论文标题
数据仓库和对综合农作物大数据的决策支持
Data Warehouse and Decision Support on Integrated Crop Big Data
论文作者
论文摘要
近年来，精确农业变得非常流行。引入了用于收集和加工农业数据的现代信息和通信技术彻底改变了农业实践。这已经开始了一段时间（20世纪初），它是由收集有关所有内容的数据的低成本驱动的。从种子，土壤，肥料，害虫等领域的信息，到天气数据，无人机和卫星图像。特别是，今天的农业数据挖掘被认为是数量，多样性，速度和真实性的大数据应用。因此，这导致了处理大量复杂和多样化信息的挑战，以为农民，农艺学家和其他企业提取有用的知识。它是建立作物情报平台的关键基础，该平台将实现有效的资源管理和高质量的农艺决策和建议。在本文中，我们设计并实施了大陆级农业数据仓库（ADW）。 ADW的特征是其（1）柔性模式； （2）来自实际农业多数据集的数据集成； （3）数据科学和商业智能支持； （4）高性能； （5）高存储； （6）安全； （7）治理和监测； （8）一致性，可用性和分区耐受性； （9）云兼容性。我们还评估了ADW的性能，并提出了一些复杂的查询，以提取和返回有关作物管理的必要知识。
In recent years, precision agriculture is becoming very popular. The introduction of modern information and communication technologies for collecting and processing Agricultural data revolutionise the agriculture practises. This has started a while ago (early 20th century) and it is driven by the low cost of collecting data about everything; from information on fields such as seed, soil, fertiliser, pest, to weather data, drones and satellites images. Specially, the agricultural data mining today is considered as Big Data application in terms of volume, variety, velocity and veracity. Hence it leads to challenges in processing vast amounts of complex and diverse information to extract useful knowledge for the farmer, agronomist, and other businesses. It is a key foundation to establishing a crop intelligence platform, which will enable efficient resource management and high quality agronomy decision making and recommendations. In this paper, we designed and implemented a continental level agricultural data warehouse (ADW). ADW is characterised by its (1) flexible schema; (2) data integration from real agricultural multi datasets; (3) data science and business intelligent support; (4) high performance; (5) high storage; (6) security; (7) governance and monitoring; (8) consistency, availability and partition tolerant; (9) cloud compatibility. We also evaluate the performance of ADW and present some complex queries to extract and return necessary knowledge about crop management.
