Instruct-ERIC prides itself on being a champion of gender equality within the research infrastructure community. Following the lifecycle of the first gender equality plan, Instruct has enhanced an already strong historical track record of gender equality, raising the base level of understanding and engagement with diversity practices and actions, whilst also reaching new heights of equality in the wider structural biology community. Instruct has expanded its ambition to include diversity in its equality activities, hence its second iteration being a diversity and gender equality plan – it was crucial to use the momentum gained from the initial audit of Hub staff and activities to measure feedback to develop impactful actions that Instruct can commit to. The culture of gender equality in Instruct runs from the decision-making level, through the Hub and its committees, to the way in which calls and access are provided to users, resulting in an increasingly diverse community of researchers that access Instruct services, providing the launchpad for continuing and improved equality in the structural biology community for years to come. Support from the Newcomer Gender Equality Champions prize will help Instruct to be even more ambitious with its future targets for gender equality and diversity.

The eRImote project is the first to consider solutions for digital and remote service provision across RI domains and to look for transferable practices and new developments that will improve accessibility and resilience of RI infrastructures. While existing processes will be collected, eRImote will also explore new solutions using defined use cases to develop and test their implementation in RI scenarios. This will take us beyond the state-of-the-art for concrete solutions. The eRImote consortium is relatively small with eight beneficiary participants representing four main ESFRI RI Roadmap domains. However, the consortium extends much more broadly through the existing contacts and networking partners of each of the project participants, increasing the reach out to hundreds of individuals, other European and global RIs, scientific networks, RI users, industry partners and policy makers. eRImote is intended for 30 months to enable timely interventions. The project is outlined relatively straightforward by four main activities. eRImote will create an online information platform with a publicly available data store on best practises and tools based on a landscape analysis, also with needs and impact. This will be translated into strategies on transition and use cases (Green Paper). All this is based on broad outreach and extensive dissemination beyond the consortium. The eRImote consortium will identify strategies and solutions to enable transition to remote and digital access to RI services that will help to enhance and make more accessible the service capacities of RIs while reducing the need for physical access to RI sites, bringing benefits to the green economy, reducing the footprint of RIs and increasing their inclusiveness as a result. In addition, eRImote will contribute to increased efficiency of remote access service provision at RIs, enhance mutual knowledge and trust, and develop joint strategies across the RI domains on transition to

This proposal systematically addresses the development, provision, and integration of services, across the European Research Infrastructures (RIs) landscape, that the scientific community can use to investigate the effects on health and the environment that artificial materials (including plastics, micro-, nano-, and biotechnological materials) can have. Exposure to such materials may occur as a result of their intended use (e.g., food packaging) or at the end of their lifecycle (e.g. plastic wear). These services, which are relevant to several areas of important societal and economic impact, are expected to span multiple scales and disciplines, including high-quality metrology, structural biology, microbiology, and ecotoxicology. The main output of this proposal will be a thorough overview of extant service offer by European RIs with respect to questions from state-of-the-art of scientific research in the aforementioned domains. FHERITALE will identify common strategies for the coordination and optimization of services at different RIs geared towards increasing the accessibility of relevant technologies. In parallel, it will identifty those service and technology gaps that are hampering high-impact research and preventing a timely assessment of the repercussions of new materials on health and the environment. These gaps constitute high-priority areas for future development. FHERITALE will design a coordination framework for the RIs to drive these key technological developments. The technological focus of this application includes emerging areas of research for which international interest is rapidly growing. The interdisciplinary nature of the cluster of identified technologies will connect health, food, and environment research, constituting one of the first examples of practical application of the “One Health” approach. This coordination effort will also serve as a fertile ground for further interdisciplinary research among RIs from the H&F and other domains.

The European Open Science Cloud (EOSC) aims to establish a FAIR research system in Europe through the EOSC Federation, enabling researchers to share and analyze data across disciplines and borders. The EOSC United project plays a crucial role in uniting the research community within this federation. The EOSC EU Node, launching in autumn 2024, will serve as the foundation for the EOSC Federation, providing blueprints and an interoperability framework for future nodes. It aims to promote multidisciplinary research by leveraging FAIR data and services across Europe and beyond. EOSC United supports the European Commission and EOSC EU Node contractors in promoting resource uptake. It engages various stakeholders, facilitates user involvement through use cases and adoption calls in collaboration with EOSC Gravity to showcase early successes. The project provides feedback on the EOSC EU Node's evolution and helps shape the EOSC Federation's governance and operational framework. Through these efforts, EOSC United aims to solidify EOSC's position in future EU framework programmes and ensure its success as a collaborative and sustainable research infrastructure. The project's work is essential in realizing the vision of open, accessible, and reusable scientific data across Europe.

Machine learning (ML) has enabled and accelerated frontier research in the life sciences, but democratised access to such methods is, unfortunately, not a given. Access to necessary hardware and software, knowledge and training, is limited, while methods are typically insufficiently documented and hard to find. Furthermore, even though modern AI-based methods typically generalize well to unseen data, no standard exists to enable sharing and fine-tuning of pretrained models between different analysis tools. Existing user-facing platforms operate entirely independently from each other, often failing to comply with FAIR data and Open Science standards. The field of AI and ML is developing at a staggering pace, making it impossible for the non-specialist to stay up to date. To enable the life science communities to benefit from AI/ML-powered image analysis methods, AI4LIFE will build bridges, providing urgently needed services on the common European research infrastructures. We will build an open, accessible, community-driven repository of FAIR pre-trained AI models and develop services to deliver these models to life scientists, including those without substantial computational expertise. Our direct support and ample training activities will prepare life scientists for responsible use of AI methods, while contributor services and open standards will drive community contributions of new models and interoperability between analysis tools. Open calls and public challenges will provide state-of-the-art solutions to yet unsolved image analysis problems in the life sciences. Our consortium brings together AI/ML researchers, developers of popular open source image analysis tools, providers of European-scale storage and compute services and European life sciences Research Infrastructures -- all united behind the common goal to enable life scientists to fully benefit from the untapped but potentially tremendous power of AI-based analysis methods.