疫情大数据赋能效果提升路径研究

Research on the pathway of Big Data enabling effect

在“新冠”肺炎疫情防控中,小到一个“健康码”,大到全国疫情发展趋势分析研判,大数据技术的密集使用都发挥了至关重要的作用。因此,研究疫情大数据如何能实现更加科学高效的赋能,不仅对疫情防控本身具有现实意义,而且对其他领域探索大数据赋能效果的提升路径都有重大参考意义。文章应用OODA循环模型理论,从观察(Observe)、判断(Orient)、决策(Decide)和行动(Act)4个阶段总结疫情大数据在流转赋能过程中出现的问题,并针对这些问题提出相应的改进方案,进而探索提升大数据赋能效果的路径。

In the prevention and control of“new crown”pneumonia epidemic situation,as small as a“health code”,as large as the national epidemic development trend analysis and judgment,the intensive use of big data technology has played a vital role.Therefore,it is of great significance to study how epidemic big data can realize more scientific and efficient enabling,not only for epidemic prevention and control itself,but also for other fields to explore the promotion path of big data enabling effect.This paper uses OODA cycle model theory to summarize the problems of big data in the process of circulation empowerment from four stages of observation(Observe),judgment(Orient),decision(Decide)and action(Act),and puts forward corresponding improvement schemes to solve these problems,and then explores the path to improve the effect of big data empowerment.