我国渔业大数据应用进展综述

doi:10.19788/j.issn.2096-6369.200102

摘要/Abstract

摘要：

渔业大数据已成为渔业绿色发展的重要资源要素,也是重要的渔业科技创新方向,不仅直接促进渔业的生产、经营、管理和服务,而且在渔业三产融合中发挥着举足轻重的作用。我国是世界第一水产养殖大国，我国也非常重视渔业大数据在现代渔业中的研究与应用发展。由于历史和现实原因，渔业数据具有资源途径多样、结构繁杂、质量参差不齐、应用范畴宽广，数据总体质量偏低的特点,因此系统梳理渔业大数据应用进展,进一步明确未来发展方向,对我国渔业大数据的研究和应用具有重要意义。本文通过文献调研并结合相关科研实践,对比分析了不同学者对渔业大数据的定义,阐述了渔业大数据的概念，介绍了其多种来源和主要特征,梳理了渔业大数据的管理与政策进展，重点关注了近年来渔业大数据在科学研究、养殖管理、资源调查、经济流通等方面的开发与应用，并结合工程实践，探索了渔业大数据的场景化应用。最后,根据我国渔业大数据发展的现状,指出问题与挑战,为进一步促进我国渔业大数据的发展提供建议。

关键词: 渔业大数据, 应用进展, 渔业科学数据, 大数据

Abstract:

Big data has become an essential resource for green fisheries, and is an important focus for innovation in fisheries science and technology. Big data promotes the production, operation, management, and service provisions of fisheries, and plays a pivotal role in advancing the integration of primary, secondary, and tertiary industries in fisheries. China is the largest aquaculture country in the world, and attaches great importance to research and application development of big data in modern fisheries. For historical and practical reasons, fisheries big data is characterized by diversified resource channels, complex structures, uneven quality, wide application scope, and low overall data quality. Therefore, for research on, and application of fisheries big data in China, it is important to review the progress regarding the application of such data systematically, and clarify the direction of future development. Based on literature research and related scientific research practices, this article compares and analyzes the definitions of fisheries big data by different scholars; elaborates on the concept of fisheries big data; introduces the multiple sources and main characteristics of fisheries big data; and reviews the management and policy progress of fisheries big data. The development and application of fisheries big data in recent years have focused mainly on scientific research, aquaculture management, resource investigation, and economic circulation. In combination with engineering practice, this article explores the scenario application of fisheries big data. Finally, based on the current situation, it identifies the problems and challenges, and provides suggestions for further promoting the development of fisheries big data in China.

Key words: big data in fishery, progress in application, scientific data in fishery, big data

中图分类号:

G203

程锦祥, 孙英泽, 胡婧, 闫雪, 欧阳海鹰. 我国渔业大数据应用进展综述[J]. 农业大数据学报, 2020, 2(1): 11-20.

Jinxiang Cheng, Yingze Sun, Jing Hu, Xue Yan, Haiying Ouyang. Progress in the Application of Big Data in fishery in China[J]. Journal of Agricultural Big Data, 2020, 2(1): 11-20.

