The Training Path of Big Data Talents in the Chinese Government in the field of Emergency Management
- Fuyu Li, Shuyan Wei, Fucang Li
- Corresponding Author
- Fuyu Li
Available Online May 2019.
- https://doi.org/10.2991/icmete-19.2019.8How to use a DOI?
- Emergency management; Big data; Big data talents; Public crisis events
- In the field of emergency management, the number of big data talents in the Chinese government is small and the quality is poor. In order to cope with the public crisis events better and meet the actual needs of emergency management, the Chinese government needs to cultivate more excellent big data talents. By applying the documentation method and consulting the relevant research both at home and abroad, it is obtained the latest research trends in the training of big data talents in the field of emergency management. Based on the analysis of detailed data, it is found that the reasons for the shortage of the emergency management talents are due to the weakness of big data awareness of governmental personnel, the lack of specialized laws for the use of big data, and the unreasonable talent training mechanism. The training of big data talents of emergency management in Chinese government should strengthen the staff’s awareness of big data, enact laws to normalize the use of big data, and innovate the training mechanism for big data talents. It will improve the quality of big data talents, increase the number of talents, and provide intellectual support for emergency management.
- Open Access
- This is an open access article distributed under the CC BY-NC license.
Cite this article
TY - CONF AU - Fuyu Li AU - Shuyan Wei AU - Fucang Li PY - 2019/05 DA - 2019/05 TI - The Training Path of Big Data Talents in the Chinese Government in the field of Emergency Management BT - 2019 International Conference on Management, Education Technology and Economics (ICMETE 2019) PB - Atlantis Press SN - 2352-5428 UR - https://doi.org/10.2991/icmete-19.2019.8 DO - https://doi.org/10.2991/icmete-19.2019.8 ID - Li2019/05 ER -