STELAR, the 3-year Horizon Europe project developing a data management system fit for today’s agrifood needs, is entering a new and exciting stage of the project lifetime cycle. After a first year filled with fruitful collaboration and efforts from the project’s consortium to set the stage for the Pilots, STELAR is ready to kick off Piloting activities revolving around topics of risk prevention in food supply lines, early crop growth predictions, and timely precision farming interventions.
Piloting Activities Underway
There are three business cases from the domain of smart agriculture, whose data value chains will be improved by the STELAR KLMS through different real-world use cases. The STELAR project has defined the three Piloting scenarios related to data-driven methods for food safety in supply lines, early crop growth predictions based on Earth Observation data, and data-driven decision-making in precision farming solutions. Overall, these consist of activities grouped into 11 use cases.
There are three business cases from the domain of smart agriculture, whose data value chains will be improved by the STELAR KLMS through different real-world use cases. The STELAR project has defined the three Piloting scenarios related to data-driven methods for food safety in supply lines, early crop growth predictions based on Earth Observation data, and data-driven decision-making in precision farming solutions. Overall, these consist of activities grouped into 11 use cases.
Three Pilots from STELAR
In the previous period, STELAR’s consortium members elaborated in detail on the technical development of concrete use cases across different business applications, including workflow diagrams to be implemented in the upcoming two years. We are now ready to take the first implementation steps! Third-party users will be involved in all three Piloting scenarios, making the integration of the KLMS into the users’ everyday business activities a more seamless endeavour. The use cases will be closely monitored in order to be evaluated in a timely manner and refined for the next stage of the project. The evaluation will serve not just the specific use cases, but the KLMS as a whole.
For the seamless development of the use cases, STELAR is taking a user-centered approach focusing, among others, on customer satisfaction, software quality, and environmental impact.
Turning Raw Data Lakes Into Knowledge Lakes
STELAR aims to design, develop and evaluate a Knowledge Lake Management System (KLMS) to empower users with data that’s easy to find, access, and reuse, as well as data that is interoperable, high quality, and reliably labelled.
Dr Dimitris Skoutas, STELAR’s Project Coordinator and Principal Researcher at Athena Research Center highlighted the importance of “tidying up” the data space in a manner that serves many players on the food value chain – companies (mainly small- and medium-sized enterprises), domain experts, data marketplaces, and exchange platforms.
“Today’s agrifood data space consists of large volumes of data. But, data is only as worthwhile as the ease with which it can be used. Users in the agricultural sector are facing difficulties in meeting their needs due to data stored in different places and forms, as well as subpar dataset search capabilities underusing the revolutionising potential of AI and machine learning. STELAR is thus developing a system consisting of a platform and set of tools which turn raw data lakes into knowledge lakes.”
Dr Dimitris Skoutas