参考文献 55

1	我国水产养殖量约占世界总量 62%，如遇“渔周期”该怎么办呢 [Ｒ/OL]海尔产业金融农业食品，2019-09-17. .
	China's aquaculture production accounts for about 62 % of the world's total. What should we do if it encounters a "fishing cycle"? Haier Industrial Finance Agricultural Food. 2019-09-17. .
2	李道亮 . 物联网支撑现代渔业大数据助推产业升级[J]. 中国科技产业,2016(2): 78-79.
	Li D L . Internet of Things supports modern fishery big data to promote industrial upgrading [J]. Science & Technology Industry of China, 2016(2): 78-79.
3	王东杰,李哲敏,张建华,等 . 农业大数据共享现状分析与对策研究[J]. 中国农业科技导报,2016,18(3): 1-6.
	Wang D J ， LI Z M ， Zhang J H ，et al . Current Situation and Countermeasures of Agricultural Data Sharing[J]. Journal of Agricultural Science and Technology, 2016,18(3): 1-6.
4	戴春晨 . 农业大数据展望：六大领域数据亟待推广[J]. 营销界（农资与市场）,2016(1): 69-70.
	Dai W C . Agricultural big data outlook: data in six major areas needs to be promoted [J]. Marketing (agricultural resources and market), 2016(1): 69-70.
5	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.
	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.
6	IBM-全球企业咨询服务部 .分析:大数据在现实世界中的[R/OL]. http : //www- 935.ibm.com/services/multimedia/use_of_big_data.pdf. 2012.
	IBM-Global Business Consulting Services . Analysis: Big Data in the Real World. http: //www-935.ibm.com/services/multimedia/use_of_big_data.pdf. 2012.
7	姚远,赵荣彩 . 基于编译指示的向量化方法[J]. 计算机工程,2012,38(12): 272-275.
	Yao Y , Zhao R C . Vectorization Method Based on Compiler Directive[J]. Computer Engineering,. 2012,38(12): 272-275.
8	杨宝琴推荐 . 来源:当代水产，智能化养殖开启渔业“大数据时代” [J]. 水产科技情报,2015,42（2）: 104.
	Yang B Q Source: Contemporary aquatic products,Intelligent farming Opens the “big data era” of fisheries [J]. Aquatic Science and Technology Information, 2015,42（2）: 104.
9	周洵 . 大数据技术与中国渔业 [J]. 中国水产,2015（8）: 31-33.
	Zou X . Big data technology and Chinese fishery [J]. China Fisheries, 2015（8）: 31-33.
10	段青玲,刘怡然,张璐,等 . 水产养殖大数据技术研究进展与发展趋势分析[J]. 农业机械学报,2018,49(6): 1-16.
	Duan Q L , Liu Y R , Zhang L , et al . State-of-the-art Ｒeview for Application of Big Data Technology in Aquaculture[J]. Transactions of the Chinese Society for Agricultural Machinery. 2018,49(6): 1-16.
11	于喆 . 渔业大数据综述[J]. 安徽农业科学,2017,45(9): 211-213.
	Yu Z . Review of Fishery Big Data[J]，Journal of Anhui Agri．2017,45(9): 211-213.
12	王志勇 . 水产养殖大数据技术研究进展与发展形势[J]. 农家科技（上旬刊）, 2018(9): 95.
	Wang Z Y . Research progress and development situation of big data technology in aquaculture [J]. NongJia KeJi, 2018(9): 95.
13	中华人民共和国国务院 . 促进大数据发展行动纲要[EB／OL]. http：∥Www．gov．cn／zhengce／contenL／2015—09／05／content—10137．htm，2015—08—31.
	State Council of the People's Republic of China . Action Plan for Promoting Big Data Development.gov. http：∥Www．gov．cn／zhengce／contenL／2015—09／05／content—10137．htm，2015—08—31.
14	中国渔业报, 大数据催生渔业增值 . 渔业致富指南[J], 2018(16): 3-4.
	China Fisheries News, Big data boosts fisheries . Fishery Guide to be Rich[J], 2018(16): 3-4.
15	黄秀芸 . 新时代“互联网+水产养殖”发展路径研究[J]. 农家参谋, 2019, 612(05):129.
	Huang X Y . Research on the Development Path of "Internet + Aquaculture" in the New Era [J]. Farm Staff, 2019, 612 (05): 129.
16	岳冬冬,方辉,樊伟,李来好,等 .中国智能渔业发展现状与技术需求探析[J].渔业信息与战略,2019,34(02):79-88.
	Yue D D , Fang H , Fan W , et al .Analysis on the Status Quo and Technology Demands of Intelligent Fishery Development in China [J] .Fishery Information and Strategy, 2019,34 (02): 79-88.
17	黄孝鹏,鲍鹏飞,萧毅鸿,等 .区域化海洋渔业环境智能观测与决策支持设计[J].计算机应用与软件,2019,36(03):84-88+130.
	Huang X P , Bao P F , Xiao Y H , et al .Intelligent Observation and Decision Support Design of Regional Marine Fishery Environment [J] .Computer Applications and Software, 2019,36 (03): 84-88 + 130.
18	赵晨光,孙庚,冯艳红,等 .渔业领域智能问答系统的研究[J].电脑编程技巧与维护,2019(05):111-113.
	Zhao C G , Sun G , Feng Y H ,et al .Research on Intelligent Question Answering System in Fishery Field [J] .Computer Programming Skills and Maintenance, 2019 (05): 111-113.
19	茆毓琦 . 基于大数据技术的智慧水产养殖系统研究[D].青岛科技大学,2018.
	Mao Y Q . Research on Smart Aquaculture System Based on Big Data Technology [D] .Qingdao University of Science and Technology, 2018.
