INSTRUCT-ERIC

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

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.

European and global research infrastructures (RIs) provide facilities and resources to support excellence and innovation, delivering socio-economic value by raising skills, advancing knowledge and technology and its exploitation, and driving new development and construction. RIs closely engage with their specialist communities but RI sustainability in the long term requires engagement with civil communities and stakeholders where an understanding of the significance and the socio-economic benefits of the services delivered underpins financial and strategic support. RI-VIS will increase the visibility of European RIs to broader scientific communities, industry and strategic partners in third countries. The RI-VIS consortium has main membership from the life sciences RIs where there is urgent need to improve outreach and strategic partnerships. Partner RIs in other thematic groups ensure that outcomes are relevant to all. A major advantage of this consortium is first hand knowledge of RI services and operating processes and their user communities. RI-VIS will target communities and stakeholders with current and precise information and match them with RIs to facilitate i) the development of new collaborations, ii) user accessibility, iii) collaborative and innovative actions, iv) funding opportunities, v) knowledge transfer and vi) training opportunities. RI-VIS will make it easier for new entrants to find out how RIs are organized and funded, where and how to access RI services and where data is available. The communication framework will include several digital platforms to achieve broad reach and generate a communication toolkit to help others benefit from the experiences gained. RI-VIS will broker engagement of RIs with various stakeholder groups using events and thematic workshops. A collaboration toolkit will identify best engagement strategies to bring new agreements to fruition. RI-VIS will mentor a selection of partnerships to broker cooperation agreements.

The IMAGINE project will develop the next generation of scale-crossing imaging technologies to enable an integrated investigation of structure and function of biological systems. It will focus on developing and integrating four major disruptive microscopy technologies, namely: X-ray imaging, cryo electron microscopy, cryo and dynamic super-resolution microscopy and large volume intravital light microscopy. It will furthermore develop the AI-powered image analysis and data integration/sharing capabilities, that are needed to correlate these technologies and make their data widely available. To harness their power for some of the most pressing societal challenges, IMAGINE will prepare its new imaging technologies to be deployed in the field, on Europe’s seas and coastlines, so that the collection of environmental specimen in their natural context can be coupled with their study by highest resolution imaging technologies. The IMAGINE technologies are currently at the cutting edge of physics and engineering and therefore only available in isolation and to specialists. The project aims to bring them to the European life science user community at large by developing and validating them for service readiness, so that they can be provided as future services by Europe’s Research Infrastructures (RIs). To this end, the project will train RI staff on the operation and use of the IMAGINE technologies. To promote broad dissemination as commercial instruments, IMAGINE will develop technologies jointly between academia and industry promoting open innovation with key instrumentation manufacturers in the imaging field. The life science community increasingly relies on RIs to access ever more complex and rapidly developing scientific instruments. The scale-crossing imaging technologies developed by IMAGINE will be critical to empower ground-breaking research in Europe, that is so urgently needed to address some of the biggest challenges our societies will face in the future.

canSERVs mission is to make cutting-edge and customised research services available to the cancer research community EU wide, enable innovative R&D projects and foster precision medicine for patients benefit across Europe. By connecting, coordinating, and aligning existing oncology and complimentary research infrastructures (RIs) and providing services in a synergistic way transnationally, canSERV will capitalise on the critical mass of experts and cutting-edge services offered by canSERVs RIs and their extended network. canSERV brings together world-class European life science RIs (BBMRI, EURO-BIOIMAGING, ELIXIR, EU-IBISBA, EuroPDX, EU-OPENSCREEN, INSTRUCT, EATRIS, INFRAFRONTIER, EMBRC, ECRIN, EATRIS, MIRRI, ARIE, CCE, EORTC and IARC) that collectively not only covers all aspects along the development pipeline for oncology, but is also capable of interconnecting these technologies providing users a guidance for navigating them through the entire translational value chain. The patient organisation ECPC will bring the patient?s perspective, while the two SMEs, ARTTIC and ttopstart, will provide valuable input regarding stakeholder engagement, and project management activities. A common access management system (CAMS) will be developed based on mature solutions from INSTRUCT and BBMRI. The CAMS will provide a method for selection of services, construction and submission of research proposals, multi-step review of research proposals, and tracking of the access process from approval through delivery to conclusion. Through a united user-intuitive transnational access where a united catalogue of oncology services will be offered, our users will have access to a comprehensive service portfolio. As our ambition is to scale up canSERV to a pan-European collaboration of RIs for accelerating the development and implementation of solutions for the cancer patient community, the sustainability of this network beyond the end of the project will also be addressed.