O. Mitrofanova, Eugenii P. Mitrofanov, Nataliya A. Bure
{"title":"ONTOLOGICAL APPROACH APPLICATION TO THE DESIGN OF A GEOSPATIAL EXPERIMENTAL DATABASE FOR INFORMATION SUPPORT OF RESEARCH IN PRECISION AGRICULTURE","authors":"O. Mitrofanova, Eugenii P. Mitrofanov, Nataliya A. Bure","doi":"10.21638/11701/spbu10.2022.206","DOIUrl":null,"url":null,"abstract":"Thanks to the development of information technologies and computing resources, it became possible to obtain and process big data, including geospatial data. Most research in the field of precision farming is interdisciplinary in nature, with experimental field data used by disparate scientific groups. In this connection, it became necessary to develop a unified web-based system for storing, organizing, and exchanging experimental information between researchers. The first step in achieving this goal was to create a geospatial database. Since the system being developed in the future may require extensions, modifications, adjustments, integration into other projects, it seems appropriate to use the ontology to form the database structure. The most popular tools were used as the main tools: the ontology language OWL (Ontology Web Language), the Protege 5.5 development environment. The main initial information obtained in the course of experimental studies carried out at the biopolygon: weather data, agrochemical indicators (sampling of soil and plants with georeferencing), agrophysical parameters (humidity, electrical conductivity), remote sensing data. Based on the results of the analysis of the current state of research in the field of storage and systematization of experimental information in crop production, as well as a survey of ARI employees, a prototype of the database structure was formed based on the ontological approach. Nine parent classes were defined as the foundation: Field, Crop rotation - experience, Agrotechnology, Yield, Meteo, Ground samples, Orthophoto, Calendar, and Dictionary - units of measurement.","PeriodicalId":43738,"journal":{"name":"Vestnik Sankt-Peterburgskogo Universiteta Seriya 10 Prikladnaya Matematika Informatika Protsessy Upravleniya","volume":"7 1","pages":""},"PeriodicalIF":0.3000,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Vestnik Sankt-Peterburgskogo Universiteta Seriya 10 Prikladnaya Matematika Informatika Protsessy Upravleniya","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.21638/11701/spbu10.2022.206","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"MATHEMATICS, INTERDISCIPLINARY APPLICATIONS","Score":null,"Total":0}
引用次数: 0
Abstract
Thanks to the development of information technologies and computing resources, it became possible to obtain and process big data, including geospatial data. Most research in the field of precision farming is interdisciplinary in nature, with experimental field data used by disparate scientific groups. In this connection, it became necessary to develop a unified web-based system for storing, organizing, and exchanging experimental information between researchers. The first step in achieving this goal was to create a geospatial database. Since the system being developed in the future may require extensions, modifications, adjustments, integration into other projects, it seems appropriate to use the ontology to form the database structure. The most popular tools were used as the main tools: the ontology language OWL (Ontology Web Language), the Protege 5.5 development environment. The main initial information obtained in the course of experimental studies carried out at the biopolygon: weather data, agrochemical indicators (sampling of soil and plants with georeferencing), agrophysical parameters (humidity, electrical conductivity), remote sensing data. Based on the results of the analysis of the current state of research in the field of storage and systematization of experimental information in crop production, as well as a survey of ARI employees, a prototype of the database structure was formed based on the ontological approach. Nine parent classes were defined as the foundation: Field, Crop rotation - experience, Agrotechnology, Yield, Meteo, Ground samples, Orthophoto, Calendar, and Dictionary - units of measurement.
由于信息技术和计算资源的发展,获取和处理包括地理空间数据在内的大数据成为可能。精准农业领域的大多数研究本质上是跨学科的,不同的科学团体使用了实验现场的数据。在这方面,有必要开发一个统一的基于web的系统来存储、组织和交换研究人员之间的实验信息。实现这一目标的第一步是创建地理空间数据库。由于将来开发的系统可能需要扩展、修改、调整、集成到其他项目中,因此使用本体来形成数据库结构似乎是合适的。使用最流行的工具作为主要工具:本体语言OWL (ontology Web language)、Protege 5.5开发环境。在生物多边形进行的实验研究过程中获得的主要初步信息:天气数据、农业化学指标(土壤和植物的地理参照取样)、农业物理参数(湿度、电导率)、遥感数据。在分析作物生产实验信息存储与系统化研究现状的基础上,通过对ARI员工的调查,建立了基于本体论方法的数据库结构原型。9个父类被定义为基础:田地,作物轮作-经验,农业技术,产量,气象,地面样本,正射影像,日历和字典-测量单位。
期刊介绍:
The journal is the prime outlet for the findings of scientists from the Faculty of applied mathematics and control processes of St. Petersburg State University. It publishes original contributions in all areas of applied mathematics, computer science and control. Vestnik St. Petersburg University: Applied Mathematics. Computer Science. Control Processes features articles that cover the major areas of applied mathematics, computer science and control.