π€ AI Summary
This study addresses the challenges of conceptual ambiguity and data integration in cross-sectoral crisis management by proposing ECMO, a modular OWL ontology. Covering core crisis concepts and aligned with the SNOMED CT public health module, ECMO pioneers the use of OWL 2 punning to resolve semantic ambiguities between hazard types and event manifestations. Furthermore, it integrates ontology design patterns with unstructured text-to-knowledge graph conversion methods to achieve unified knowledge representation. Ultimately, this work successfully constructs an end-to-end epidemiological knowledge graph compliant with the ECMO standard and validates its consistency, providing a scalable knowledge infrastructure for cross-domain crisis response.
π Abstract
This paper presents the European Crisis Management Ontology (ECMO), a modular OWL-based ontology intended as a cross-sectoral reference for disaster risk reduction and response. ECMO is designed to be organised as a network of ontological modules. Among the modules, ECMO-CORE captures fundamental crisis management concepts such as hazard, event, exposure, impact, and response measure and uses ontology design patterns and the OWL2 punning technique to resolve ambiguities between hazard types and event manifestations. In addition, domain-specific modules are defined as in the case of the public health module aligned with SNOMED CT and ICD-11. To demonstrate the resource's utility, we used ECMO to represent the data of the Epidemic Intelligence from Open Sources system of the Joint Research Centre to generate an end-to-end pipeline that populates an ECMO-compliant knowledge graph from unstructured epidemiological news. Initial results demonstrate that ECMO provides the formal guardrails necessary for consistent and unified knowledge representation and integration. The ontology is publicly available at https://doi.org/10.5281/zenodo.20070268 and is released under the Creative Commons Attribution 4.0 International (CC BY 4.0) license.