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文章论述了大数据环境下数据密集型科研活动面临的挑战,在此基础上分析了科学大数据服务平台构建的必要性和可行性,并具体阐述了科学大数据服务平台构建模型,包括科学大数据接收层、科学大数据存储层、科学大数据组织层、科学大数据计算层、科学大数据分析层以及科学大数据用户接口层等,旨在解决数据密集型科研活动面临的大数据采集存储、分析管理以及共享应用等问题。
This paper discusses the challenges faced by data-intensive research activities in big data environments. Based on this analysis, the necessity and feasibility of constructing big data service platforms for science are analyzed. The models for building large data service platforms for science are elaborated, Data receiving layer, science big data storage layer, science big data organization layer, science big data computing layer, science big data analysis layer and science big data user interface layer and so on, aimed at solving the problem of data-intensive research activities in big data acquisition and storage , Analysis and management and sharing applications and other issues.