Harmonized terms, concepts and metadata for microbiological risk assessment models: The basis for knowledge integration and exchange

Abstract

Harmonized terms, concepts and metadata for microbiological risk assessment models: the basis for knowledge integration and exchange, Microbial Risk Analysis (2018Analysis ( ), doi: 10.1016Analysis ( /j.mran.2018 This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain. Author names and affiliations Leticia Corresponding authorsLaurent Guillier; Maarten Nauta; Matthias Filter Short Title or Running HeadHarmonization for microbiological risk assessment modelling AbstractIn the last decades the microbial food safety community has developed a variety of valuable knowledge (e.g., mathematical models and data) and resources (e.g., databases and software tools)in the areas of quantitative microbial risk assessment (QMRA) and predictive microbiology.However, the reusability of this knowledge and the exchange of information between resources are currently difficult and time consuming. This problem has increased over time due to the lack of harmonized data format and rules for knowledge annotation. It includes the lack of a common understanding of basic terms and concepts and of a harmonized information exchange format to describe and annotate knowledge. The existence of ambiguities and inconsistencies in the use of terms and concepts in the QMRA and predictive microbial (PM) modelling necessitates a consensus on their refinement, which will allow a harmonized exchange of information within these areas.Therefore, this work aims to harmonize terms and concepts used in QMRA and PM modelling spanning from high level concepts as defined by Codex Alimentarius, Food and Agriculture Organization (FAO) and World Health Organization (WHO), up to terms generally used in statistics or data and software science. As a result, a harmonized schema for metadata that allows consistent annotation of data and models from these two domains is proposed. This metadata schema is also a . This platform will facilitate the sharing and execution of curated QMRA and PM models using the foundation of the proposed harmonized metadata schema and information exchange format. Furthermore, it will also provide access to related open source software libraries, converter tools and software-specific import and export functions that promote the adoption of FSK-ML by the microbial food safety community. In the future, these resources will hopefully promote both the knowledge reusability and the highquality information exchange between stakeholders within the areas of QMRA and PM modelling worldwide.

Establishment of a prototypic Quantitative Microbial Risk Assessment (QMRA) food and feed safety model repository

“…FSK-ML is an open XML-based data standard adaptable to different risk assessment domains in a transparent and reproducible way (Haberbeck et al, 2018). The original model metadata schema and the controlled vocabularies were proposed from the Risk Assessment Knowledge Integration Platform (RAKIP) community.…”

“…8. Other properties of the "Metadata Master Table" were described in detail in Haberbeck et al (2018). In this way the user does not have to choose the parameter unit category him/herself but it will be added automatically once the parameter unit is chosen.…”

“…The minimal set of model metadata was selected from the domain-specific community resource called FSK-ML "Metadata Master Schema" that has been developed and described by food safety risk assessment experts (Haberbeck et al, 2018 The present document has been produced and adopted by the bodies identified above as author(s). Firstly, the general guiding principles are postulated; these principles were adapted from best-practice minimum information guidelines previously established in other scientific disciplines.…”

“…Secondly, a minimal set of metadata and a specific guidance on technical requirements are provided to enable the fulfillment of the general guiding principles. The minimal set of model metadata was selected from the domain-specific community resource called FSK-ML "Metadata Master Schema" that has been developed and described by food safety risk assessment experts (Haberbeck et al, 2018 The present document has been produced and adopted by the bodies identified above as author(s). In accordance with Article 36 of Regulation (EC) No 178/2002, this task has been carried out exclusively by the author(s) in the context of a grant agreement between the European Food Safety Authority and the author(s).…”

Quantitative microbial risk assessment for Salmonella in eggs

“…This model is avalaible in Food Safety Knowledge Markup Language (FSK-ML) format to facilitate its reuse. This open information exchange format is based on harmonised terms, metadata and controlled vocabulary to harmonise annotations of risk assessment models (Haberbeck et al 2018). This format also contained model script, visualisation script and simulation settings (de Alba Aparicio et al 2018).…”