Data ecosystem framework proposal to implement Food Informatics systems in agri-food chains

Abstract

Agri-food chains face permanent climate change, population growth, and water and input access challenges. These impact production, processing, and marketing processes, making the capture, processing, and analysis of the data generated by each link more complex, isolated, and independent. Extracting this information for intelligent analysis to allow the optimization of agri-food chains based on data analytics is called Food Informatics. The study paradigm has given rise to the concept of data ecosystems in agri-food chains. The aim of this study is to design a data ecosystem model for the implementation of Food Informatics systems in agri-food chains. The PRISMA methodology was implemented for the identification, screening, eligibility, and inclusion of studies from the Scopus and Clarivate databases. A total of 26 records were included in the in-depth analysis, identifying two data ecosystem types: those with integrated bidirectional views that facilitate link interoperability and others of an individual nature focused on one link. The proposed integrated data ecosystem model has as its core an ETL in GCP for Data Issued in Batches with a Data Catalog and Data Mesh-type structure, which integrates a physical and a digital layer and data infrastructure for storage, processing, visualization, curation, and interaction with the user.