Supporting research and pandemic preparedness with an ontology for interoperable pathogen-resource catalogues

Pandemic preparedness requires pathogen resources and services to be discoverable and comparable across heterogeneous provider catalogues. The European Viral Outbreak Response Alliance Ontology (EVORAO) provides an open semantic model for describing shareable pathogen materials, derived products and associated services. EVORAO uses the Data Catalog Vocabulary (DCAT) as a structural backbone, implements selected constraints aligned with the DCAT Application Profile (DCAT-AP), and defines pathogen-resource concepts, properties and relationships covering identification, biological material origin, availability, request routes, biosafety, transport, licensing, provenance and contacts. Scientific experts curated the terms, definitions and structure used to generate EVORAO and the implementation artefacts that facilitate its adoption. Automated validation includes ontology reasoning, constraint validation and competency-query testing. EVORAO 1.2.0 declares 79 classes and 209 properties; its namespace contains 72 classes, 64 object properties and 129 data properties. EVORAO is released under Creative Commons Zero (CC0) 1.0 Universal. Its implementation in the EVORA Portal illustrates how EVORAO supports unified catalogue search and comparison of pathogen resources and services across providers, thereby supporting pandemic preparedness.

Authors

Institutions

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2026-10-06
DOI
https://doi.org/10.5281/zenodo.23182766
Primary Topic
Semantic Web and Ontologies
Type
preprint
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
preprint

Supporting research and pandemic preparedness with an ontology for interoperable pathogen-resource catalogues

Romain David, Helen E. Parkinson, Agathe M. G. Colmant, Philippe Lieutaud et al.
Zenodo (CERN European Organization for Nuclear Research)
Semantic Web and Ontologies
preprint

Supporting research and pandemic preparedness with an ontology for interoperable pathogen-resource catalogues

Romain David, Helen E. Parkinson, Agathe M. G. Colmant, Philippe Lieutaud, Jonathan J. Ewbank, Christine M. A. Prat, A Haas, James Alastair McLaughlin, Bruno Coutard, M. Bardsley
preprint en

Abstract

Pandemic preparedness requires pathogen resources and services to be discoverable and comparable across heterogeneous provider catalogues. The European Viral Outbreak Response Alliance Ontology (EVORAO) provides an open semantic model for describing shareable pathogen materials, derived products and associated services. EVORAO uses the Data Catalog Vocabulary (DCAT) as a structural backbone, implements selected constraints aligned with the DCAT Application Profile (DCAT-AP), and defines pathogen-resource concepts, properties and relationships covering identification, biological material origin, availability, request routes, biosafety, transport, licensing, provenance and contacts. Scientific experts curated the terms, definitions and structure used to generate EVORAO and the implementation artefacts that facilitate its adoption. Automated validation includes ontology reasoning, constraint validation and competency-query testing. EVORAO 1.2.0 declares 79 classes and 209 properties; its namespace contains 72 classes, 64 object properties and 129 data properties. EVORAO is released under Creative Commons Zero (CC0) 1.0 Universal. Its implementation in the EVORA Portal illustrates how EVORAO supports unified catalogue search and comparison of pathogen resources and services across providers, thereby supporting pandemic preparedness.

Zenodo (CERN European Organization for Nuclear Research)
European Bioinformatics Institute (GB), European Research Infrastructure on Highly Pathogenic Agents (FR), Association des Operateurs Postaux Publics Europeens (BE), European Molecular Biology Laboratory (DE), Leibniz Institute DSMZ – German Collection of Microorganisms and Cell Cultures (DE)
Semantic Web and Ontologies
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.