Establishment of a prototypic Quantitative Microbial Risk Assessment (QMRA) food and feed safety model repository. Issue 9 (13th September 2019)

• Record Type: Journal Article
• Authors: Lopez de Abechuco, Estibaliz; Mesa Varona, Octavio; Valentin, Lars; de Alba Aparicio, Miguel; Schüler, Thomas; Günter, Taras; Swaid, Ahmad; Buschhardt, Tasja; Filter, Matthias
• Is Part Of: EFSA supporting publications. Volume 16:Issue 9(2019)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2019-09-13
• Subjects: Food -- Europe -- Safety measures -- Periodicals; Food -- Safety measures; Europe; Periodicals; Periodicals; 363.192094
• DOI: 10.2903/sp.efsa.2019.EN-1701
• Languages: English
• ISSNs: 2397-8325

Abstract

Abstract : The transfer and re‐use of existing food safety knowledge (ranging from experimental data, published mathematical models to risk assessment software code) is currently a major bottleneck in the area of food safety risk assessment. Such knowledge transfer and knowledge re‐use would be possible if curated, community‐driven risk assessment knowledge repositories would exist, that provide mathematical models/modules in a machine‐readable format. This project therefore aims at the development of necessary resources (standards, ontology‐based controlled vocabularies, software tools and services) facilitating the establishment of open, community‐driven, curated knowledge repositories for scientists and risk assessors. The main goal of this project is the provisioning of a proof‐of‐principle implementation of a food and feed safety model repository on the following basis: Development of a generic model exchange format (FSK‐ML) to encode food and feed safety models, data and simulation scenarios. Development of open technical resources (converter, software libraries, data processing workflows) as well as domain‐specific ontologies facilitating the broad adoption of FSK‐ML in the area of Quantitative Microbial Risk Assessment (QMRA) Development and extension of software tools for de‐novo generation, export, import, validation and execution of FSK‐ML files. Establishment of a prototypic web‐based knowledge repository for QMRA with seamless interoperation with EFSA's Knowledge Junction (KJ), which allows access to the collected resources as well as the provision of digital object identifiers (DOI).