Managing evidence in food safety and nutrition. (8th July 2019)

• Record Type: Journal Article
• Authors: Cavalli, Ermanno; Gilsenan, Mary; Van Doren, Jane; Grahek‐Ogden, Danica; Richardson, Jane; Abbinante, Fabrizio; Cascio, Claudia; Devalier, Paul; Brun, Nikolai; Linkov, Igor; Marchal, Kathleen; Meek, Bette; Pagliari, Claudia; Pasquetto, Irene; Pirolli, Peter; Sloman, Steven; Tossounidis, Lazaros; Waigmann, Elisabeth; Schünemann, Holger; Verhagen, Hans
• Is Part Of: EFSA journal. Volume 17(2019)Supplement 1
• Page Start: n/a
• Page End: n/a
• Publication Date: 2019-07-08
• Subjects: data -- evidence integration -- evidence management -- food safety; Food -- Europe -- Safety measures -- Periodicals; Food Safety; Food -- Safety measures; Europe; Periodicals; Periodicals; Fulltext; Government Publications, International; Internet Resources; Periodicals; Periodicals; 363.19209405
• DOI: 10.2903/j.efsa.2019.e170704
• Languages: English
• ISSNs: 1831-4732

Abstract

Abstract: Evidence ('data') is at the heart of EFSA's 2020 Strategy and is addressed in three of its operational objectives: (1) adopt an open data approach, (2) improve data interoperability to facilitate data exchange, and (3) migrate towards structured scientific data. As the generation and availability of data have increased exponentially in the last decade, potentially providing a much larger evidence base for risk assessments, it is envisaged that the acquisition and management of evidence to support future food safety risk assessments will be a dominant feature of EFSA's future strategy. During the breakout session on 'Managing evidence' of EFSA's third Scientific Conference 'Science, Food, Society', current challenges and future developments were discussed in evidence management applied to food safety risk assessment, accounting for the increased volume of evidence available as well as the increased IT capabilities to access and analyse it. This paper reports on presentations given and discussions held during the session, which were centred around the following three main topics: (1) (big) data availability and (big) data connection, (2) problem formulation and (3) evidence integration.