According to the European Research Data Landscape – Final report, a survey involving almost 9,898 responders, highlighted some of the main barriers to management and sharing of research data: time, effort, storage, skills required, and the lack of recognition and data protection. RAISE Suite will develop a system specifically designed to remove barriers to data sharing, replacing technological achievements that do not influence researchers’ attitude towards sharing data. To do so, RAISE Suite will develop the solutions required to automate the process from data collection to dataset generation, guided by a FAIR-by-design principle to remove barriers such as perceived effort, time, as well as skills required for data sharing. At the same time, EOSC-RAISE will be integrated into RAISE Suite, for a platform which supports simple dataset sharing and exploitation, mitigating the sense of lack of recognition and data protection among researchers. Furthermore, RAISE Suite will implement a DMP-guided data collection and management policy. In particular, RAISE Suite will not only adopt a Machine Actionable Data Management Plan (ma-DMP), but further extend it to support designated actions, τurning the persistent identifier DMP-ID into the main reference point for the whole data lifecycle, following research activities, making the connections with underlying algorithms and data, and updating the DMP accordingly from collection, depositing and storing, to discovery, management, processing, reusing and exploitation. RAISE Suite capitalises on the results of a previously funded EC initiative. To this end, RAISE Suite will leverage work done by the EOSC-RAISE project, incorporating its technical platform that moves from open data to data open for processing, introducing the technology required to cover the data lifecycle from the data collection to the dataset generation.

EOSC Future responds to INFRAEOSC-03-2020 call in order to integrate, consolidate, and connect e-infrastructures, research communities, and initiatives in Open Science to further develop the EOSC Portal, EOSC-Core and EOSC-Exchange of the European Open Science Cloud (EOSC). EOSC Future is structured around six thematic pillars that strategically group the work package tasks and activities and coherently present the key objectives and activities of the project to stakeholders: Pillar 1 on Policy & Strategy will coordinate and support a strategic vision for the future EOSC; Pillar 2 on Connection & Integration will connect and integrate EOSC infrastructures, data, and services; Pillar 3 on Excellent Science & Interdisciplinarity will extend the EOSC value Chain with scientific use cases; Pillar 4 on Growth & Innovation will grow and innovate EOSC with value-added services; Pillar 5 on Skills & Training will train users and providers of the EOSC ecosystem; and Pillar 6 on Engagement & Communications will engage the wider EOSC Community at a global level. EOSC Future will unlock the potential of European research via a vision of Open Science for Society by (1) bringing all major stakeholders in the EOSC ecosystem together under one project umbrella to break the disciplinary and community silos and consolidate key EOSC project outputs, (2) developing scientific use cases in collaboration with the thematic communities showcasing the benefits and societal value of EOSC for doing excellent and interdisciplinary research, (3) engaging the wider EOSC community and increasing the visibility of EOSC through communications campaigns, marketing strategies, and physical and online engagement events, and (4) including the EOSC community in developing the EOSC Portal (including the long tail of science, public and private sectors, and international partners) via co-creation open calls.

SoBigData++ strives to deliver a distributed, Pan-European, multi-disciplinary research infrastructure for big social data analytics, coupled with the consolidation of a cross-disciplinary European research community, aimed at using social mining and big data to understand the complexity of our contemporary, globally-interconnected society. SoBigData++ is set to advance on such ambitious tasks thanks to SoBigData, the predecessor project that started this construction in 2015. Becoming an advanced community, SoBigData++ will strengthen its tools and services to empower researchers and innovators through a platform for the design and execution of large-scale social mining experiments. It will be open to users with diverse background, accessible on project cloud (aligned with EOSC) and also exploiting supercomputing facilities. Pushing the FAIR principles further, SoBigData++ will render social mining experiments more easily designed, adjusted and repeatable by domain experts that are not data scientists. SoBigData++ will move forward from a starting community of pioneers to a wide and diverse scientific movement, capable of empowering the next generation of responsible social data scientists, engaged in the grand societal challenges laid out in its exploratories: Societal Debates and Online Misinformation, Sustainable Cities for Citizens, Demography, Economics & Finance 2.0, Migration Studies, Sport Data Science, Social Impact of Artificial Intelligence and Explainable Machine Learning. SoBigData++ will advance from the awareness of ethical and legal challenges to concrete tools that operationalise ethics with value-sensitive design, incorporating values and norms for privacy protection, fairness, transparency and pluralism. SoBigData++ will deliver an accelerator of data-driven innovation that facilitates the collaboration with industry to develop joint pilot projects, and will consolidate an RI ready for the ESFRI Roadmap and sustained by a SoBigData Association.

PathOS aims to identify and quantify the Key Impact Pathways of Open Science relating to the research system and its interrelations with economic and societal actors. PathOS will enable a new understanding of OS impacts and their causal mechanisms through its workplan encompassing actions to synthesise and structure current evidence, development of new methods and tools for measuring impact, iterative pilot-testing via in-depth case studies, innovative dissemination and networking, and co-creation synthesis activities culminating in policy recommendations. This is pivotal in order to develop effective OS policy in the EU. It will do so by collecting concrete evidence of the causal effects of OS by studying the pathways of OS practices, from input to output, outcome and impact, including the consideration of enabling factors and key barriers. Impacts and pathways will be developed in particular in the three areas of science, society and economy. By investigating, measuring and comparing its costs and benefits together with its pathways, PathOS will (i) bring a better understanding of the implications of open science for science, economy and society, (ii) provide recommendations to policy makers and other actors in the R&I ecosystem as to how and to what extent open science should be promoted in a balanced way, and (iii) develop innovative tools and methods using a big data to augment traditional ones for studying the causal effects of open science. This will enable evidence-based Open Science policy prioritisation, maximum OS impact, and increased R&I capacity in EU research systems.

EOSC Beyond overall objective is to advance Open Science and innovation in research in the context of the European Open Science Cloud (EOSC) by providing new EOSC Core capabilities allowing scientific applications to find, compose and access multiple Open Science resources and offer them as integrated capabilities to researchers. To do so, EOSC Beyond supports a new concept of EOSC: a federated and integrated network of Nodes operated at different levels, national, regional, international and thematic, to serve the specific scientific missions of their stakeholders. Further specific objectives of the project are to accelerate ‘time to product’ of new scientific applications with software adapters, enable Open Science with machine composability and dynamic deployment of shared resources, support innovation in EOSC with a testing and integration environment, and align the EOSC Core architecture and specifications to integrate with European dataspaces. The project extends the state of the art of the EOSC Core and adopts a co-design methodology, including requirements elicitation, software development and validation in collaboration with different use cases from EOSC national and regional initiatives (e-Infra CZ, Czechia, NFDI, Germany, and NI4OS, South East Europe region), thematic research infrastructures from Social Sciences and Humanities (CESSDA), Life Sciences (CNB-CSIC and Instruct-ERIC), Environmental Science (ENES and LifeWatch), and Health and Food (METROFood-RI). EOSC Beyond builds on the capacities of prospective EOSC Nodes and partners with multi-annual experience in developing solutions for large-scale federated digital infrastructures and aligns with the technical architecture and requirements of data spaces from different business sectors. Ultimately, EOSC Beyond supports Open Science in modern, data-intensive, and multidisciplinary research, facilitating resource discovery, access, and reuse across scientific communities, organisations, and countries.