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Ontologies define the main concepts and relations of a domain and can play the role of common language between domain experts, software developers and computer systems, allowing for easier and more comprehensive data management. Ontologies can provide a structure and context for data, enabling better analysis and decision‐making. Ontologies can be leveraged for improving various Machine Learning‐based tasks (they can be used for improving the accuracy and consistency of training data, and we can combine ML‐based predictions with ontology‐based reasoning). Ontologies are key components for achieving semantic data integration. In the context of this deliverable, we have surveyed 40 ontologies and 7 other knowledge organization systems related to food safety and we have categorized them according to a set of appropriate criteria. Subsequently we analysed the 18 case studies, that could involve ontologies, and for each one we have described the possible use of ontologies and what would be the benefit. Finally the identified case studies have been evaluated with respect to a set of criteria regarding benefits, cost and maturity. This publication is linked to the following EFSA Supporting Publications articles: http://onlinelibrary.wiley.com/doi/10.2903/sp.efsa.2024.EN-9118/full, http://onlinelibrary.wiley.com/doi/10.2903/sp.efsa.2024.EN-9119/full This publication is linked to the following EFSA Journal article: http://onlinelibrary.wiley.com/doi/10.2903/j.efsa.2024.e221201/full [ABSTRACT FROM AUTHOR]

This report proposes a governance model for managing the activities involving ontologies at EFSA. It contains recommendations about (a) the scoping of the ontology development activities at EFSA (purpose and subject matter), (b) external and internal consistency and interoperability, (c) maintenance and evolution, (d) access policies, (e) IT considerations (aligned with Deliverable D4), (f) outsourcing strategy, (g) training needs related to ontologies. The proposed model is aligned with the existing governance activities of EFSA, such as Rebuild DF. The document is complemented with the adopted governance model of other ontologies. This publication is linked to the following EFSA Supporting Publications articles: http://onlinelibrary.wiley.com/doi/10.2903/sp.efsa.2024.EN-9118/full, http://onlinelibrary.wiley.com/doi/10.2903/sp.efsa.2024.EN-9120/full This publication is linked to the following EFSA Journal article: http://onlinelibrary.wiley.com/doi/10.2903/j.efsa.2024.e221201/full [ABSTRACT FROM AUTHOR]

This document describes the steps that required for creating and maintaining an ontology; for exploiting an ontology in order to describe data from one or more data sources; and for developing services and applications that provide unified access and insightful analysis on the data. The document provides the state of the art of the various tools and software components that exist and can be used for carrying out various tasks of the overall process. The components are grouped based on their intended use and for each one of them a concise description, as well as other useful details (i.e. if they are open‐source, their license, etc.), are provided. For each step or task, the involved software components are also described in a table presenting their details with respect to various dimensions (e.g. open‐source, license, available online, key advantages, etc.), in order to enable their quick comparison. Moreover, successful examples of semantic data integration are presented, i.e., for cases where a top‐level ontology is used for integrating data for the cultural and biodiversity domain, and services for large‐scale semantic data integration (including hundreds of datasets from several domains). Furthermore, it provides the high‐level architectural suggestions that can be used as a basis for the actual implementation of any ontology‐based system; the described processes and tools can be exploited for the development of the ontology‐based functionality. Finally, it offers the adaptations of the proposed architecture for the EFSA case studies, by providing details about their components and indicative pipelines and tools. This publication is linked to the following EFSA Supporting Publications articles: http://onlinelibrary.wiley.com/doi/10.2903/sp.efsa.2024.EN-9119/full, http://onlinelibrary.wiley.com/doi/10.2903/sp.efsa.2024.EN-9120/full This publication is linked to the following EFSA Journal article: http://onlinelibrary.wiley.com/doi/10.2903/j.efsa.2024.e221201/full [ABSTRACT FROM AUTHOR]