EGI Foundation

The interdependence of human, animal, plant and ecosystem health necessitates systemic, cross-domain collaboration to address global challenges, such as emerging diseases, climate change and biodiversity severe change. Through the Crete Declaration, Europe’s (e-)infrastructures, organisations and projects that focus on the functioning of our biosphere commit to jointly advancing the One Health approach. In doing so, the signatories aim to strengthen Europe’s resilience and leadership through the sharing of data and expertise, the development of innovative solutions and the promotion of evidence-based policies.

CoastPredict UN Ocean Decade Programme represents a cutting-edge initiative that integrates scientific advancements in coastal ocean observing and predicting with the aim of developing applications to support coastal resilience. CoastPredict will support multi-hazard early warning systems, climate risk assessment, and digital twins of the coastal ocean for ecosystems and environmental management and climate adaptation, by integrating observational data from satellites, existing in situ networks, Internet of Things (IoT) sensors, and citizen science into coastal models, and using Artificial Intelligence (AI) and Machine Learning (ML) tools to underpin risk mitigation and resilience strategies.The development of a flexible and interoperable 'GlobalCoast' distributed cloud infrastructure, will link a network of regional and Pilot Site data spaces and existing repositories—such as EMODnet, Copernicus —through a federated system with orchestrated workflows that will provide a cloud-based platform for high-resolution data sharing and analytic tools to ultimately bridge the end-to-end value chain from oceanographic data to user-focused applications. This system will enhance interoperability and real-time access to diverse data including from satellites and cost-effective in situ instruments, and will provide cloud-based computing capacity. The infrastructure will allow for scalable, region-specific cloud platforms, each tailored with customised models and high-resolution simulations for local needs. Furthermore it will support sharing and adaptation of existing prototypes for other regions, for example climate downscaling for risk assessment in the Adriatic Sea, multi-risk early warning systems for extreme events in the Savannah region, and digital twins for nature-based solutions in Italy’s Emilia-Romagna region. Utilising Application Programming Interfaces (APIs), AI and ML driven services, CoastPredict’s cloud framework will enable adaptive, localised modelling, such as storm surge predictions and marine heat wave tracking, offering end users—including researchers, environmental managers, and coastal communities—actionable insights in response to evolving climate risks. *This abstract is proposed for IOC Session 1 - From science to shoreline: bridging knowledge, policy and action for coastal resilience.

The EC-funded iMagine project aims to revolutionise aquatic science research by providing open access to AI-powered image analysis tools and resources. Focused on the theme of "Healthy Oceans, Seas, Coastal and Inland Waters," iMagine addresses the growing need for efficient analysis of vast amounts of image data generated from diverse sources like underwater cameras, drones, microscopes, and satellites.iMagine operates the iMagine AI Platform", a computational platform built upon the AI4OS framework and supported by AI4EOSC. Hosted on OpenStack clouds within the EGI e-Infrastructure Federation, the platform offers significant GPU and storage capacity to handle the dynamic needs of various research projects. It provides a complete suite of tools for the entire machine learning lifecycle, including image annotation, preprocessing, a deep learning model catalogue, model training and evaluation, and model inference for scientific end-users. This comprehensive approach facilitates collaboration and knowledge sharing between AI experts and aquatic science researchers.The platform's core functionalities include:A generic computational platform supporting the development of AI-based image analysis services for the aquatic science community. Development of AI-based image analysis services addressing various scientific challenges within aquatic research. Provision of labelled image datasets, enabling AI models' training and retraining. Sharing of best practices, disseminating knowledge related to imaging data and AI-driven image analysis in aquatic sciences. iMagine supports a diverse range of use cases, demonstrating the power of AI for image analysis in aquatic research. These use cases tackle critical issues including floating litter classification and quantification, plankton taxonomic identification, ecosystem statistics generation, oil spill movement and spread prediction, underwater audio data analysis to track vessel activity, and coral reef health monitoring.The iMagine Competence Centre, consisting of AI experts, domain scientists, and image data owners, facilitates collaboration between use cases and platform providers. The Competence Centre organises regular meetings, training sessions, and feedback collection to refine AI models and ensure the development of robust online services for end-users.To further enhance data quality, reproducibility, and scientific progress, iMagine adheres to best practices in data management, quality control, and model development. All use cases contribute to publicly available image datasets on Zenodo, allowing for model validation, retraining, and the development of new models. iMagine actively collaborates with other prominent projects like EOSC, AI4EU, and Blue-Cloud 2026 to maximise its impact and promote the broader adoption of AI-powered solutions within the aquatic science community.

