English

A Knowledge Graph Informing Soil Carbon Modeling

Computers and Society 2025-08-18 v1 Symbolic Computation

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.

Keywords

Cite

@article{arxiv.2508.10965,
  title  = {A Knowledge Graph Informing Soil Carbon Modeling},
  author = {Nasim Shirvani-Mahdavi and Devin Wingfield and Juan Guajardo Gutierrez and Mai Tran and Zhengyuan Zhu and Zeyu Zhang and Haiqi Zhang and Abhishek Divakar Goudar and Chengkai Li and Virginia Jin and Timothy Propst and Dan Roberts and Catherine Stewart and Jianzhong Su and Jennifer Woodward-Greene},
  journal= {arXiv preprint arXiv:2508.10965},
  year   = {2025}
}
R2 v1 2026-07-01T04:50:33.590Z