EarthServer-2 makes Agile Analytics on Big Earth Data Cubes of sensor, image, simulation, and statistics data a commodity for non-experts and experts alike through • navigation, extraction, aggregation, and recombining of any-size space/time data cubes; • easy to install & maintain value-adding services extending the existing portfolio of data and compute centers; • based on open standards, in particular: the OGC Big Data standards and the forthcoming ISO SQL/MDA (“Multi-Dimensional Arrays”) standard. In the Joint Research Activity, the project will advance the existing, world-leading rasdaman Array Database technology wrt. query functionality, inter-federation data processing with automatic data and query distribution, tape archive integration, and 3D/4D visualization based on NASA’s virtual globe technology. In the Services Activity, large data centers (ECMWF, PML, MEEO/ESA, GeoScience Australia, JacobsUni) will set up water, air, weather, and planetary services on 3D & 4D data cubes up to Petabyte-size with user-tailored clients for both visual and textual ad-hoc mix&match. In the Networking Activity, the project will advance open Big Data standards in OGC, RDA, and ISO (in particular: write ISO SQL/MDA). Further, all adequate channels will be used for strong dissemination & exploitation, specifically: writing a monograph explaining OGC Big Geo Data standards; scientific publications & active conference organization; Earth science data user workshops for each domain addressed; actively contributing technology & experience to GEO / GEOSS and further bodies; establish standardized Big Geo Data benchmark and run it against EarthServer-2 and further relevant systems. Altogether, EarthServer-2 will maintain and extend the lead in Big Earth Data services established in the highly successful EarthServer-1 project. Being already supported by ESA, rasdaman will form an enabling building block for COPERNICUS / Sentinel.

According to Water Europe statistics, 90% of the global economy and 75% of jobs depend on water, while water-related risks are among the top 5 risks. Τhe term “water” includes both drinkable water (with respect to pollution) and hydrology water modelling (with respect to floods and sea level rise). As a result, the significance of modelling techniques, especially regarding water pollution, coastline management, flood prediction and sea level rise assessment cannot be overstated. Copernicus has already tools to forecast, assess and analyse such domains and also to manage forthcoming emergencies. Indeed, JRC states that Copernicus Emergency Management Service (CEMS) is gaining a lot of traction from policy makers, scientists and public bodies for managing, assessing and preventing climate-related emergencies such as floods and droughts. Despite this trend, the potential of Copernicus data and services, especially for emergency and climate applications has not been fully realised by industrial and policy-making stakeholders. TERRA realises that innovation stemming from Copernicus services and data could set the basis for future collaborations, accelerate R&I progress, and increase the EU’s excellence in cutting-edge technologies. To this end, we target the second R&I area of the “HORIZON-CL4-2024-SPACE-01-35”, namely the “the development of an integrated, harmonized and coherent product provision system … to improve global scale hydrological monitoring and forecasting.” TERRA envisions the creation of several services and product chains that fuse Copernicus services with state-of-the-art technologies to provide solutions for coastline detection, coastline erosion prediction, flood risk assessment and mitigation, water pollution assessment and coastline modelling. Τhe project targets the SWOT mission and Group on Earth Observation objectives, and provides the necessary framework to promote its outcomes through the Global Earth Observation System of Systems (GEOSS).

OpenAIRE-Nexus brings in Europe, EOSC and the world a set of services to implement and accelerate Open Science. To embed in researchers workflows, making it easier for them to accept and uptake Open Science practices of openness and FAIRness. To give the tools to libraries, research communities to make their content more visible and discoverable. To assist policy makers to better understand the environment and ramifications of Open Science into new incentives, scientific reward criteria, impact indicators, so as to increase research and innovation potential. To foster innovation, by providing SMEs with open data about scientific production. To this aim, OpenAIRE-Nexus onboards to the EOSC fourteen services, provided by public institutions, einfrastructures, and companies, structured in three portfolios: PUBLISH (catch all repository; Open Access overlay journal platform; data anonymization; Data Management Plans), MONITOR (Open Science and research impact monitoring; open citation indexes for article-article, article-dataset links; European monitoring of Article Processing Charges, publication usage statistics), and DISCOVER (open catalogue and APIs to the OpenAIRE Research Graph of interlinked publications, data, software, projects; discovery portals for communities; validation and brokering services for data sources to improve their metadata). The services are widely used in Europe and beyond and integrated in OpenAIRE-Nexus to assemble a uniform Open Science Scholarly Communication package for the EOSC. The project aims at forming synergies with other INFRAEOSC-07 awarded projects, the INFRAEOSC-03 project, research infrastructures, einfrastructures, and scholarly communication services define a common Open Science interoperability framework for the EOSC, to facilitate sharing, monitoring, and discovery of EOSC resources across disciplines.

DataGEMS is a data discovery platform with Generalized Exploratory, Management, and Search capabilities. DataGEMS is built on the principles of data FAIRness, openness and re-use. It aims to seamlessly integrate data sharing, discovery and analysis into a system that addresses the whole data lifecycle, i.e., sharing, storing, managing, discovering, analyzing and reusing (data and/or metadata), bridging the gap between the data provider and the data consumer. DataGEMS is a next-generation data discovery and management ecosystem that engulfs different types of data (structured, unstructured, real-time and historical) and enables users to (a) enrich data through powerful data profiling mechanisms (b) seamlessly discover and analyze data across and within datasets using user-intuitive discovery and analysis mechanisms, such as using natural language and patterns, and (c) effectively explore and combine data with the help of stepwise guidance mechanisms during dataset discovery and analysis. The effective and efficient functioning of these mechansims will be powered by a data and model management layer that decouples data management at the low level from the data analytics at the higher level. DataGEMS is informed by and will be initially tested and deployed to promote data FAIRness and benefit diverse user communities and types of users on core domains: education, meteorology, and language data infrastructures.

IntelComp sets out to build an innovative Cloud Platform that will offer Artificial Intelligence based services to public administrators and policy makers across Europe for data- and evidence-driven policy design and implementation in the field of Science, Technology and Innovation (STI) policy. Large STI datasets are processed on High Performance Computing (HPC) environment part of the European Open Science Cloud (EOSC) imitative. Public administration at all geographical and organizational levels, STI stakeholders and civil society produce a great amount of dynamic, multilingual and heterogeneous data (i.e. national STI strategies, plans and work programmes, calls, projects, reports, scientific publications, patents, dissemination articles, etc.), so understanding and analyzing this data is crucial for evidence-based policy making. The objective of IntelComp is to deliver a platform that provides tools for assisting the whole spectrum of STI policy, i.e., agenda setting, modeling design, implementation, monitoring and evaluation. It will do so by involving multi-disciplinary teams to co-develop innovative analytics services, Natural Language Processing pipelines and Artificial Intelligence workflows and by exploiting open data, services and computational resources from the EOSC, HPC environments and federated distributed operations at the European Union, national and regional level. It will ensure a cooperative environment where different actors can visualize, interact and analyze information. Through co-creation, IntelComp will adopt a living labs approach and will engage public policy makers, academia, industry, SMEs, local actors, civil society and citizens to explore, experiment with and evaluate STI policies at all stages. IntelComp will be targeting domains aligned with the European Agenda and the Horizon Europe Missions: Artificial Intelligence, Climate Change and Health.