20	唐峰华,靳少非,张胜茂,等 .北太平洋柔鱼渔场时空分布与海洋环境要素的研究[J].中国环境科学,2014,34(08):2093-2100.
	Tang F H , Jin S F , Zhang S M , et al .Study on Spatial-Temporal Distribution and Marine Environmental Factors of Ommastrephes bartrami in the North Pacific [J] .China Environmental Science, 2014,34 (08): 2093-2100.
21	戴立峰,张胜茂,樊伟 .南极磷虾资源丰度变化与海冰和表温的关系[J].极地研究,2012,24(04):352-360.
	Dai L F , Zhang S M , Fan W .Relationship between Antarctic krill resource abundance changes and sea ice and surface temperature [J] .Polar Research, 2012,24 (04): 352-360.
22	张衡,张胜茂 .东南太平洋智利竹筴鱼渔场及单位捕捞努力量的时空分布[J].生态学杂志,2011,30(06):1142-1146.
	Zhang H , Zhang S m .Temporal and Spatial Distribution of Chilean Pike Fish Farm and Unit Fishing Effort in Chile in the Southeast Pacific [J] .Chinese Journal of Ecology, 2011,30 (06): 1142-1146.
23	汤伟 . 海洋渔业地理格网模型研究与设计[D].浙江海洋大学,2018.
	Tang W . Research and design of marine fishery geographic grid model [D] .Zhejiang Ocean University, 2018.
24	甄爱军 . 基于ASP-NET的水产病害图谱管理系统的设计与实现[J]. 水产养殖, 2015(12):7-10.
	Zhen A J . Design and Implementation of Aquatic Disease Atlas Management System Based on ASP-NET [J]. Aquaculture, 2015 (12): 7-10.
25	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.
26	Feng Y , Wang X N ． LI H T . Research and construction of intelligent service platform for aquaculture[C].∥5 th International　Conference on Frontiers of Manufacturing Science and Measuring Technology. 2017,130: 801—804.
27	叶炼炼 . 海洋水产养殖数据分析和云计算研究[J]. 信息与电脑(理论版), 2016(07): 123-124.
	Ye L L . Marine aquaculture data analysis and cloud computing research [J]. China Computer&Communication, 2016(07): 123-124.
28	冯菲 .大数据技术在南海鸢乌贼资源调查上的研究进展[J]. 安徽农业科学,2018(33): 12-13, 18.
	Feng F . Research Progress of Big Data Technology in the Investigation of the Sthenoteuthis oualaniensis Resources in the South China Sea[J]. Journal of Anhui Agricultural Sciences, 2018(33): 12-13, 18.
29	党子乔 .大数据环境下水生生物增殖放流工作的思考. 中国水产,2019(6): 40-42.
	Dang Z Q . Thoughts on the proliferation and release of aquatic organisms under the big data environment[J]. China Fisheries,2019(6): 40-42.
30	一帅 .普中国·乡村e站大数据助力水产互联开拓乡村振兴之路[J]. 今日农业,2018(8).
	Yi S . Pu China·Country e station big data helps the aquatic products to open up the road to rural revitalization[J]. Agriculture today, 2018 (8).
31	农业部科技教育司 .农业部关于启动农业基础性长期性科技工作的通知[EB／OL]. 2017-03-25 00:00 .
	Department of Science and Technology Education of the Ministry of Agriculture. Notice of the Ministry of Agriculture on Launching Basic Long-term Scientific and Technological Work in Agriculture. 2017-03-25 00:00 .
32	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(自然科学版),2010.,40(S1): 201-206.
	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.
33	曾首英,欧阳海鹰, 中国水产种质资源保存共享现状与建议 [J]. 现代渔业信息,2008(4): 9-12.
	Zeng S Y ， Ouyang H Y . Sharing Status and Suggestion on Conservation of Fish Germplasm Resources in China[J]. Modern Fisheries Information, 2008(4): 9-12.
34	马卓君,刘英杰 . 我国水产种质资源平台建设的需求与现状[J]. 中国水产,2009(11): 25-27.
	Ma Z J , Liu Y J . Demand and current status of China's aquatic germplasm resources platform construction[J]. China Fisheries, 2009(11): 25-27.
35	我国水产种质资源共享平台服务社会化[J]. 江西饲料,2006(4): 45.
	China's aquatic germplasm resources sharing platform service socialization. Jiangxi feed, 2006(4): 45.
36	李道亮 . 信息化支撑渔业现代化产学研协作助推产业升级--中国渔业物联网与大数据产业创新联盟成立大会暨水产养殖信息化论坛侧记[J]. 中国科技产业,2016(4): 57-57.
	Li D L . Informatization supports fishery modernization, industry-university-research cooperation, and promotes industrial upgrading--A Sidelight on the Establishment of China Fishery Internet of Things and Big Data Industry Innovation Alliance and Aquaculture Informatization Forum [J]. Science & Technology Industry of China, 2016(4): 57-57.
37	传道授业解众惑经世致用展雄才——访中国农业大学信息与电气工程学院教授、中国渔业物联网与大数据产业创新联盟执行理事长李道亮[J]. 中国水产,2016(9): 54-56.
