基于区块链的渔业种质资源管理系统设计

Design of Fishery Germplasm Resource Management System Based on Blockchain

针对传统渔业种质资源管理系统存在的数据中心化存储、数据易篡改和数据信任,以及难以高效获取与利用多源异构渔业疾病数据等问题,在分析区块链与知识图谱关键技术的基础上,设计了渔业种质确权可信溯源区块结构,确保渔业种质溯源数据不可伪造和安全可信;提出了“On-Chain+Off-Chain”渔业种质资源可信确权信息协同管理存储策略,解决渔业种质资源溯源区块链网络中各节点数据存储压力大、查询效率低等问题;构建渔业疾病知识图谱,实现渔业疾病数据隐藏关系的有效挖掘;基于微服务技术研制了集种质确权、品种选择、疾病防治、知识图谱、环境智能预测等一体化的渔业种质资源管理系统,实现渔业种质资源可信确权与管理、渔业养殖品种智能分析与决策、海量异构的渔业疾病知识资源池的集成与共享、环境参数(溶解氧浓度、酸碱度等)智能预测预警等功能。测试结果表明,该系统解决了溯源信息真实可信的问题,有效挖掘出渔业疾病数据中隐藏的关系,并取得了较好的应用效果。

Aiming at the problems of data center storage,data tampering and data trust in traditional fishery germplasm resource management system,as well as the difficulty in efficient acquisition and utilization of multi-source heterogeneous fishery disease data,based on the analysis of key technologies of blockchain and knowledge graph,the structure of fishery germplasm confirmation and trusted traceability block was designed to ensure the unforgeability and security of fishery germplasm traceability data.The collaborative management and storage strategy of'On-Chain+Off-Chain'fishery germplasm resources credible confirmation information is proposed to solve the problems of high data storage pressure and low query efficiency of each node in the fishery germplasm resources traceability blockchain network.The fishery disease knowledge graph is constructed to realize effective mining of hidden relationship of fishery disease data.Based on micro-service technology,a fishery germplasm resource management system integrating germplasm confirmation,variety selection,disease prevention and control,knowledge map and environmental intelligent prediction was developed to realize the functions of credible confirmation and management of fishery germplasm resources,intelligent analysis and decision-making of fishery breeding varieties,integration and sharing of massive heterogeneous fishery disease knowledge resource pools,intelligent prediction and early warning of environmental parameters(dissolved oxygen concentration,pH,etc.).The test results show that the system solves the problem of authenticity and credibility of traceability information,effectively excavates the hidden relationship in fishery disease data,and achieves good application results.