on 15 Jun 2018 12:00 AM
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On 14 June 2018 AGNFRA PLUS project published its first Journal article by the name “Harmonized terms, concepts and metadata for microbiological risk assessment models: the basis for knowledge integration and exchange”. The authors of the article are Leticia Ungaretti, Haberbecka Carolina, Plaza Rodríguezb, Virginie Desvignesc, Paw Dalgaarda, Moez Sanaac, Laurent Guillierc, Maarten Nautaa and Matthias Filter, the publication venue is the “9th International Workshop on Science Gateways (IWSG 2017), 19-21 June 2017”, the name of the Journal is Microbial Risk Analysis and the publisher is the ELSVIER.

This work aims to harmonize terms and concepts used in quantitative microbial risk assessment (QMRA) and predictive microbial (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 key component of the Food Safety Knowledge Markup Language (FSK-ML), a harmonized format for information exchange between resources in the QMRA and PM modelling domain. This work is carried out within a research project that aims to establish a new community resource called Risk Assessment Modelling and Knowledge Integration Platform (RAKIP). 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.

You can read the article here



The selected AGINFRA+ Use Cases will illustrate the benefits of applying the Science as a Service approach to pressing research questions from the corresponding research communities.


This community focuses on use cases aim to support the workflow of researchers, intermediaries and business analysts working on crop modelling, crop phenology estimation and yield forecasting, as well as related activities in the area of policy and decision support in food security, farm management advice and related activities.



This community focuses on use cases to support scientists in the multidisciplinary field of risk assessment and emerging risk identification as there is currently a strong need to create new technology-supported solutions that facilitate the knowledge integration processes relevant for these tasks.



This community focuses on use cases related to the high-throughput phenotyping large amount of data which need to be analyzed immediately for decision making. This aims to support phenomics researchers to select plant species and varieties which are the most adapted to specific environments and to global changes.


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