农业大数据学报 ›› 2021, Vol. 3 ›› Issue (3): 45-54.doi: 10.19788/j.issn.2096-6369.210305

• 专题——农业模型 • 上一篇    下一篇

渔船渔港综合管理服务平台构建与应用

薛沐涵1(), 徐硕1,2(), 鲁峰1,2(), 朱勇1, 吴建光1, 王义刚1   

  1. 1. 中国水产科学研究院渔业工程研究所,北京 100141
    2. 青岛海洋科学与技术试点国家实验室,青岛 266237
  • 收稿日期:2021-04-10 出版日期:2021-09-26 发布日期:2021-12-22
  • 通讯作者: 徐硕,鲁峰 E-mail:1036514981@qq.com;xush_cafs@126.com;lufeng@cafs.ac.cn
  • 作者简介:薛沐涵,女,硕士,研究方向:渔业信息技术与应用;E- mail: 1036514981@qq.com
  • 基金资助:
    山东省支持青岛海洋科学与技术试点国家实验室重大科技专项“船联网关键技术研究”(2018SDKJ0103-2);渔业通信导航与大数据创新团队项目(2020TD84);中国水产科学研究院基本科研业务费专项(2020HY-ZC003)

Construction and Application of a Comprehensive Management Service Platform for Fishing Vessels and Fishing Ports

Muhan Xue1(), Shuo Xu1,2(), Feng Lu1,2(), Yong Zhu1, Jianguang Wu1, Yigang Wang1   

  1. 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:2021-04-10 Online:2021-09-26 Published:2021-12-22
  • Contact: Shuo Xu,Feng Lu E-mail:1036514981@qq.com;xush_cafs@126.com;lufeng@cafs.ac.cn

摘要:

渔船渔港数据是渔船渔港相关业务办理和运营维护中积累的基础性数据,对渔船动态监管、渔港运营管理、船员管理、渔业安全生产、渔获物追溯以及智慧渔港建设等方面具有广泛的应用价值。渔船渔港数据资源的整合、交换与共享,对推动渔船渔港综合管理改革以及提升渔船渔港信息化支撑能力具有重要意义。渔船渔港信息化系统的全面推广和成熟应用,为渔船渔港科学化管理与研究提供了丰富的数据来源和坚实的技术基础。针对渔船渔港现有信息系统建设部署分散,且系统间尚未实现业务协同和数据对接,导致渔船渔港数据资源无法共享,无法实现数据资源价值的最大化的问题,本文以渔船渔港信息资源整合配置与渔业安全生产联动指挥需求为背景,基于数据分类、共享标准、交互模式、模型构建等方法,对数据资源结构、共享元数据标准和信息交互模式展开研究,为渔船渔港综合管理中各个环节的数据特征描述和共享交换模式提供标准化依据,实现渔船渔港数据资源共享,形成安全稳定的信息传递方式,全面提升渔船渔港科学管理与信息化技术应用水平。本研究提出渔船渔港信息交互模型,充分挖掘渔船渔港数据资源的潜在价值,并对数据共享标准和信息交互模式等技术规范进行介绍,同时对该模型应用及推广进行了布局规划。

关键词: 渔船渔港, 数据分类, 数据共享, 信息交互, 模型构建, 渔业大数据

Abstract:

The tracking data of fishing vessels and fishing ports are basic data needed for the management and operational maintenance of businesses related to these entities. These data have wide scientific applications and can add value to the dynamic supervision of fishing vessels, the operation and management of fishing ports, crew management, safety in the fish production chain, catch traceability, and the construction of ‘intelligent’ fishing ports. The integration, sharing, and exchange of such data resources are of great worth for comprehensive fisheries reform and to enhance the capacity of the vessels and ports. A popularized and comprehensively applied shared information system for fishing vessels and the ports that support fishing vessels would provide more abundant data for scientific fisheries management and research. Presently, there is scattered construction and deployment of information systems for fishing vessels and fishing ports, a lack of business collaboration and data docking among the existing systems, no capacity for data sharing among fishing vessels, and failure to maximize the value of the data collected. Based on the integration and allocation of the information resources of fishing vessels and fishing ports and the demand for joint command of safety in fishery production, this study considered the methods currently used for data classification, sharing standards, interaction modes, and model construction. Thereafter, the structure of these data resources, shared metadata standards, and interaction patterns were examined. The study provides a standardized basis for describing the features of specific data sets and for realizing data resource sharing by fishing vessels and fishing ports, as well as the exchange mode of each link; formulates a safe and stable information transmission mode; and improves the levels of information technology applications for fishing vessels and fishing ports. Finally, the study proposes an information interaction model for fishing vessels and fishing ports. This research reveals the high potential value of the data resources of fishing vessels and fishing ports, and introduces technical specifications of data-sharing standards and information interaction modes. In addition, the application and promotion of this model is planned.

Key words: fishing vessels and fishing ports, data classification, data sharing, information interaction, model building, big data in fishery

中图分类号: 

  • G203