Journal of Agricultural Big Data >

2020 , Vol. 2 >Issue 4: 29 - 37

DOI: https://doi.org/10.19788/j.issn.2096-6369.200404

Research on Opening sharing and Application of Fishery Scientific Observation Data

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  • 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: 2020-10-19

  Online published: 2021-03-11

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Abstract

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.

Key words： fishery scientific observation data; scientific data management; data convergence; data sharing; standard system

Cite this article

Muhan Xue, Huiyuan Liu, Feng Lu, Qingzhao Jiang . Research on Opening sharing and Application of Fishery Scientific Observation Data[J]. Journal of Agricultural Big Data, 2020 , 2(4) : 29 -37 . DOI: 10.19788/j.issn.2096-6369.200404

References

1 王立华,孙璐,孙英泽,等.渔业科学数据共享平台建设研究[J].中国海洋大学学报,2010, 40(S1): 201-206.
1 Wang L H, Sun L,Sun Y Z, et al. Construction of Fishery Scientific Data Sharing Platform [J]. Periodical of Ocean University of China, 2010, 40(S1): 201-206.
2 鲁峰,王立华,徐硕.渔业科学数据中心建设研究.农业大数据学报[J], 2019, 1(3): 57-70.
2 Lu F, Wang L H, Xu S. Research on Construction of Fisheries Science Data Center [J]. Journal of Agricultural Big Data, 2019, 1(3): 57-70.
3 蔡研聪,黄梓荣,孙铭帅,等.南海北部近海渔业资源密度概率分布特征[J].应用生态学报,2019, 30(07):2426-2436.
3 Cai Y C, Huang Z R, Sun M S, et al. Probability distribution characteristics of fishery resources density in the northern South China Sea [J]. Journal of Applied Ecology, 2019, 30(07):2426-2436.
4 孙忠富,杜克明,郑飞翔,等. 大数据在智慧农业中的研究与应用展望[J]. 中国农业科技导报.2013, 15(6): 63-71.
4 Sun Z F,Du K M,Zheng F X,et al. Perspectives of Research and Application of Big Data on Smart Agriculture[J].Journal of Agricultural Science and Technology, 2013,15(6):63-71.
5 程锦祥,孙英泽,胡婧,等.我国渔业大数据应用进展综述[J].农业大数据学报,2020,02(01):11-20.
5 Cheng J X, Sun Y Z, Hu J,et al.Progress in the Application of Big Data in fishery in China[J].Journal of Agricultural Big Data,2020,02(01):11-20.
6 Niwa, H S. Exploitation Dynamics of Fish Stocks [J].Ecological Informatics, 2006, 1(1): 87-99.
7 Huang J, Meng X, Xie Q, et a1. Complete sets of aquaculture automation equipment and their monitoring cloud platform [J]. Advances in Intelligent Systems and Computing, 2017, 691:429-435.
8 Tacon A G J, Metian M, Turchini G M, et al. Responsible Aquaculture and Trophic Level Implications to Global Fish Supply [J]. Reviews in Fisheries Science, 2009, 18(1): 94-105.
9 林娜,黄硕琳.美国地区渔业管理委员会的决策机制探究[J].上海海洋大学学报,2017,26(3):465-472.
9 Lin N, Huang S L.Study on the decision making mechanism of regional fishery management committee in the United States [J]. Journal of Shanghai Ocean University, 2017,26(3):465-472.
10 Sigler M, DeMaster D, Boveng P, et al. Advances in Methods for Marine Mammal and Fish Stock Assessments: Thermal Imagery and CamTrawl [J]. Marine Technology Society Journal, 2015, 49(2): 99-106.
11 Apeti D A, Lauenstein G G, Evans D W, et al. Recent Status of Total Mercury and Methyl Mercury in The Coastal Waters of The Northern Gulf of Mexico Using Oysters and Sediments From NOAA's Mussel Watch Program [J]. Marine Pollution Bulletin, 2012, 64(11): 2399-2408.
12 Froese Rainer, Winker Henning, Coro Gianpaolo, et al. Status and rebuilding of European fisheries [J]. Marine Policy, 2018, 93:159-170.
13 Man Liu，Guilin Han, Qian Zhang. Effects of agricultural abandonment on soil aggregation, soil organic carbon storage and stabilization: Results from observation in a small karst catchment, Southwest China [J]. Agriculture, Ecosystems and Environment, 2020, 288.
14 Zhi Chen, Yan Liu, Chaojie Yang, et al. Analysis of Ways to Strengthen the Management of Marine Fishery Resources in China in the New Period [J]. Lifelong Education, 2020, 9(6).
15 Luoliang Xu, Mazur Mackenzie, Xinjun Chen, et al. Improving the robustness of fisheries stock assessment models to outliers in input data [J]. Fisheries Research, 2020, 230.
16 Li Si, Yueting Li, Xiaozhe Zhuang, et al. An empirical study on the performance evaluation of scientific data sharing platforms in China [J]. Library Hi Tech, 2015, 33(2):211-229.
17 Lokhande P. C., Shirdhankar M. M., Chaudhari K. J.. Digitization of Inland Water Resources for Fisheries through Remote Sensing and Geographical Information System - A Study in Ratnagiri District [J], Fishery Technology, 2017, 54(2):86-93.
18 Shamsuzzaman, Md. Mostafa, Xu Xiangmin,et al. Sustainable Marine Fisheries Resources of Bangladesh: A Strategic Response for Economic Security [J].Indian journal of marine sciences, 2017, 46(4):757-765.
19 王伟,焦飞翔,陈磊等.地质数据集成与共享服务模式研究与应用——以泰州市为例[J].国土资源信息化,2020(04):50-55.
19 Wang W, Jiao F X, Chen L, et al. Research and application of geological data integration and shared service patterns-A case study of Taizhou city [J]. Land and Resources Informatization, 2020,(04):50-55.
20 Huiyan Gao, Hongquan Liu, Chunling Chai, et al. Research on the Service Mode of University Library based on Data Mining [J]. World Scientific Research Journal, 2020, 6(7).
21 Jagoda Walny, Christian Frisson, Mieka West, et al. Data Changes Everything: Challenges and Opportunities in Data Visualization Design Handoff [J]. IEEE transactions on visualization and computer graphics, 2020, 26(1):12-22.
22 Niida A, Hasegawa T, Miyano S (2019) Sensitivity analysis of agent-based simulation utilizing massively parallel computation and interactive data visualization[J/OL]. PLoS ONE14(3): e0210678.
23 张小琼,梁苑苑,邓力涌,等.运维数据可视化展示平台的设计与实现[J].气象研究与应用,2019,40(01):84-87.
23 Zhang X Q, Liang Y Y, Deng L Y, et al. Design and implementation of operation and maintenance data visualization platform [J]. Meteorological research and Application, 2019, 40(01):84-87.
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