植物品种资格审查数据仓库气象条件记录的特点

S. Melnyk, N. Leschuk, N. Orlenko, E. M. Starychenko, K. M. Mazhuha, Y. A. Shkapenko
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引用次数: 0

摘要

意图开发一个多维数据存储模型,用于植物品种的资格审查,以确定气象条件,并结合经过DUS和SVD专业知识的品种的发育阶段。方法。为了建立多维数据仓库的主要结构元素,采用了归纳、推导、分析和综合的方法进行研究。在仓储设施的设计过程中,应用了W.H.Inmon的概念,适用于农业和农业企业。后果分析了植物品种资格审查的各个阶段,并考虑了创建多维数据仓库模型的方法论方法。强调了使用数据存储来存储植物品种的清晰度、一致性和稳定性鉴定结果(DUS)以及品种在乌克兰传播的适宜性(SVD)的特点。根据电子领域期刊上的记录,特别注意植物品种资格审查结果与植物生长和发育各个酚期的气象观测数据之间的相互联系。在MS SQL Server环境下设计并实现了数据仓库的逻辑数据模型。结论。确定了进入数据仓库的数据来源,并根据“雪花”方案实施了多维数据仓库模型。介绍了数据仓库图,该图提供了实地实验的气象条件与资格审查的初步数据之间的联系,并有四个测量表。对于每个维度表和事实表,都定义了数据的属性组成。数据仓库被实际用于分析天气条件对DUS和SVD检查指标的影响。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Features of recording of meteorological conditions in the data warehouse of qualification examination of plant varieties
Purpose. To develop a multidimensional model of the data storage for the qualification examination of plant varieties for fixing meteorological conditions in conjunction with the phenological stages of development of varieties that undergo DUS and SVD expertise. Methods. To conduct research with the establishment of the main structural ele­ments of a multidimensional data warehouse, methods of induction, deduction, analysis and synthesis were used. In the design process of the storage facility, W. H. Inmon’s concept was applied, adapted for the agricultural and agricultural business. Results. The stages of qualification examination of plant varieties were analyzed and methodolo­gical approaches to the creation of a multidimensional data warehouse model were considered. The features of the use of data storages for storing the results of qualification exa­mination of plant varieties for distinctness, uniformity and stability (DUS) and suitability of a variety for dissemination in Ukraine (SVD) were highlighted. Particular attention was paid to the implementation of the interconnection between the results of the qualification examination of plant varie­ties with the data of meteorological observations at various phenological stages of plant growth and development, according to the records in the electronic field journal. The logical data model of the data warehouse was designed and implemented in the MS SQL Server environment. Conclusions. Sources of data entry into data warehouses were determined and a multidimensional data warehouse model was implemented according to the “snowflake” scheme. The diagram of the data warehouse was presented, which provided a link between the meteorological conditions of the field experiments and the initial data of the qualification examination, and had four tables of measurements. For each dimension table and fact table, an attribute composition of the data was defined. The data warehouse was practically used to analyze the influence of weather conditions on the indicators of DUS and SVD examinations.
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