JupyterHub is an open-source system enabling multiple users to access individual computational environments. This facilitates collaborative development and execution of Jupyter notebooks, Python scripts, and other tools among researchers and educators

Research projects heavily rely on the exchange and processing of data and in this context Pangeo (https://pangeo.io/), a world-wide community of scientists and developers, thrives to facilitate the deployment of ready to use and community-driven platforms for big data geoscience. The European Open Science Cloud (EOSC) is the main initiative in Europe for providing a federated and open multi-disciplinary environment where European researchers, innovators, companies and citizens can share, publish, find and re-use data, tools and services for research, innovation and educational purposes. While a number of services based on Jupyter Notebooks were already available, no public Pangeo deployments providing fast access to large amounts of data and compute resources were accessible on EOSC. Most existing cloud-based Pangeo deployments are USA-based, and members of the Pangeo community in Europe did not have a shared platform where scientists or technologists could exchange know-how. Pangeo teamed up with two EOSC projects, namely EGI-ACE (https://www.egi.eu/project/egi-ace/) and C-SCALE (https://c-scale.eu/) to demonstrate how to deploy and use Pangeo on EOSC and emphasise the benefits for the European community. The Pangeo Europe Community together with EGI deployed a DaskHub, composed of Dask Gateway (https://gateway.dask.org/) and JupyterHub (https://jupyter.org/hub), with Kubernetes cluster backend on EOSC using the infrastructure of the EGI Federation (https://www.egi.eu/egi-federation/). The Pangeo EOSC JupyterHub deployment makes use of 1) the EGI Check-In to enable user registration and thereby authenticated and authorised access to the Pangeo JupyterHub portal and to the underlying distributed compute infrastructure; and 2) the EGI Cloud Compute and the cloud-based EGI Online Storage to distribute the computational tasks to a scalable compute platform and to store intermediate results produced by the user jobs. To facilitate future Pangeo deployments on top of a wide range of cloud providers (AWS, Google Cloud, Microsoft Azure, EGI Cloud Computing, OpenNebula, OpenStack, and more), the Pangeo EOSC JupyterHub deployment is now possible through the Infrastructure Manager (IM) Dashboard (https://im.egi.eu/im-dashboard/login). All the computing and storage resources are currently supplied by CESNET (https://www.cesnet.cz/?lang=en) in the frame of EGI-ACE project (https://im.egi.eu/). Several deployments have been made to serve the geoscience community, both for teaching and for research work. To date, more than 100 researchers have been trained on Pangeo@EOSC deployments and more are expected to join, in particular with easy access to large amounts of Copernicus data through a recent collaboration established with the C-SCALE project. In this presentation, we will provide details on the different deployments, how to get access to JupyterHub deployments and more generally how to contribute to Pangeo@EOSC.

The European Commission has a program to accelerate the Digital Transition and is putting forward a vision based on cloud, common European Data Spaces and AI. As the data space paradigm unfolds across Europe, the Green Deal Data Space emerges. Its foundational pillars are to be built by the GREAT project. Data Spaces will be built over federated data infrastructures with common technical requirements (where possible) taking into account existing data sharing initiatives. Services and middleware developed to enable a federation of cloud-to-edge capacities will be at the disposal of all data spaces.GREAT, the Green Deal Data Space Foundation and its Community of Practice, has the ambitious goal of defining how data with the potential to help combat climate and environmental related challenges, in line with the European Green Deal, can be shared more broadly among many stakeholders, sectors and boundaries, according to European values such as fair access, privacy and security. The project will consider and incorporate community defined requirements and use case analyses to ensure that the resulting data space infrastructure is designed and built with and for the users. An implementation roadmap will guide the efforts of multiple actors to converge toward a blueprint technical architecture, a data governance scheme that enables innovative business cases, and an inventory of high value datasets, that will enable proof of concept, implementation and scale-up of a minimum viable green deal data space.This roadmap will identify the resources and other key ingredients needed for the Green Deal Data Space to be successful. Data sharing by design and data sovereignty are some of the main principles that will apply from the early stages ensuring cost effective and sustainable infrastructures that will drive Europe towards a single data market and green economic growth. This talk will present how to engage with the project, the design methodology, progress towards the roadmap for deployment and the collaborative approach to building data spaces in conjunction with all the sectoral data spaces and the Data Space Support Centre.

