Description and objectives


The main goal of the AI4EOSC project is to foster an AI/ML/DL exchange in the EOSC context, enhancing the current EOSC service offer delivering added value, innovative and easily customizable services serving a broad range of scientific users. As such, we will focus on tools to provide Artificial Intelligence (AI), Machine Learning (ML) and Deep Learning (DL) services by integrating into the project real life use cases to co-design the project proposal and drive our integration activities.

This overarching goal will be set up by fulfilling the following project specific objectives:

  1. Provide machine learning practitioners with feature rich services to build and deploy customizable machine learning, deep learning and artificial intelligence applications following a platform and serverless approach with horizontal scalability over the EOSC continuum.
  2. Enhance existing cloud services to support machine learning and deep learning on distributed datasets, with a particular focus on federated learning.
  3. Deliver methods to build and compose machine learning and deep learning tools, making possible the development of more complex data-driven composite AI applications.
  4. Foster a machine learning and deep learning exchange in the context of the European Open Science Cloud, enhancing and increasing the application offer currently available in the DEEP Open Catalogue.
  5. Extend the service offer and the capabilities being offered through the EOSC portal, coordinating with the operational and management activities carried out by existing and future initiatives, creating and establishing cooperation synergies whenever possible.

The project

Artificial intelligence, deep learning and machine learning are at the forefront of scientific and industrial research. The impact of these techniques, together with the avalanche of large datasets in the big data era is transforming science and innovation, opening many new research areas. The high potential of these techniques in the next few years is clear, with large expectations to make it possible to tackle new scientific
problems. Machine and deep learning applications and services are more and more demanded by research and innovation stakeholders as pathways to effectively build and exploit tools based on these techniques.

The vision of the AI4EOSC project is to increase the service offer in the EU landscape by expanding the European Open Science Cloud (EOSC) ecosystem to support the effective utilization of state of the art AI techniques by the research community. In this regard, our project will provide highly innovative services built on top of existing EOSC services, thus allowing EU researchers to efficiently exploit large and
distributed datasets, following a service-oriented approach over the EOSC continuum.

The AI4EOSC project bases its activities on the technological framework delivered by the DEEP-Hybrid- DataCloud H2020 project. This project delivered the DEEP platform 1 (provided through the EOSC portal 2), allowing researchers to exploit computing resources from pan-European e-Infrastructures. The DEEP platform is a production-ready system that is being effectively used by researchers in the EU to train and develop machine learning and deep learning models. AI4EOSC will enhance this platform, delivering new high-level services and functionalities, targeting direct exploitation by scientific teams, allowing them to reduce the time to results and increase productivity by building better analytics tools, products, and services leveraging artificial intelligence, machine learning, and deep learning (AI/ML/DL), with focus on advanced features like federated learning, split learning or distributed training. We will make a special emphasis in ensuring that all the research outputs and sub-products (data, models, metadata, publications, etc.) adhere to the FAIR data and research principles.


This project has received funding from the European Union’s Horizon Research and Innovation programme under Grant agreement No. 101058593