YuHang Xian, Xingyu Zhao

(School of Finance, Nanjing Audit University)

Abstract：

In response to the problems of large data volume, diverse data types, and high barriers to knowledge mining and visualization analysis technology in the field of forestry and grassland, combined with the current situation of scientific research data in the forestry and grassland industry, a forestry and grassland scientific research big data platform was constructed based on computer application technology, realizing the aggregation of forestry and grassland scientific research data resources and knowledge discovery. The platform adopts a design pattern that includes four layers of overall architecture: infrastructure layer, data resource layer, data analysis layer, and data service layer. It uses Java language and is based on the Spring MVC framework and ECharts visualization tool. The system implements functions such as deep search of forest and grass knowledge, big data analysis, knowledge graph, and visualization display. It also integrates security authentication shiro, log management log4j, and caching Redis components based on the Spring framework. This article first outlines the connotation and research status of big data in forestry and grassland scientific research; Then, the data resource construction process of the forestry and grassland research big data platform was elaborated from the perspectives of data types, data processing and integration, data analysis and interpretation; Detailed introduction of the technical implementation framework and four typical characteristic functional applications of the forestry and grassland research big data platform; Finally, the achievements of the forestry and grassland research big data platform were summarized and prospects were made. Research has shown that building a big data platform for forestry and grassland scientific research, aggregating and sharing forestry and grassland data resources, providing precise knowledge-based services, effectively promoting the efficient management and utilization of forestry and grassland scientific research data, as well as the deep mining of scientific research knowledge, is of great significance for accelerating forestry and grassland scientific and technological innovation.

Key Words：

forest and grass; research big data; knowledge services; application