The initial Data Management Plan (DMP) introduces a report that specifies how research data will be collected, processed, monitored, and catalogued. Each dataset describes the type of data and their origin, the related metadata standards, the approach to sharing and target groups, and the approach to archival and preservation. This deliverable is considered a living document that will evolve during the project’s lifespan.

The European Open Science Cloud's (EOSC) ambition to provide European researchers, innovators, companies, and citizens with a federated and open multi-disciplinary environment where they can publish, find and reuse data, tools and services for research, innovation, and educational purposes. To enable this, EOSC promotes the use of the FAIR (Findable, Accessible, Interoperable and Re-usable) principles. The EOSC Sustainability Working Group under the EOSC Secretariat published the FAIR Lady Report (European Commission, Directorate-General for Research and Innovation, 2020), formulating recommendations for sustainability in the form of a Minimal Viable EOSC (MVE) including criteria for its sustainable implementation, formed by three essential components: EOSC Core, containing the minimum set of components necessary to provide researchers with the means to discover, share, access and reuse data and services; ESOC Exchange, a marketplace built on top of the EOSC Core to extend the set of public and private providers, and EOSC Data federation. EOSC Core, containing the minimum set of components necessary to provide researchers with the means to discover, share, access and reuse data and services; ESOC Exchange, a marketplace built on top of the EOSC Core to extend the set of public and private providers, and EOSC Data federation. The EOSC Association was established in July 2020 as the legal entity to govern EOSC. The Association appointed several Advisory Groups to provide recommendations towards the implementation of EOSC, including two Task Forces on Long Term Data Preservation and on the Financial Sustainability for Sustaining EOSC. This presentation will focus on the Financial Sustainability Task Force. The Task Force formed three "Working Streams" following the recommendation of the FAIR Lady Report to tackle the EOSC Core, Exchange, and Data Federation in smaller groups. Within the Data Federation Working Stream, the experts have identified many thematic data federations that have exisisted for quite some time, notably in environmental sciences, biodiversity, and social sciences. The case of Biodiversity Informatics is presented here as one of these sucess stories, retracing the history of major data federations such as GBIF (Global Biodiversity Information Facility), the CoL (Catalogue of Life), BHL (Biodiversity Hertiage Library) and how they managed to move from community-driven initiatitves to structurally funded research infrastructures supported by national and international governmental authorities with a long term perspective, leading to the establishment of infrastructures like the Distributed System of Scientific Collections (DiSSCo) and LifeWatch. This presentation will also address the essential contributions of associations like TDWG (Biodiversity Information Standards) and CETAF (Consortium of European Taxonomic Facilities) to achieving long-term sustainability and on how to successfully obtain complementary funds from EU projects in Horizon 2020 and its successor, Horizon Europe, with programs such as Synthesis of Systematic Resources (SYNTHESYS), DiSSCo Prepare, Biodiversity Community Integrated Knowledge Library (BiCiKL), and Transforming European Taxonomy through Training, Research, and Innovations (TETTRIs), to name a few.

<p>This report presents an update of the assessment of the C-SCALE services provided through the Virtual Access (VA) mechanism to the users. These include computing and storage resources. The deliverable describes the existing VA installations, their management within the project, updates the usage metrics delivered from the start of the project (January 2021) until Month 18 (June 2022) and reports on the Green Computing metrics and initiatives from the C-SCALE providers.</p>