"Higher Education Classroom Of the Future (HECOF) project will be implemented by a mixed partnership of organisations from different sectors that have the capacity to innovate in terms of digital tools and teaching and learning methods for the higher education systems, by leveraging the power of AI and machine learning for student assessment and adaptive learning based on individual learner’s performance and behavior. The main goal of the HECOF initiative is to create systemic change in higher education teaching practice and national reforms in education by developing and testing an innovative personalised, adaptive way of teaching that exploit the digital data from students' learning activity in immersive environments and use computational analysis techniques from data science and AI. The project wil design and develop this learning system with a conceptual focus on ""Chemical Engineering"" academic discipline and will engage teaching staff and students from two pilot universties in its desing and pilot testing. HECOF also wants to foster the development and uptake of safe and lawful AI that respects fundamental rights by providing insights on ethical and legal issues around the design of the system. It will drive the policy agenda by formulating recommendations on the role and use of AI for personalised, adaptive learningHECOF technology has a clear potential to be mainstreamed in vocational education and training sector for employees in chemical engineering sector. Therefore, HECOF will support the first strategic priority of the Digital Education Action Plan (2021-2027), the development of a high-performing digital education ecosystem, by building capacity and critical understanding in all type of education and training institutions on how to exploit the opportunities offered by digital technologies for teaching and learning at all levels and for all sectors and to develop and implement digital transformation plans of educational institutions."

Across Europe, the need for a more dynamic governance and a better societal integration of research and innovation is increasingly appreciated. Internal drivers of change (such as the digitalization of science) and political will to better align with societal needs and concerns are bringing about aspirational policies and processes of transformation of the R&I system, including those of RRI – responsible research and innovation. In order for the aspirations of RRI to be realised, robust tools must be developed for R&I policy and practice. The MoRRI project (2014-2018) conceptualised and implemented the first RRI monitoring system in Europe. The SUPER_MoRRI project builds upon and continues the work of MoRRI, ensuring sustained data collection, curation, further assessment and refinement of the MoRRI indicators. EU-28(-27) data will be complemented by monitoring data from selected non-EU countries. Furthermore, SUPER_MoRRI will go well beyond the technical efforts of MoRRI and develop a more complete scientific understanding of the complex and diverse relationships between RRI policies and practices and their societal, democratic and economic benefits. These theoretical advances together with the continuous data stream into the project form the basis of the iterative learning processes needed to create a mature monitoring system with indicators and metrics that are robust, realistic, in themselves responsible, and easy to implement. To meet these ambitious research challenges, the original scientific partners of MoRRI have included complementary RRI expertise to form the truly interdisciplinary SUPER_MoRRI consortium. In line with the concept of RRI itself, our learning processes will also be enhanced by participatory co-creation practices with stakeholders. Last, but not least, the project includes a series of measures to facilitate dissemination of the mature monitoring system, including international benchmarking and an easy-to-customize online dashboard system.

InterPED aims to enable the concept of PEDs via sector coupling, cross-vector integration, demand flexibility and consumer engagement, while improving utilisation of local RES, storage and excess/waste heat (E/WH) sources. InterPED will couple RES, storage and E/WH sources (community assets) available in the pilots with the necessary know-how and ICT expertise to ensure improved operation of PEDs and grid robustness. This will allow InterPED’s end users (aggregators, service providers, urban planners) to deliver benefits to both, grid stakeholders (DSO/TSOs) and final consumers (and prosumers). To do so, InterPED will deliver a scalable and adaptable cloud-based platform composed of analytical, modelling and optimization services for planning, supervision and control of integrated PEDs (including power, heating and cooling, mobility). Optimized PED operations will be demonstrated at pilot sites, while enabling a cooperative demand response (DR) strategy at community/district level. In addition to automated control actions, InterPED intends to engage the consumers via community building (e.g. CECs or RECs), representing a still largely untapped source of flexibility, while enabling them to play an active role in grid balancing. By making it cloud-based and by ensuring system interoperability (both syntactic and semantic), InterPED will enable aggregators and actors positioned to adopt proposed business model (e.g. ESCOs, energy retailers, DSOs) to deploy the InterPED solution immediately almost anywhere, while reducing the cost to its scalability. The key strategy to ensure solutions will work well in an everyday context of consumers, is that InterPED will involve the consumers (community) and service providers in the design of the solutions through participatory co-design processes. InterPED will verify the technical and commercial feasibility of its integrated package in four large-scale pilots, each representing an existing PED.

ITHACA project aims to better understand the complexities and controversies for applying AI into the field of civic participation and stimulate new and responsible practices of research and innovation that anchor AI technologies design in human rights, values and principles, and moral and ethical reflection.The project vision is to contribute to the maximisation of the possible positive impact of AI on the functioning of democratic institutions and processes by developing and testing of a human centric Artificially Intelligent and Ethics by Design online discussion platform for civic participation in local governance, which incorporates human and social interpretations into the design process to ensure that AI decision-making processes are explainable, transparent and fair. ITHACA will pay particular attention to the needs and voices of citizens from vulnerable groups, with a view to ensuring that human rights impacts stemming from the design, development and ongoing deployment of algorithmic systems are comprehensively monitored, debated and addressed. Through its pilot activities in two different EU countries, ITHACA plans to assess the ability of AI to enhance citizens participation in the local governance while preventing or minimizing possible adverse effects stemming from unregulated use of AI and empowering citizens with knowledge about the AI model involved. ITHACA will also provide scalable tools for the identification of security risks and threats and for conformity with the Fairness principle and Privacy principle in AI-based systems and big data for civic engagement applications. Based on its implementation experiences, the project will define a data governance framework with relevant ethical principles and practices to be implemented in the design, development, deployment process for AI civic engagement platforms as well as policy recommendations on philosophical, legal and ethical values that should be embedded in the development of such platforms.

The MatCHMaker project is determined to support excellence in research on methods and tools for advanced materials development. MatCHMaker will enable the integration and interoperability of complex C&M workflows matching the needs of EU manufacturing industry. Requirements on multiphase and multiscale materials coming from Construction, Energy and Mobility sectors will be translated into specific innovation challenges that can be addressed by an integrated approach combining characterization and (physics and data-based) modelling for establishing the process-microstructure-macroscopic properties correlation in advanced materials in a reproducible and efficient way reducing development costs, time and risks while improving sustainability. Knowledge transfer, data sharing and full interoperability between C&M “communities” will be facilitated using data related standards (CHADA, MODA, EMMO) and by the creation of an open repository with connection to design and manufacturing processes. The repository will be based on Semantic Web to represent rich and complex ontologies. EMMO is the starting point, domain and application ontologies related to MatCHMaker use cases and providing a fully semantical vocabulary to describe the produced C&M data will be developed. Standardisation of MatCHMaker ontologies, data documentation and domain ontologies will be sought via engagement in specific activities (e.g. collaboration with EMMC, EMCC, OntoCommons CSA). The ambition of MatCHMaker is to validate project results on three Use Cases (UC) representatives of low carbon and clean industry: UC1\Construction\Cement; UC2\ Energy\ Solid Oxide Fuel Cells/Solid Oxide Electrolysis Cells (SOFC/SOEC); UC3\ Mobility\Proton-Exchange Membrane Fuel Cells (PEMFC). The project will foster synergies and interaction with EMMC and EMCC to align MatCHMaker results to councils’ objectives.