TY - JOUR
T1 - How might technology rise to the challenge of data sharing in agri-food?
AU - Durrant, Aiden Mark
AU - Markovic, Milan
AU - Matthews, David
AU - May, David
AU - Leontidis, Georgios
AU - Enright, Jessica
N1 - Acknowledgement
This work was supported by an award made by the UKRI/EPSRC funded Internet of Food Things Network+ grant EP/R045127/1. We would also like to thank Mr Steve Brewer and Professor Simon Pearson for supporting the work presented in this paper.
PY - 2021/3/1
Y1 - 2021/3/1
N2 - 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.
AB - 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.
KW - Data Trusts
KW - Data Sharing
KW - AI technologies
KW - Agri-food supply chains
KW - Machine Learning
UR - https://authors.elsevier.com/a/1cQKt7sxZ%7E8CDV
U2 - 10.1016/j.gfs.2021.100493
DO - 10.1016/j.gfs.2021.100493
M3 - Article
VL - 28
JO - Global Food Security
JF - Global Food Security
SN - 2211-9124
M1 - 100493
ER -