Journal of Agricultural Big Data >

2022 , Vol. 4 >Issue 2: 99 - 107

DOI: https://doi.org/10.19788/j.issn.2096-6369.220215

Research on Ocean Fishery Scientific Data Governance and Application Services

Expand
  • 1.Institute of Fisheries Engineering, Chinese Academy of Fishery Sciences, Beijing 100141, China
    2.Pilot National Laboratory for Marine Science and Technology (Qingdao), Qingdao 266237, China

Received date: 2022-03-01

  Online published: 2022-11-08

Fold

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

Cite this article

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 . DOI: 10.19788/j.issn.2096-6369.220215

References

1 司莉,曾粤亮.机构科研数据知识库联盟数据治理框架研究[J]. 图书馆论坛,2018,(8):61-67.
1 Si L, Zeng Y L. Research on data governance framework of institutional research data knowledge base alliance [J]. Library forum, 2018,(8): 61-67.
2 DAMA.The Future of Data Governance: Balancing Data Governance and Data management[EB/OL].[2018-12-27].
3 IBM.What is data governance[EB/OL].[2018-12-27].
4 Wende K, Otto B.A Contingency Approach to Data Governance[A]. International Conference on Informati on Quality.[C]. OAI, 2017:187-198.
5 Kim S.The analysis of data governance model for business and IT alignment［J].Journal of the Korea S ociety of Computer and Information,2013,18(7):69-78．
6 Ke Changwen, Wang Kuisheng.Research and Application of Enterprise Big Data Governance[A].CSAE201 8[C]. New York : ACM Press, 2018:1-5. .
7 张明英,潘蓉.《数据治理白皮书》国际标准研究报告要点解读[J].信息技术与标准化,2015,(6):53-107.
7 Zhang M Y, Pan R. Interpretation of the key points of the International Standards Research Report of the white paper on Data Governance [J]. Information technology and standardization, 2015,(6): 53-107.
8 包冬梅,范颖捷,李鸣.高校图书馆数据治理及其框架[J].图书情报工作.2015,(18):133-541.
8 Bao D M, Fan Y J, Li M. University Library Data Governance and its framework [J]. Library and information work, 2015,(18): 133-541.
9 夏义堃.试论数据开放环境下的数据治理:概念框架与主要问题[J].图书情报知识,2018,(1):95-104.
9 Xia Y K. On data governance in the open data environment: conceptual framework and main issues [J]. Library and information knowledge, 2018, (1): 95-104.
10 徐峰,吴旻瑜,徐萱,等.教育数据治理:问题、思考与对策[J].开放教育研究,2018,(2):107-1 12.
10 Xu F, Wu M Y, Xu X, et al. Education Data Governance: problems, thoughts and countermeasures [J]. Open education research, 2018,(2):107-112.
11 吴善鹏, 李萍, 张志飞. 政务大数据环境下的数据治理框架设计[J]. 电子政务, 2019,(2):7.
11 Wu S P, Li P, Zhang Z F. Data governance framework design in the context of government big data [J]. Electronic Government, 2019,(2): 7.
12 黄冬梅，赵丹枫，魏立斐，等. 大数据背景下海洋数据管理的挑战与对策[J]. 计算机科学，2016, 43(6): 17-23.
12 Huang D M, Zhao D F, Wei L F, et al. Challenges and Countermeasures of marine data management in the context of big data [J]. Computer science, 2016, 43 (6): 17-23.
13 Chen G, Li W, Kong Q, et al. Recent progress of marine geographic information system in China: A review for 2006–2010[J]. Journal of Ocean University of China, 2012, 11(1): 18-24.
14 张春玲, 王振峰, 李宏. 基于最优插值法的Argo数据网格化实验[J]. 海洋测绘, 2012, 32(3):3.
14 Zhang C L, Wang Z F, Li H. Argo data gridding experiment based on optimal interpolation [J]. Marine surveying and mapping, 2012, 32 (3): 3.
15 张威,崔铁军,郭黎,等.一种基于空间数据共享的数据模型的设计与实现[J].测绘与空间地理信息,2007,(6):P139-P143.
15 Zhang W, Cui T J, Guo L, et al. Design and implementation of a data model based on spatial data sharing [J]. Surveying and mapping and spatial geographic information, 2007,(6): 139-143.
16 李郅明, 余荣君, 叶馥榕. 海洋数据仓库的数据清洗规则应用研究[J]. 海洋开发与管理, 2018, 35(2):4.
16 Li Z M, Yu R J, Ye F R. Research on the application of data cleaning rules in marine data warehouse [J]. Ocean development and management, 2018, 35 (2): 4.
17 谭凯中, 秦勃, 何亚文. 面向过程的海洋时空数据分布式存储与并行检索[J]. 中国海洋大学学报（自然科学版）, 2021:51-11.
17 Tan K Z, Qin B, He Y W. Process oriented distributed storage and parallel retrieval of marine spatiotemporal data [J]. Journal of Ocean University of China (NATURAL SCIENCE EDITION), 2021:51-11.
18 Yawen H, Fenzhen S, Yunyan D, et al. Web-based visualization of marine environment data[C]//2010 18th International Conference on Geoinformatics, IEEE, 2010: 1-6.
19 张晓冬,张志强,陈进,等.基于交互仿真的生产决策专家系统构建方法[J].计算机集成制造系统,2013,19(2):404-410.
19 Zhang X D, Zhang Z Q, Chen J, et al. Construction method of production decision expert system based on interactive simulation [J]. Computer integrated manufacturing system, 2013,19 (2): 404-410.
20 郭刚刚, 樊伟, 张胜茂,等. 船位监控系统数据挖掘与应用研究进展[J]. 海洋渔业, 2016, 38(2):8.
20 Guo G G, Fan W, Zhang S M, et al. Research progress in data mining and application of ship position monitoring system [J]. Marine fisheries, 2016, 38 (2): 8.
21 纪世建, 周为峰, 樊伟,等. 中国远洋作业渔场海表温度异常年际变动分析[J]. 海洋科学, 2016(1):9.
21 Ji S J, Zhou W F, Fan W, et al. Analysis on the interannual variation of sea surface temperature anomalies in China's pelagic fishing grounds [J]. Marine science, 2016 (1): 9.
22 丁慧彦. 基于风险评估的自然灾害应急响应决策优化——以台风渔船回港避风为例[D]. 北京师范大学, 2012.
22 Ding H Y. Optimization of natural disaster emergency response decision-making based on risk assessment —Taking typhoon fishing boats as an example [D]. Beijing Normal University, 2012.
23 Han Q. Architecture of a Marine Information Service Platform: A Cloud Computing Framework[J]. Journal of Coastal Research, 2020, 106(sp1):596.
24 Luo M, Fan Z, Yu T. Marine Information Management Service Platform: A GIS Based Study[J]. Journal of Coastal Research, 2020, 106(sp1):557.
Options
Outlines

/

〈 〉

  • ISSN 2096-6369
  • CN 10-1555/G2
  • Address: No.12 South Street, Zhongguancun, Beijing
  • Zip Code: 100081
  • Telephone: 010-82106275
  • E-mail: agbigdata@caas.cn
website design copyright © Journal of Agricultural Big Data