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Life Science (LS) communities must increase the sustainability of their data resources, software tools, and workflows, to allow their long-term re-use by the wider scientific community, especially in future applications involving machine-based analyses. Here, we describe key findings regarding sustainable LS resources, based on experiences from the EOSC-Life project. EOSC-Life involves 13 European LS Research Infrastructures. It lays the foundation for an open, digital and collaborative space for biological and medical research. We describe organisational, technical, financial and legal/ethical challenges that represent the main barriers to sustainability in the LS domain. Using lessons from 27 scientific projects selected via open calls, we demonstrate the efficiency of the EOSC-Life support model for sustainable FAIR data management and explore the complex sustainability needs for sensitive- and industry-related data resources. We describe cross-disciplinary sharing of best practices, and how this contributes to the sustainability of knowledge across communities, through building of training resources. We formulate a set of recommendations, focusing on working with experts, and communicating outcomes, to establish strong credibility and recognition of research projects. Furthermore, demonstrating and practising also permit a more sustainable adoption of reproducible research outputs. Recommended measures include sustainable training methodologies, as well as ensuring high quality metadata to drive the sustainable reusability of scientific objects. Responsibilities and roles to ensure sovereignty, sustainable services and tools must also be attributed. Finally, our analysis demonstrates how data harmonisation facilitates interoperability of tools, data, solutions and a better understanding of concepts, functionalities and semantics in the LSs., This research is mainly a product of the EOSC-Life European programme funding from the European Union's Horizon Europe research and innovation programme under grant agreement Nº824087. Complementary support was provided through EU funded project AgroServ (grant agreement Nº101058020), EU funded project BY-COVID (grant agreement Nº101046203), EU funded project DANUBIUS-IP (grant agreement Nº101079778), EU funded project EMPHASIS-GO (grant agreement Nº101079772), EU funded project FAIRplus (IMI grant agreement Nº802750), EU funded project FAIRsharing (Wellcome grant agreement Nº212930/Z/18/Z), EU funded project ISIDORe (grant agreement Nº101046133), EU funded project Precision Toxicology (grant agreement Nº965406), UKRI DASH (grant agreement NºMR/V038966/1). Special thanks to T. Biro and her radical collaboration team from Research Data Alliance who gave us great inspiration on how to lead this radical collaboration work.

The Horizon Europe project ISIDORe is dedicated to pandemic preparedness and responsiveness research. It brings together 17 Research Infrastructures (RIs) and networks to provide a broad range of services to infectious disease researchers. An efficient and structured treatment of data is central to ISIDORe’s aim to furnish seamless access to its multidisciplinary catalogue of services, and to ensure that users’ results are treated FAIRly. ISIDORe therefore requires a data management plan (DMP) covering both access management and research outputs, applicable over a broad range of disciplines, and compatible with the constraints and existing practices of its diverse partners. We undertook an iterative, step-by-step, process to build a community-approved living document, identifying good practices and processes, on the basis of use cases, presented as proof of concepts. International fora such as the RDA and EOSC, and primarily the BY-COVID project, furnished registries, tools and online data platforms, as well as standards, and the support of data scientists. Together, these elements provide a path for building an umbrella, FAIR-compliant DMP, aligned as fully as possible with FAIR principles, which could also be applied as a framework for data management harmonisation in other large-scale, challenge-driven projects. Finally, we discuss how data management and reuse can be further improved through the writing of realistic DMPs using 'DMP profiles' and, in the future, the contribution of an inter RIs data steward network, to produce a Community of Practice that could be integrated into planned trans-RI competence centres., Preprint added on zenodo with the autorisation of DSJ Editor

A análise de cenário representa uma iniciativa do Instruct-ERIC de realizar um entendimento de baixo para cima da situação da região da América Latina e Caribe (LAC) com respeito à pesquisa em Biologia Estrutural., This report has been translated into Brazilian Portuguese from the English version - https://zenodo.org/record/7260779#.Y7QYuOzP2dG

Este análisis panorámico, que es una iniciativa de Instruct-ERIC, tiene como finalidad lograr comprender - en una perspectiva de abajo hacia arriba - la situación de la biología estructural existente en la región de Latinoamérica y el Caribe (LAC)., This report has been translated into Spanish from the English version - https://zenodo.org/record/7260779#.Y7QYuOzP2dG

The landscape analysis explores the opinions of structural biologists on how access provision to research infrastructure is currently facilitated in Latin America. The analysis aims to understand the environment of structural biology research in Latin America, as well as the challenges to carry out excellent research in the region., This report is also translated into: Brazilian Portuguese - https://zenodo.org/record/7501164#.Y7QblezP2dE Spanish - https://zenodo.org/record/7501152#.Y7QeoezP2dE

This deliverable 3.2 is a report on the demonstrator projects, the eight scientific and technical pilot projects that were selected to provide concrete scientific use-cases and guide and structure the work done in EOSC-Life to build an open digital and collaborative space for biological and medical research. We report in this deliverable the process of integration of the demonstrators within EOSC-Life, the achievement of the demonstrators who developed and made available to the scientific community several valuable resources (databases, workflows, web platform...), the actions undertaken within EOSC-Life to disseminate the demonstrator achievement and finally the results of the demonstrator survey to learn from the demonstrator experience and improve the integration of the new pilot project within EOSC-Life.

The EOSC-Life project aims to integrate data resources and data processing workflows developed by and in collaboration with the Life Science Research Infrastructures (LS RIs) in the European Open Science Cloud (EOSC). This Work Package, WP3, has the objective to identify scientific user projects that will drive this integration and that will allow the scientific community to shape the building of the EOSC for the life sciences by expressing their needs, and by feeding in their requirements. With this document, WP3 presents the guidelines on the preparation, organization and framework of Open Calls for User Projects that will be the main tool for the identification of suitable projects. The Open Calls are designed to contribute to achieving the overarching goal of WP3: to enable EOSC-empowered ground-breaking research, and to generate new knowledge by linking the life science communities to a variety of data resources and a platform of various data analysis tools. By identifying and selecting suitable user projects, WP3 will take a pragmatic approach for populating as well as developing solutions and testing of the EOSC for life sciences. Reusing FAIR data resources and having workflows run in the cloud is becoming increasingly important for researchers, however, building and spreading of cloud technology related skills is still needed for many researchers. WP3 will address those scientists via Open Calls by offering applicants training and consultation with experts across the EOSC-Life consortium. By providing funding, WP3 will also empower scientific groups that have built the capacity and skill sets to run their projects mostly independently or in collaboration. Importantly, selected projects are expected to have a lasting impact and to leave behind some legacy, so that future projects can benefit from their work and re-use their data, tools or workflows. Projects should present novelty in terms of the interplay between RIs and the EOSC, and address important challenges and needs of the life science community.

This Data Management Plan (DMP) describes the data management life cycle for the data to be collected, processed, and generated by the Horizon Europe eRImote project. It covers data formats such as text documents, presentations, tables, survey data, personal data, as well as information materials presented on the eRImote website. The first version of the DMP is submitted by month 4 of the project but is intended to function as a living document.