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.
Translated title of the contributionONTOLOGICAL APPROACH APPLICATION TO THE DESIGN OF A GEOSPATIAL EXPERIMENTAL DATABASE FOR INFORMATION SUPPORT OF RESEARCH IN PRECISION AGRICULTURE
Original languageRussian
Pages (from-to)253-262
Number of pages10
Journal ВЕСТНИК САНКТ-ПЕТЕРБУРГСКОГО УНИВЕРСИТЕТА. ПРИКЛАДНАЯ МАТЕМАТИКА. ИНФОРМАТИКА. ПРОЦЕССЫ УПРАВЛЕНИЯ
Volume18
Issue number2
DOIs
StatePublished - 15 Mar 2022

    Scopus subject areas

  • Computer Science(all)
  • Control and Optimization
  • Applied Mathematics

ID: 98301630