	Preaching to teach the public to solve the confession and making practical use to show the talents - Interview with Professor Li Daoliang of Information and Electrical Engineering, China Agricultural University, Executive Director of China Fishery Internet of Things and Big Data Industry Innovation Alliance [J]. China Fisheries, 2016(9): 54-56.
38	韩超 . 渔业大数据研究院将成立[J]. 水产科技情报,2018(4): 234.
	Han C . Fisheries Big Data Research Institute will be established [J]. Aquatic Science and Technology Information, 2018(4): 234.
39	渔业协会将成立中国渔业大数据研究院 . 甘肃畜牧兽医, 2018(5): 9-10.
	China Fisheries Association will establish China Fisheries Big Data Research Institute. Gansu Animal Husbandry and Veterinary, 2018(5): 9-10.
40	吴佳辉 . 九项指标居全球首位,中国渔业大数据研究院落成[J]. 海洋与渔业·水产前沿,2018(7): 12.
	Wu J H . Nine indicators rank first in the world, and China Fishery Big Data Research Institute is established [J]. Ocean and Fishery, 2018(7): 12.
41	唐启升院士、崔利锋院长出席“ 2018大数据智能与知识服务高端论坛暨农林渔知识服务产品发布会”. .
	Academician Tang Qisheng and Dean Cui Lifeng attended the " 2018 Big Data Intelligence and Knowledge Service High-end Forum and Agricultural, Forestry and Fishery Knowledge Service Product Launch Conference". .
42	2018大数据智能与知识服务高端论坛，暨农林渔知识服务产品发布会在青岛召开. .
	2018 Big Data Intelligence and Knowledge Service High-end Forum, and Agriculture, Forestry and Fishery Knowledge Service Product Launch Conference Held in Qingdao. .
43	梁蔚浩,徐承旭 . 上海打造淡水鱼产地追溯大数据全程可监管[J]. 水产科技情报,2019,46(02): 68.
	Liang W H , Xu C X . Freshwater fish origin traceable big data can be supervised throughout the process in Shanghai [J]. Fisheries Science & Technology Information, 2019, 46 (02): 68.
44	编辑部当代水产 . 帮邦:打造大数据,构建水产O2O服务新平台——本刊专访帮邦总经理万奎吉[J]. 当代水产,2015(5): 36-37.
	The editorial department of contemporary aquatic products . Bangbang: build big data and a new platform for aquatic O2O services - interview with Wan Kuiji, general manager of Bangbang [J]. Contemporary aquatic products, 2015(5): 36-37.
45	青岛帮邦信息科技有限公司 . 百度百科 https://baike.baidu.com/item/青岛帮邦信息科技有限公司/18148385.
	Qingdao Bangbang Information Technology Co., Ltd. .
46	赵红梅 . 京津冀将共建渔业基础信息大数据中心. 农村科学实验, 2017(1): 21.
	Zhao H M . Beijing-Tianjin-Hebei will jointly build a fishery basic information big data center. Scientific Experiment in Countryside, 2017(1): 21.
47	河北省人民政府网站 . 京津冀将共建渔业基础信息大数据中心(来源：河北日报)[N/OL].2017.01.16.
	Hebei Provincial People's Government website . Beijing-Tianjin-Hebei will jointly build a fishery basic information big data center (Source: Hebei Daily).
48	周国民 . 我国农业大数据应用进展综述[J]. 农业大数据学报,2019, 1(01): 16-23.
	Zhou G M . Progress in the Application of Big Data in Agriculture in China[J]. Journal of Agricultural Big Data, 2019, 1(01): 16-23.
49	蔡家轩,杜宏宇,蔡晓童,等 . 面向水产农业的大数据技术应用分析与对策[J]. 南方农机,2019(13): 86-87.
	Cai J X , Du H Y , Cai X T , et al . Application Analysis and Countermeasure of Big Data Technology for Aquatic Agriculture[J]. China Southern Agricultural Machinery,,2019(13): 86-87.
50	唐峰 . Map Reduce 计算模型及其在水产农业中的应用[J]. 科技视界, 2019(17): 115-116，70.
	Tang F , Du H Y , Cai J X , et al . MapReduce Computation Model and its Application in Aquatic Agriculture[J]. Science & Technology Vision. 2019(17): 115-116，70.
51	紫琳 . 利用卫星大数据助力水产养殖[J]. 中国食品,2016(21): 124-125.
	Zi L . Using satellite big data to help aquaculture[J]. China Food, 2016(21): 124-125.
52	李钒, 欧盟采用“天眼”和大数据助力水产养殖[J]. 海洋与渔业·水产前沿,2016(11): 78-78.
	Li F . EU adopts "eyes" and big data to help aquaculture [J]. Ocean and Fishery, 2016(11): 78-78.
53	智慧渔船船联网系统[J]. 船舶工程, 2018,(4).
	Smart fishing boat network system [J]. Ship Engineering, 2018,(4).
54	郭承坤,刘延忠,陈英义,等 . 发展农业大数据的主要问题及主要任务[J]. 安徽农业科学,2014,42（27）: 9642-9645.
	Guo C K , Liu Y Z , Chen Y Y , et al . Major Issues and Missions in Agricultural Big Data[J]. Journal of Anhui Agricultural Sciences, 2014,42（27）: 9642-9645.
55	王东雨,等 . 我国水产大数据及应用技术研究初探. 山东农业科学,2016.48(10): 152-156.
	Wang D Y ， Zheng J Y ， Wang D , et al . Primary Research of Fishery Big Data andApplication Technology in China[J]. Shandong Agricultural Sciences, 2016.48(10): 152-156.

