Project and Goals

The Project

AI4EOSC stands for Artificial Intelligence for the European Open Science Cloud.

Artificial Intelligence (AI) along with Deep Learning (DL) and Machine Learning (ML) 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. Expectations are high and so is their potential.

Besides, machine and deep learning applications and services are increasingly 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, the 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, with focus on advanced features like federated learning, split learning or distributed training. AI4EOSC 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.


The main goal of the AI4EOSC project is to foster an AI, ML and DL exchange in the EOSC context, enhancing the current EOSC service offer delivering added value, innovative and easily customisable services serving a broad range of scientific users. As such, we will focus on tools to provide AI, ML and 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. Providing ML practitioners with feature-rich services to build and deploy customisable ML, DL and AI applications following a platform and serverless approach with horizontal scalability over the EOSC continuum.
  2. Enhancing existing cloud services to support ML and DL on distributed datasets, with a particular focus on federated learning. Delivering methods to build and compose machine learning and deep learning tools, making possible the development of more complex data-driven composite AI applications.
  3. Fostering a ML and DL exchange in the context of the European Open Science Cloud, enhancing and increasing the application offer currently available in the DEEP Open Catalogue.
  4. Extending the service offer and the capabilities available 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.