How might technology rise to the challenge of data sharing in agri-food?

Aiden Mark Durrant, Milan Markovic, David Matthews, David May, Georgios Leontidis*, Jessica Enright

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

Abstract

Data sharing is often hindered by a number of real word challenges caused by a mixture of technological and social factors. To date, the agri-food sector significantly lags behind other sectors in overcoming these challenges. However, the benefits of data sharing are too great to be ignored as they have a potential to address many historical failings such as issues related to food safety, traceability and transparency, and must be carefully considered as the sector is undergoing a widespread digitalisation. In this article, we explore the potential of different technologies in addressing the challenges presented by data sharing in the agri-food sector, and how the use of these technologies in the narrative of a Data Trust may address many of these obstacles. We argue the importance of utilising semantic web technologies, distributed ledger technologies, machine learning, and privacy preserving technologies to enable future transformative data sharing infrastructures in the agri-food sector. The utilisation of holistic statistical analysis of the shared data is also discussed, vital in supporting many of the sectors optimisation and sustainability goals.
Original languageEnglish
Article number100493
Number of pages8
JournalGlobal Food Security
Volume28
Early online date16 Jan 2021
DOIs
Publication statusPublished - 1 Mar 2021

Keywords

  • Data Trusts
  • Data Sharing
  • AI technologies
  • Agri-food supply chains
  • Machine Learning

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