农业科学数据在线分析挖掘平台设计与应用
收稿日期: 2024-03-29
录用日期: 2024-05-16
网络出版日期: 2025-06-23
基金资助
国家重点研发计划(2022YFF0711805);国家重点研发计划(2022YFF0711801);国家自然科学基金(31971792);国家自然科学基金(32160421);中国农业科学院创新工程(CAAS-ASTIP-2023-AII);中国农业科学院创新工程(ZDXM23011);中国农业科学院创新工程(ZDXY23011);三亚中国农业科学院国家南繁研究院南繁专项(YBXM2312);三亚中国农业科学院国家南繁研究院南繁专项(YDLH01);三亚中国农业科学院国家南繁研究院南繁专项(YDLH07);三亚中国农业科学院国家南繁研究院南繁专项(YBXM10);中央级公益性科研院所基本科研业务费专项(JBYW-AII-2023-06);三亚崖州湾科技城科技专项(SCKJ-JYRC-2023-45)
Design and Application of Online Analysis and Mining Platform for Agricultural Science Data
Received date: 2024-03-29
Accepted date: 2024-05-16
Online published: 2025-06-23
随着数据驱动科学研究范式的发展,农业科学数据在科技创新中的作用越来越突出,随之而来的是农业科学数据分析挖掘和应用方法与技术研究也不断发展。围绕农业科学数据分析挖掘存在数据语义孤岛严重,以及数据挖掘工具不全、不配套与场景适应性差等突出问题。本文设计了平台架构,构建了分析挖掘引擎,加载了典型和专业分析挖掘算子工具,形成了农业科学数据在线分析挖掘平台,包括数据层、领域数据分析工具层、自动化挖掘框架层、在线分析引擎,以及用户界面层5个层次,开发了数据管理、组件管理、场景管理、挖掘分析4大功能模块。平台具备应用场景管理、在线分析、自动化挖掘等功能,突破“数据资源—分析工具—应用场景”衔接不畅的问题,形成集数据资源、分析模型、组件工具、场景分析和标准流程于一体的在线分析挖掘应用环境,支撑从“数据聚合—挖掘分析链—在线分析—场景应用”的农业科学数据在线分析挖掘全过程,实现超大规模数据及不同场景分析应用的并发在线交互计算分析。
李佳乐 , 林佳 , 贺子康 , 王健 , 张建华 , 周国民 . 农业科学数据在线分析挖掘平台设计与应用[J]. 农业大数据学报, 2025 , 7(2) : 183 -192 . DOI: 10.19788/j.issn.2096-6369.000045
With the development of data-driven scientific research paradigm, the role of agricultural science data in science and technology innovation is becoming more and more prominent, and consequently the methodological and technological research on the analysis and mining and application of agricultural science data is also developing, around the analysis and mining of agricultural science data there are still data semantic silos serious, as well as the data mining tools are incomplete, mismatched and poor adaptability of the scenarios, such as the outstanding problems.In this paper, we designed the platform architecture, constructed the analysis and mining engine, loaded the typical and professional analysis and mining algorithm tools, formed the online analysis and mining platform for agricultural scientific data, including the data layer, the domain data analysis tool layer, the automated mining framework layer, the online analysis engine layer, and the user interface layer, and developed four functional modules, namely, the data management, the component management, the scenario management, and the mining analysis. The platform is equipped with application scenario management, online analysis, automated mining and other functions, breaking through the problem of poor connection of "data resources-analysis tools-application scenarios", forming an online analysis and mining application environment integrating data resources, analysis models, component tools, scenario analysis and standard processes, supporting the whole process of online analysis and mining of agricultural scientific data from "data aggregation - mining and analysis chain - online analysis - scenario application", and realizing the concurrent online interactive computation and analysis of ultra-large-scale data and different scenario analysis applications.
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