The EATS Project

Over the last few decades rapid advances in processes to collect, monitor, disclose, and disseminate information have contributed towards the development of entirely new modes of environmental monitoring and governance for supply chains.

Unfortunately, existing approaches often suffer from limitations in terms of collection and dissemination of data; over-simplification of supply chains; power dynamics influencing information inclusion/exclusion decisions; and potentially perverse outcomes regarding how the information is used, by whom and to what effect.

The EATS project will explore novel approaches for transparent sustainibility through the following questions:

What datasets, indicators and decision-making processes are relevant to the different actors participating in supply chains to realize sustainable food futures?

How do we formulate appropriate vocabularies with which to characterise sustainability practices, their context and rationale, and facilitate data capture and integration?

Can we realize a provenance-based sustainability solution for supply chains, operating across a range of technologies and organisational boundaries, that is trusted and able to facilitate pro-environmental decision-making and action?

How do we exploit sustainability data assets and technologies such as machine learning (ML) and AI to inform decision making towards net-zero, resulting in demonstrable changes to practice and behaviour?


Evaluate the role of sensors and carbon reporting tools in capturing data about agri-food processes.


Design a trusted digital platform able to manage structured sustainability data and report it across supply chain actors.


Employ the use of data-analytics and machine learning to support decision-making and action.

Our Team

Our Use Cases

Soft Fruit

Our Project partners & Funding

EATS is supported by the awards made by the RCUK Digital Economy programme; award references: EP/V042270/1; EP/V041657/1; EP/V041487/1; and EP/V041371/1