GreenSCENT aims at developing a competence framework embracing all the Green Deal focus areas through an iterative, participated, experience and learning-by-doing based design approach. GreenSCENT will develop the GreenComp framework using both experts and researchers inputs and advise, citizen participation and stakeholder engagement initiatives; then it will test the framework on the field, in different European regions, different educational levels (from primary schools to higher education), at different engagement levels (from observation to data collection and processing, to contribution to scientific and policy agenda). Pilots will implement a range of pedagogies (collaborative learning, debate, research-based learning, inquiry-based learning) and demonstrators, digital, physical and hybrid educational technologies designed for or integrated into the project from existing initiatives. GreenSCENT legacy will consist of the Competence Framework (GreenComp), its Methodolog, Use Cases, User Guides; Training kits codesigned for implementing the framework; SCENTbox, the set of digital, physical and hybrid demonstrators developed by the project; and ECCEL, a European "driving license" for Climate and Environmental competences and skills, that will be tested during the project. GreenSCENT activities will involve more than 100 experts including the External Advisor Board members, already supporting the project and coming from all European Regions; about 45 schools and universities across EU will implement the pilot, while the Open Innovation Challenges designed and implemented by Agorize will cover the entire European Union and impact on tens of thousands of citizens. A special attention will be devoted to promote and foster the adoption of the framework, through the several tools developed, involving stakeholders (educational institutions, policy and decision makers, HR and industries) in the exploitation strategy of the project.

The core objective of FAIRiCUBE is to enable players from beyond classic Earth Observation (EO) domains to provide, access, process, and share gridded data and algorithms in a FAIR and TRUSTable manner. To reach this objective, we propose creating the FAIRiCUBE HUB, a crosscutting platform and framework for data ingestion, provision, analysis, processing, and dissemination, to unleash the potential of environmental, biodiversity and climate data through dedicated European data spaces. Within this project, TRL 7 will be attained, together with the necessary governance aspects to assure continued maintenance of the FAIRiCUBE HUB beyond the project lifespan. This projects goal is to leverage the power of Machine Learning (ML) operating on multi-thematic datacubes for a broader range of governance and research institutions from diverse fields, who at present cannot easily access and utilize these potent resources. Selected use cases will illustrate how data-driven projects can benefit from cube formats, infrastructure, and computational benefits. They will guide us in creating a user-friendly FAIRiCUBE HUB, which is tightly integrated to the common European data spaces, providing relevant stakeholders an overview of both data and processing modules readily available to be applied to these data sources. Tools enabling users not intimately familiar with the worlds of EO and ML to scope the requirements and costs of their desired analyses will be implemented, easing uptake of these resources by a broader community. The FAIR sharing of results with the community will be fostered by providing easy to use tools and workflows directly in the FAIRiCUBE HUB.