Forschungsdatenbank

This UC Project addresses two objectives: First: provide and disseminate a FAIR-annotated image dataset on potato viruses to the community with the goal of enabling publicly usable insights (e.g. using AI). Second: Create seamless interoperability between the Agri-Gaia AI-development platform (Agri-Gaia) with the ARC DataHUB (DataHUB) a FAIR research data management and publication platform. 

The idea of creating, disseminating and analyzing a potato virus data set was brought to RPTU and HSOS by the GFPi and EuroPlant. The dataset will be used to showcase semantical and technical interoperability. This integration will facilitate seamless interaction and model training on data encapsulated as ARCs, while also providing a FAIR description of the AI workflow via the ARC RO-Crate workflow profile. 

Agri-Gaia supports the whole AI-lifecycle. Platforms may be used at user’s premise or by using a managed cloud-installation. Using the Eclipse Dataspace Components, platforms can be combined into one data space or connected to other data spaces. Each platform instance provides an OpenAPI-based connector to connect external software services or integrate public base data. The results are integrated into the Agri-Gaia data management system. 
ARC DataHUB enables users to progressively transform their data into FAIR digital objects and publish them in line with the evolving FAIR-by-design principle. Acting as a technological middleware, the DataHUB integrates large datasets from diverse providers within the FAIRagro consortium and offers a suite of user-friendly tools for ARC-based research data management and evolution. Additionally, it establishes connections with other consortia such as DataPLANT, Microbiota, and Biodiversity.