媒体大数据防疫应急网络基础设施

Jing He, Yining He, Haonan Chen
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引用次数: 0

摘要

媒体大数据量大、增长快、种类多,面临诸多挑战。此外,在全球新冠肺炎疫情防控背景下,媒体大数据具有不同的特点和使命。本文提出的科学数据平台、工具集成、科研流程和国际合作,在国际合作四条主线上实施媒体大数据科学防疫应急领域的实施思路和技术方法,实现有效的数据管理和分析,提高科学发现效率。网络基础设施研究前期需要构建数字化、数据化、智能化的网络基础设施框架和疾病预防、心理安慰、物质安全等应急响应措施。基于“数据-方法-模型-系统-标准”的理念,生成媒体防疫大数据研究总体设计框架,研究成果旨在助力媒体防疫大数据生态布局。建立了全球一体化基础信息平台。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Media Big Data Cyber Infrastructure for Epidemic Prevention and Emergency Response
Big data in the media is facing many challenges with huge volume, rapid increase, and a wide variety. Moreover, in the context of the global coronavirus epidemic prevention and control, media big data has different characteristics and missions. The scientific data platform, tool integration, scientific research process and international cooperation proposed in this article are implemented in four main lines of international cooperation for the implementation of ideas and technical methods in the field of media big data science for epidemic prevention and emergency, to achieve effective data management and analysis to improve the efficiency of scientific discovery. For cyber infrastructure research, preliminary research needs to build a digital, data-based, and intelligent cyber infrastructure framework and emergency response measures for disease prevention, psychological comfort, and material security. Based on the concept of "Data-Method-Model-System-Standard", the research overall design framework of MEP (media big data for epidemic prevention) is generated, and the research results are intended to help the epidemic prevention ecological layout of the media big data. An integrated basic information platform has been established globally.
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