risk, food safety risk and flood risk as typical industrial or regional application cases; focus on big data driven public security identification, assessment and governance practices through industry or field multi-source data aggregation, data governance and data analysis.

Relying on the Project, the research team has reached various achievements, including more than 70 academic papers published, 7 utility model patents and 6 computer software copyrights attained, 19 policy suggestions and think tank reports provided to different levels of governments, and 8 doctoral students and 15 master’s students trained. “Data-driven Public Security Risk Governance” has been incorporated into the publication plan of the major projects of MOE, and will be published by the designated publishing house (Economic Science Press).