A Knowledge Graph Informing Soil Carbon Modeling

Authors: SHIRVANI-MAHDAVI, NASIM - University Of Texas At Arlington; WINGFIELD, DEVIN - University Of Texas At Arlington; GUTIERREZ, JUAN GUAJARDO - University Of Texas At Arlington; TRAN, MAI - University Of Texas At Arlington; ZHU, ZHENGYUAN - University Of Texas At Arlington; ZHANG, ZEYU - University Of Texas At Arlington; ZHANG, HAIQI - University Of Texas At Arlington; GOUDAR, ABHISHEK - University Of Texas At Arlington; LI, CHENGKAI - University Of Texas At Arlington; Jin, Virginia; PROPST, TIMOTHY - Oklahoma State University; Roberts, Daniel; Stewart, Catherine; SU, JIANZHONG - University Of Texas At Arlington; Woodward Greene, Mary

Submitted to: Proceedings
Publication Type: Proceedings
Publication Acceptance Date: 8/14/2025
Publication Date: 10/11/2025
Citation: Shirvani-Mahdavi, N., Wingfield, D., Gutierrez, J., Tran, M., Zhu, Z., Zhang, Z., Zhang, H., Goudar, A.D., Li, C., Jin, V.L., Propst, T., Roberts, D.P., Stewart, C.E., Su, J., Woodward Greene, M.J. 2025. A Knowledge Graph Informing Soil Carbon Modeling. Proceedings. 2026:226-241. https://doi.org/10.1007/978-3-031-97207-2.
DOI: https://doi.org/10.1007/978-3-031-97207-2

Interpretive Summary: Soil organic carbon is crucial for soil health and agricultural sustainability. To consolidate soil carbon data from multiple sources, the Soil Organic Carbon Knowledge Graph (SOCKG) was developed. SOCKG is designed to transform agricultural research data into a searchable relationships. SOCKG features agricultural experimental data, enabling precise mapping of datasets from the USDA-ARS's Agricultural Collaborative Research Outcomes System. Terminology is aligned with the National Agricultural Library Thesaurus. SOCKG has advanced querying capabilities and user-friendly dashboard to allow easy exploration of knowledge. SOCKG also allows advanced analyses, such as comparing soil organic carbon changes across fields and treatments, advancing soil carbon research, and informing more effective agricultural strategies.

Technical 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.