A Knowledge Graph Informing Soil Carbon Modeling

TL;DR

This paper presents SOCKG, a semantic knowledge graph that integrates heterogeneous soil carbon data to enhance research, analysis, and decision-making in climate and agriculture.

Contribution

The paper introduces SOCKG, a novel semantic infrastructure that models and links soil carbon data for improved interoperability and advanced querying capabilities.

Findings

SOCKG enables complex queries across diverse datasets.

The knowledge graph improves understanding of soil carbon dynamics.

SOCKG supports climate change mitigation strategies.

Abstract

Soil organic carbon is crucial for climate change mitigation and agricultural sustainability. However, understanding its dynamics requires integrating complex, heterogeneous data from multiple sources. This paper introduces the Soil Organic Carbon Knowledge Graph (SOCKG), a semantic infrastructure designed to transform agricultural research data into a queryable knowledge representation. SOCKG features a robust ontological model of agricultural experimental data, enabling precise mapping of datasets from the Agricultural Collaborative Research Outcomes System. It is semantically aligned with the National Agricultural Library Thesaurus for consistent terminology and improved interoperability. The knowledge graph, constructed in GraphDB and Neo4j, provides advanced querying capabilities and RDF access. A user-friendly dashboard allows easy exploration of the knowledge graph and ontology. SOCKG supports advanced analyses, such as comparing soil organic carbon changes across fields and treatments, advancing soil carbon research, and enabling more effective agricultural strategies to mitigate climate change.