EFRA - Food Safety Hazards Thesaurus

Hazard annotations have complex semantics: often a general food safety hazard is coupled with a specific substance, chemical compound, etc. (e.g., too much nitrogen, lack of nitrogen, little nitrogen, presence of nitrogen, etc.). For these concepts, we modeled the general class of hazard in the EFRA Food Safety Hazard Thesaurus and let the identification of the involved substance by means of external ontologies. Some hazards do not mention external concepts or entities (e.g. unauthorized import, incorrect pasteurization process, incorrect product labeling). The EFRA Food Safety Hazards Thesaurus has been formalized using a SKOS model and is expressed in Terse RDF Triple Language (Turtle).

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Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2025-10-18
DOI
https://doi.org/10.5281/zenodo.18772547
Primary Topic
Biomedical Text Mining and Ontologies
Type
article
Field-Weighted Citation Impact
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article

EFRA - Food Safety Hazards Thesaurus

Ali Hürriyetoğlu, Alessio Bosca
Zenodo (CERN European Organization for Nuclear Research)
Biomedical Text Mining and Ontologies
article

EFRA - Food Safety Hazards Thesaurus

Ali Hürriyetoğlu, Alessio Bosca
article en

Abstract

Hazard annotations have complex semantics: often a general food safety hazard is coupled with a specific substance, chemical compound, etc. (e.g., too much nitrogen, lack of nitrogen, little nitrogen, presence of nitrogen, etc.). For these concepts, we modeled the general class of hazard in the EFRA Food Safety Hazard Thesaurus and let the identification of the involved substance by means of external ontologies. Some hazards do not mention external concepts or entities (e.g. unauthorized import, incorrect pasteurization process, incorrect product labeling). The EFRA Food Safety Hazards Thesaurus has been formalized using a SKOS model and is expressed in Terse RDF Triple Language (Turtle).

Zenodo (CERN European Organization for Nuclear Research)
Koç University (TR), Universitas Borneo Tarakan (ID), Wageningen University & Research (NL)
Zero hunger
Openalex Percentile: Top 33%
Biomedical Text Mining and Ontologies
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