The Climate Change Knowledge Graph: Supporting Climate Services

2026-02-23

AI Summary

This study addresses the limitations of traditional climate data retrieval systems, which rely on fragmented interfaces and metadata and struggle to support complex queries across multi-source simulation data for effective decision-making. For the first time, this work systematically introduces knowledge graph technology into climate services by developing a semantic knowledge graph grounded in an expert-informed ontology. The resulting framework integrates heterogeneous climate simulation datasets and enables joint semantic querying over models, variables, and spatiotemporal extents. Through comprehensive knowledge graph construction, ontology modeling, semantic integration, and an open API, the project achieves cross-dataset and cross-scenario semantic interoperability and intelligent data exploration. The authors publicly release the knowledge graph and ontology framework, significantly enhancing the efficiency of climate data discovery and its utility for informed decision support.

Technology Category

• Data Mining & Knowledge Management: Linked Open Data, Knowledge Graphs & KB Completion
• Knowledge Representation and Reasoning: Ontologies
• Machine Learning: Graph-based Machine Learning

Application Category

• Semantics and Knowledge: Scalable techniques for the creation, curation, publication, maintenance, and consumption of large, Web-based, structured, reusable, knowledge graphs and ontologies
• Graph Algorithms and Modeling for the Web: Querying, indexing, and retrieval in Web-related graphs
• Search and Retrieval-Augmented AI: Web query analysis, representation and understanding

Abstract

Climate change impacts a broad spectrum of human resources and activities, necessitating the use of climate models to project long-term effects and inform mitigation and adaptation strategies. These models generate multiple datasets by running simulations across various scenarios and configurations, thereby covering a range of potential future outcomes. Currently, researchers rely on traditional search interfaces and APIs to retrieve such datasets, often piecing together information from metadata and community vocabularies. The Climate Change Knowledge Graph is designed to address these challenges by integrating diverse data sources related to climate simulations into a coherent and interoperable knowledge graph. This innovative resource allows for executing complex queries involving climate models, simulations, variables, spatio-temporal domains, and granularities. Developed with input from domain experts, the knowledge graph and its underlying ontology are published with open access license and provide a comprehensive framework that enhances the exploration of climate data, facilitating more informed decision-making in addressing climate change issues.

Problem

• climate change
• climate models
• knowledge graph
• data integration
• climate services

Innovation

• Knowledge Graph
• Climate Modeling
• Ontology
• Interoperability
• Climate Data Integration