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SSD2 and FoodEx2 compliant real‐time registration and classification of food sampling data ‐ Improving Data Quality for Risk Assessment (IDRisk)

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Disclaimer: 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). The present document is published complying with the transparency principle to which the Authority is subject. It cannot be considered as an output adopted by the Authority. The European Food Safety Authority reserves its rights, view and position as regards the issues addressed and the conclusions reached in the present document, without prejudice to the rights of the authors.

Abstract

The present report describes the work done under the IDRisk project (Improving Data quality for RISK assessment), within the grant agreement GP/EFSA/ENCO/2018/03, from the sign in on 12/12/2018. The main goal of this project was to improve quality of raw occurrence data for risk assessment by reducing error, incrementing completeness and timeliness both in data fields and food classification, and simultaneously reducing the workload and time‐consuming manual tasks and therefore allowing scientists more time for data analysis and for performing risk assessment. The improvements are reflected on the strengthening of food safety risk assessment capacity of the countries involved and contributing to a better evaluation on risks associated with the food chain by EFSA. The objectives proposed and results achieved by this project presents a solution to improve data collection, management and interoperability, facilitating data exchange, with robust methodologies and tools, allowing the competent authorities to substantially enhance their own National Data Management Systems (NDMS). The proposed solution consists of the implementation of a system capable of real‐time sample data collection, based on preparatory digital forms, as well as an automatic approach to FoodEx2 classification of food samples using the existing knowledge and NDMS's databases. The aim of such system is to automate the whole execution of the official control plans and data transmission to EFSA, while mitigating the errors that normally accumulate throughout the process as a result of data manually handled by several people and of the consequent amount of inaccurate information that is produced. It was expected that the proposed solution could increase the data quality, through robust sample collection that could be monitored online and in real time, reducing the risk of misidentification/management. This document also describes the challenges encountered during the implementation of the project, and provides a general analysis on its limitations and potential future developments.