State of the art review of Big Data and web-based Decision Support Systems (DSS) for food safety risk assessment with respect to climate change

Technology is being developed to handle vast amounts of complex data from diverse sources. The terms Big Data and Decision Support Systems (DSS) refer to computerised multidimensional data management systems that support stakeholders in making use of modern data-driven approaches to identify and solve problems and to enable enhanced decision making. Big Data has become ubiquitous in food safety. Information in the food supply chain is scattered and involves heterogenicity in format, scale, geographical origin. Also, interactions among environmental factors, food contamination, and foodborne diseases are complex, dynamic, and challenging to predict. Therefore, this state-of-the-art review article focuses on the underlying architecture of Big Data and web-based technologies for food safety, focusing on climate change influences. Challenges in adopting Big Data in food safety are presented, and future research directions regarding technologies/methods in the food supply chain are summarised and analysed. The analysis and discussion provided aim to assist agri-food researchers and stakeholders in taking initiatives and gathering insights on the application of Big Data and web-based DSS for food safety, which would alleviate challenges and facilitate the implementation of Big Data in food safety risk assessment while considering the possible implications of climate change.

Automated summary

This article presents the application of Big Data and web-based Decision Support Systems (DSS) in the field of food safety. It provides an overview of the challenges in using Big Data technology to address food safety issues and suggests future research directions.