With the advent of the Copernicus program with its wealth of open data, the Earth Observation application and service development domain is increasingly adopting big data technologies. This adoption is first related to efficient data storage and processing infrastructures, but most importantly data analytics and application development framework. CANDELA project main objective is to allow the creation of value from Copernicus data through the provisioning of modelling and analytics tools given that the tasks of data collection, processing, storage and access will be provided by the Copernicus Data and Information Access Service (DIAS), which the team is fully familiar with. The implementation starts by putting in place a set of powerful tools that drastically lowers the cost of getting familiar with the data and creating new services. These modules adopt new developments in the domain of machine learning, data mining, data fusion and web semantics, combining the Copernicus data and information with other non-Earth Observation data sources to derive novel applications and services. CANDELA will demonstrate the breadth of project capabilities with a real-life small demonstrator by means of two reference scenarios: a “macro-economics and agriculture” scenario to show how remote sensing capacities to extract adequate information from images could be used to feed economical models; and a “forest health monitoring” (FHM) scenario which aim is to present how Earth Observation satellite data collection can be used for the monitoring of forest health conditions. CANDELA team is a well-balanced consortium, consisting of nine partners from five European countries, and with strong participation from the industry as encouraged by the Call, being half of the partners well positioned SME’s.

This proposal introduces a pioneering new on-orbit services system concept which would rapidly industrialize the European space ecosystem, making Europe a world leader in robotized and sustainable modular infrastructures as well as reusable launchers, with additional competitive benefits for a sustainable European digital industry and sovereign cloud autonomy. European space technology has now reached a level of maturity that makes possible a revolutionary – yet feasible – endeavour: the installation of internet data centres in orbit, in order to reduce the exponential impact of digital technology on energy consumption and on climate warming. The installation of large modular space infrastructures with robotic assembly, megawatt level space-based solar power, high throughput optical communications, low cost and reusable launchers, is now within the European space industry’s capability. The goal of the proposed study is to demonstrate that placing future data centre capacity in orbit, using solar energy outside the earth’s atmosphere, will substantially lower the carbon footprint of digitalization. Space data centres could therefore become an active contributor to the EC Green Deal objective of carbon neutrality by 2050, which would justify the investment required to develop and install such a large space infrastructure system. It would also strengthen Europe’s digital sovereignty and autonomy, for a sustainable and prosperous digital future. Given the ambition and huge potential impact of this project, which would become a major European flagship program, a broad system-level feasibility and business study is necessary. For that purpose, the ASCEND consortium has brought together major players in the fields of environment analysis (Carbone 4, Vito), data centres architecture, hardware and software (Orange, CloudFerro, HPE), space systems development (Thales Alenia Space, Airbus, DLR), and access to space (ArianeGroup).

The project aerOS aims at transparently utilising the resources on the edge-to-cloud computing continuum for enabling applications in an effective manner, incorporating multiple services deployed on such a path. Therefore, aerOS will establish the missing piece: a common meta operating system that follows a collaborative IoT-edge–cloud architecture supporting flexible deployments (e.g., federated or hierarchical), bringing tremendous benefits as it enables the distribution of intelligence and computation – including Artificial Intelligence (AI), Machine Learning (ML), and big data analytics – to achieve an optimal solution while satisfying the given constraints. The overarching goal of aerOS is to design and build a virtualized, platform-agnostic meta operating system for the IoT edge-cloud continuum. As a solution, to be executed on any Infrastructure Element within the IoT edge-cloud continuum – hence, independent from underlying hardware and operating system(s) – aerOS will: (i) deliver common virtualized services to enable orchestration, virtual communication (network-related programmable functions), and efficient support for frugal, explainable AI and creation of distributed data-driven applications; (ii) expose an API to be available anywhere and anytime (location-time independent), flexible, resilient and platform-agnostic; and (iii) include a set of infrastructural services and features addressing cybersecurity, trustworthiness and manageability. aerOS will: (a) use context-awareness to distribute software task (application) execution requests; (b) support intelligence as close to the events as possible; (c) support execution of services using “abstract resources” (e.g., virtual machines, containers) connected through a smart network infrastructure; (d) allocate and orchestrate abstract resources, responsible for executing service chain(s) and (e) support for scalable data autonomy.

In today’s changing climate is of urgent importance to understand the adverse impacts of climate change to the local and regional Arctic natural environments, infrastructures and industries. To this end, Earth Observation (EO) is the way forward, as it is extremely challenging to obtain long-term continuous ground observations. Recent advances in EO sensors, in cloud computing, geographical information systems (GIS) and in the field of socioeconomics provide unique opportunities to promote research and socioeconomic studies in the Arctic. Yet, despite their plethora, EO data are provided in a dispersed and unconnected way through several web platforms and in diverse formats, making their use difficult. EO-PERSIST proposes the development of a single cloud-based system that will allow in a unique way the availability of the collection, management and exploitation of the available EO data suitable to permafrost studies. The system leverages existing services, datasets and novel technologies to: a)create a continuously updated ecosystem with EO datasets suitable for permafrost studies, b)promote methodological advances in permafrost studies by exploiting the huge volume of EO datasets and c)provide indicators directly connected with socioeconomic effects to permafrost dynamics. Experimental analysis will also be carried with the system to showcase its use via five carefully selected and innovative Use Cases, that will serve as Key Performance Indicators of the system. EO-PERSIST brings together staff from academia and industry via a series of carefully-designed secondments, establishing a unique fertile collaborative research and innovation environment to promote pioneering research and socioeconomic studies implementation in the Arctic. A strong inter-sectoral experienced research team, of 5 academic and 6 industrial partners, coming from Greece(3), North Macedonia (1), Finland(1), Sweden(1), Cyprus (1), Poland(1), Romania(2) and Italy(1) constitute the project’s consortium.

The EU Copernicus programme has established itself globally as the predominant spatial data provider, through the provision of massive streams of high resolution earth observation (EO) data. These data are used in environmental monitoring and climate change applications supporting European policy initiatives, such as the Green Deal and others. To date, there is no single European processing back-end that serves all datasets of interest, and Europe is falling behind international developments in big data analytics and computing. This situation limits the integration of these data in science and monitoring applications, particularly when expanding the applications to regional, continental, and global scales. The proposed C-SCALE (Copernicus - eoSC AnaLytics Engine) project aims to federate European EO infrastructure services, such as the Copernicus DIAS and others. The federation shall capitalise on the European Open Science Cloud’s (EOSC) capacity and capabilities to support Copernicus research and operations with large and easily accessible European computing environments. That would allow the rapid scaling and sharing of EO data among a large community of users by increasing the service offering of the EOSC Portal. By making such a scalable Big Copernicus Data Analytics federated services available through EOSC and its Portal and linking the problems and results with experience from other research disciplines, C-SCALE will help to support the EO sector in its development and furthermore will enable the integration of EO data into other existing and future domains within EOSC. By abstracting the set up of computing and storage resources from the end-users, C-SCALE will enable the deploying of custom workflows to quickly and easily generate meaningful results. The project will deliver a blueprint, setting up an interaction model between service providers to facilitate interoperability between commercial (e.g. DIAS-es) and public cloud infrastructures.