[1]	陈彦清, 曹永生, 林雨楠, 方沩. 国家作物种质资源观测鉴定站点体系布局方法研究[J]. 农业大数据学报, 2020, 2(4): 20-28.
[2]	吕佳乐, 徐学农. 大数据驱动的天敌资源调查与监测体系构建研究[J]. 农业大数据学报, 2020, 2(4): 78-85.
[3]	胡国铮, 干珠扎布, 余沛东, 杨振琳, 高清竹. 基于农业环境的农业科学观测数据融合研究[J]. 农业大数据学报, 2020, 2(4): 86-94.
[4]	王文生. 可信区块链在农业农村应用展望[J]. 农业大数据学报, 2020, 2(2): 14-24.
[5]	孙忠富, 马浚诚, 郑飞翔, 杜克明. 区块链支撑农业大数据安全初探[J]. 农业大数据学报, 2020, 2(2): 25-37.
[6]	刘克宝, 毕洪文, 李杨, 陆忠军, 张冬梅, 吕志群, 张宇, 王晓楠. 大数据在黑龙江省数字农业中的应用现状与展望[J]. 农业大数据学报, 2020, 2(1): 21-28.
[7]	赵佳, 阮怀军, 封文杰. 大数据在山东马铃薯全产业的应用及建设探索[J]. 农业大数据学报, 2020, 2(1): 29-35.
[8]	孙素芬, 赵继春, 郭建鑫, 乔珠峰, 陈会娜, 王敏. 农民远程教育大数据分析平台设计与实现[J]. 农业大数据学报, 2020, 2(1): 3-10.
[9]	张萌, 董伟, 钱蓉, 杨前进, 张立平. 安徽省植保大数据平台建设与应用展望[J]. 农业大数据学报, 2020, 2(1): 36-44.
[10]	张辉, 冯晓, 王来刚, 李国强, 乔璐, 魏东, 郑国清. 花生大数据平台建设研究和展望[J]. 农业大数据学报, 2020, 2(1): 45-52.
[11]	王来刚, 郭燕, 王利军, 贺佳, 张彦, 杨秀忠, 张红利, 郑国清. 河南省秋季作物空间分布“一张图”遥感制作[J]. 农业大数据学报, 2020, 2(1): 53-59.
[12]	高文波, 何鹏, 林正雨, 张媛. 气候变化背景下四川省热量资源时空变化特征研究[J]. 农业大数据学报, 2020, 2(1): 60-69.
[13]	吕新, 梁斌, 张立福, 马富裕, 王海江, 刘阳春, 高攀, 张泽, 侯彤瑜. 新疆生产建设兵团棉花生产大数据平台建设与探索[J]. 农业大数据学报, 2020, 2(1): 70-78.
[14]	温希军, 李捷, 王琼. 新疆畜牧业经济信息服务平台建设与应用[J]. 农业大数据学报, 2020, 2(1): 79-83.
[15]	刘海清, 卢琨, 刘晓珂, 梁伟红. 农业科学大数据资源平台在热区的实践思考[J]. 农业大数据学报, 2019, 1(4): 58-64.