SPATIO-TEMPORAL DATA HARMALIZATION USING KNOWLEDGE GRAPH FOR SOIL HEALTH MANAGEMENT

Spatio-temporal data harmonization is crucial for effectively managing soil health in sustainable agriculture. In the case of Indian soil, known for its diversity and complexity, integrating and analyzing different soil data sources presents significant challenges. This research proposes a novel approach that utilizes knowledge graphs to address these challenges in soil health management. This paper presents a knowledge graph that captures domain-specific information about Indian soil, such as soil properties, climatic conditions, land use patterns, and agricultural practices. This knowledge graph serves as a unified framework for integrating diverse data sources, such as soil survey lab reports, sensor data, and agricultural databases. An architecture for spatiotemporal data harmonization is presented in this paper, which includes data acquisition, pre-processing, knowledge graph construction, embedding techniques, alignment, harmonization, and integration. In the context of soil health management, it facilitates the integration and analysis of diverse soil data sources.