远洋渔业科学数据治理与应用服务研究

doi:10.19788/j.issn.2096-6369.220215

Abstract

Abstract:

Ocean fishery scientific data refers to the basic data collected in the scientific research and production activities of ocean fishery, it has wide application value in marine environment monitoring and protection, fishery resources management, weather forecast, water area utilization, zoning management and production and operation guidance of ocean fishing vessels. The organization, management and application of scientific data of ocean fishery are of great significance to realize the modernization development of ocean fishery in China and to safeguard the legitimate rights and interests of the ocean. Establishing a reasonable, efficient and perfect ocean fishery data governance model can effectively organize and manage data, reconstructhistorical status and track and predict changes. Aiming at the problems of scattered storage and management of scientific data of ocean fishery and limited application scope, based on the promotion of information construction and specific business needs of ocean fishery, this paper studies the integration and integration of multi-source data, the governance of ocean fishery scientific data, the construction of data warehouse and the data application service mode, proposed ocean fishery scientific data governance model and based on this model, information mining and application theme exploration of scientific data of ocean fishery are carried out, it provides a carrier for the regulatory policy, user demand and service mode of ocean fishery scientific data, and improves the utilization efficiency, economic value and social value of ocean fishery scientific data. As an example of a data application service, designed and realized the integrated service platform of ocean fishery, it effectively verified the feasibility and practicability of ocean fishery scientific data governance in data supervision service. This study guides the specific service practice of data application through the establishment of ocean fishery scientific data governance model, and provide reference for the next step of the research on the interconnection, sharing and standardization of ocean scientific data.

Key words: ocean fishery, scientific data, data governance, data application, data service

CLC Number:

S973

Muhan Xue, Shuo Xu, Huiyuan Liu, Feng Lu, Yu Wang, Ao Li. Research on Ocean Fishery Scientific Data Governance and Application Services[J].Journal of Agricultural Big Data, 2022, 4(2): 99-107.

Figures/Tables 6

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Research on Ocean Fishery Scientific Data Governance and Application Services

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