渔业科学观测数据的开放共享与应用研究
收稿日期: 2020-10-19
网络出版日期: 2021-03-11
基金资助
中国水产科学研究院基本科研业务费专项(2020HY-ZC003);渔业通信导航与大数据创新团队项目(2020TD84);国家科技基础条件平台建设项目“渔业科学数据共享平台建设”
Research on Opening sharing and Application of Fishery Scientific Observation Data
Received date: 2020-10-19
Online published: 2021-03-11
渔业科学观测数据是渔业日常观测工作中积累的基础性数据，它直接反映了渔业科学观测工作的整体水平，在渔业资源评估、捕捞生产、生态环境、加工养殖、病害防治和管理决策等方面具有重要的科学意义和广泛的保存、开发应用价值，渔业科学观测数据的分类、共享和应用对推动渔业产业的绿色发展和提高科学数据的管理能力具有重要意义。我国在渔业科学观测数据方面的应用研究起步较晚，研究进展与成果和发达国家相比还有一定的差距，存在数据资源各自孤立、信息缺乏共享、数据利用率低等问题，为提升渔业科学观测数据的开放共享能力和数据利用价值，本文以渔业科学观测数据的共享与应用需求为背景，基于数据分类、共享标准、体系建设、服务模式、大数据分析、典型应用等方法，对数据资源结构、共享体系构建和应用服务分析展开研究，梳理了渔业科学观测数据的标准化结构，提出了渔业科学观测数据的共享体系建设方案，设计了渔业科学观测数据共享服务平台的总体技术架构，加强了渔业科学观测数据的资源整合和汇聚处理。渔业科学观测数据是支撑渔业科技创新、发展现代渔业的战略性、基础性资源，本研究对共享服务内容和数据应用提出合理建议，为充分发挥渔业科学观测数据的应用价值，进一步开展渔业科学观测数据的研究工作提供参考。
薛沐涵, 刘慧媛, 鲁峰, 蒋庆朝 . 渔业科学观测数据的开放共享与应用研究[J]. 农业大数据学报, 2020 , 2(4) : 29 -37 . DOI: 10.19788/j.issn.2096-6369.200404
Fishery scientific observation data is the basic data accumulated in daily fishery observation work. It has wide application value in fishery resources assessment, fishing production, ecological environment, processing and breeding, disease control and management decision-making. The classification, sharing and application of fishery scientific observation data is of great significance to promote the green development of fishery industry and improve the ability of scientific data management. In order to enhance the open sharing ability and data utilization value of fishery scientific observation data, this paper studies data resource structure, sharing system construction and application service analysis, based on data classification, sharing standards, system construction, service mode, big data analysis, typical application and other methods. Sorted out the standardized structure of fishery scientific observation data, proposed the construction scheme of fishery scientific observation data sharing system, designed the overall technical framework of fishery scientific observation data sharing service platform, strengthened the resources integration and aggregation processing of fishery scientific observation data. This study provides reasonable suggestions for sharing service content and data application, provides reference for further researching on fishery scientific observation data.
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