Product Update: Roadmap 2020

This roadmap reflects two priorities for Agrimetrics. The first is our overriding objective to become a ‘one-stop-marketplace’ for food and farming data. This means meeting the requirements not just of agribusiness, but also Finance, Retailers, Logistics, and others. It means providing features for data providers, as well as data consumers. It also means pre-linking this data: creating data supply chains that run alongside real-world systems.

During 2020, we aim to facilitate a growth in the use of predictive analytics, enabled by pre-processed linked data. In the first instance, this will be through support of specific use cases, such as the predictive harvest model developed alongside Barfoots.

Secondly, this roadmap reflects our emphasis on sustainability. This is driven by an emerging commercial need. The move to ELMs, the focus on carbon farming and natural capital, changing consumer habits, and the shift towards ethical investing mean commercial-success and corporate-responsibility are increasingly tied. However, it is also a moral decision; all organisations have a responsibility to do what they can to preserve Earth’s life support systems.

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Spring 2020

During Spring 2020, we will release in-season predictions of the crops growing in each of the UK’s 2.8 million fields. Our ambition is to make a more accurate prediction of what crops are growing where, and to do this earlier in the season than has been previously possible. This information is critical for the functioning of a range of crop management models, from disease and Lodging predictions to managing fertilizer applications and irrigation. The data is also in high demand from the commodities and finance sector.

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Central to our ability to make early and accurate in-season crop identifications is Synthetic Aperture Radar (SAR). This data, from the Sentinel I Satellite, will also be available through our Data Marketplace. Critically, our processing pipeline will halve the amount of data preparation required before the ‘real work’ can begin.

We will also make our first public foray into linked-livestock data. The creation of a Livestock Knowledge Graph has been accelerated by our participating in the EU-funded SmartCow project, where our work has enabled 15 partners to quickly query, share and analyse each other’s data.

Finally, we will improve navigation through our linked data. For example, users will be able to search our entire catalogue by concept, e.g. natural capital. It will also improve exploration of the links between data; we will move closer to the reality of a self-serving AI. This builds on our learnings from the launch of our Query Builder, which uses GraphQL.

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Summer 2020

During Summer 2020, we will significantly increase the amount of natural capital data available through our Data Marketplace; the initial focus will be on carbon and biodiversity data. Critically, this data will be linked: radically reducing the costs of operating in this space for public and private sector actors.

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For the first time, farmer sentiment data will be made widely available. Organisations will be able to quickly understand farmers’ perspective on policy, issues and new machinery. We will also release Knowledge Graphs for sustainability, farm business and supply chains; this will bring us much closer to running seamless data chains alongside physical agri-food supply chains.

A key part of the Data Marketplace is the ability of data owners to market their data. This functionality is available today, however, the summer will see these processes significantly improved, including the ability to self-serve.

Autumn 2020

“Plug and play sustainability accounting” is our key objective for autumn of 2020. The vast amounts of linked data, organised via knowledge graphs, will provide a platform for organisations looking to improve the tracking and auditing of sustainability information. The initial focus will be on carbon accounting. Additional land data will also be incorporated, e.g. hedgerows and habitats.

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Digital twins will make their first appearance. This service will drastically simplify the process of analysing real-world entities, including fields, animals, supply chains and produce. In other sectors, Smart Manufacturers have begun to utilise digital twins of production lines, or even entire factories; predictive maintenance is just one of the things this has enabled, which has pushed down maintenance costs by 40%.

Finally, we will introduce a self-service mechanism for data linking. Data Providers will be able to upload their data to our Data Marketplace and, aided by AI, will be able to quickly link their data to a vast array of relevant information. Considering the huge costs and technical limitations surround enterprise-level data integrations, we think this technology could be game changing for the sector.

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About Agrimetrics

Agrimetrics is the food and farming sector’s Data Marketplace. We enable organisations to safely share and monetise their data, whilst making it easier for data-consumers to access the information they need. Our goal is to help create a more productive and sustainable food system by enabling next-generation solutions as quickly and affordably as possible.

We are one of four centres for agricultural innovation founded with an initial investment from Innovate UK. Our founding partners are NIAB, SRUC, Rothamsted Research and The University of Reading. We have strategic partnerships with Airbus and Microsoft and are a participant in Microsoft’s prestigious AI for Earth programme.

About the four centres
The Agri-Tech Centres are a unique collaboration between Government, academia and industry created to drive greater efficiency, resilience and wealth across the agrifood sector. A £90m investment from the UK’s strategic innovation agency (Innovate UK) is enabling the Centres to harness leading UK research and expertise as well as build new infrastructures and innovation. They include CHAP (Crop Health and Protection), CIEL (Centre for Innovation Excellence in Livestock), Agri-EPI (Engineering and Precision Technologies), and Agrimetrics.

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