Dataset Information

"Be sustainable": EOSC-Life recommendations for implementation of FAIR principles in life science data handling.

ABSTRACT: The main goals and challenges for the life science communities in the Open Science framework are to increase reuse and sustainability of data resources, software tools, and workflows, especially in large-scale data-driven research and computational analyses. Here, we present key findings, procedures, effective measures and recommendations for generating and establishing sustainable life science resources based on the collaborative, cross-disciplinary work done within the EOSC-Life (European Open Science Cloud for Life Sciences) consortium. Bringing together 13 European life science research infrastructures, it has laid the foundation for an open, digital space to support biological and medical research. Using lessons learned from 27 selected projects, we describe the organisational, technical, financial and legal/ethical challenges that represent the main barriers to sustainability in the life sciences. We show how EOSC-Life provides a model for sustainable data management according to FAIR (findability, accessibility, interoperability, and reusability) principles, including solutions for sensitive- and industry-related resources, by means of cross-disciplinary training and best practices sharing. Finally, we illustrate how data harmonisation and collaborative work facilitate interoperability of tools, data, solutions and lead to a better understanding of concepts, semantics and functionalities in the life sciences.

SUBMITTER: David R

PROVIDER: S-EPMC10690449 | biostudies-literature | 2023 Dec

REPOSITORIES: biostudies-literature

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"Be sustainable": EOSC-Life recommendations for implementation of FAIR principles in life science data handling.

David Romain R Rybina Arina A Burel Jean-Marie JM Heriche Jean-Karim JK Audergon Pauline P Boiten Jan-Willem JW Coppens Frederik F Crockett Sara S Exter Katrina K Fahrner Sven S Fratelli Maddalena M Goble Carole C Gormanns Philipp P Grantner Tobias T Grüning Björn B Gurwitz Kim Tamara KT Hancock John M JM Harmse Henriette H Holub Petr P Juty Nick N Karnbach Geoffrey G Karoune Emma E Keppler Antje A Klemeier Jessica J Lancelotti Carla C Legras Jean-Luc JL Lister Allyson L AL Longo Dario Livio DL Ludwig Rebecca R Madon Bénédicte B Massimi Marzia M Matser Vera V Matteoni Rafaele R Mayrhofer Michaela Th MT Ohmann Christian C Panagiotopoulou Maria M Parkinson Helen H Perseil Isabelle I Pfander Claudia C Pieruschka Roland R Raess Michael M Rauber Andreas A Richard Audrey S AS Romano Paolo P Rosato Antonio A Sánchez-Pla Alex A Sansone Susanna-Assunta SA Sarkans Ugis U Serrano-Solano Beatriz B Tang Jing J Tanoli Ziaurrehman Z Tedds Jonathan J Wagener Harald H Weise Martin M Westerhoff Hans V HV Wittner Rudolf R Ewbank Jonathan J Blomberg Niklas N Gribbon Philip P

The EMBO journal 20231115 23

The main goals and challenges for the life science communities in the Open Science framework are to increase reuse and sustainability of data resources, software tools, and workflows, especially in large-scale data-driven research and computational analyses. Here, we present key findings, procedures, effective measures and recommendations for generating and establishing sustainable life science resources based on the collaborative, cross-disciplinary work done within the EOSC-Life (European Open ...[more]

PMID: 37964598

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Project description:BackgroundData stewardship is an essential driver of research and clinical practice. Data collection, storage, access, sharing, and analytics are dependent on the proper and consistent use of data management principles among the investigators. Since 2016, the FAIR (findable, accessible, interoperable, and reusable) guiding principles for research data management have been resonating in scientific communities. Enabling data to be findable, accessible, interoperable, and reusable is currently believed to strengthen data sharing, reduce duplicated efforts, and move toward harmonization of data from heterogeneous unconnected data silos. FAIR initiatives and implementation trends are rising in different facets of scientific domains. It is important to understand the concepts and implementation practices of the FAIR data principles as applied to human health data by studying the flourishing initiatives and implementation lessons relevant to improved health research, particularly for data sharing during the coronavirus pandemic.ObjectiveThis paper aims to conduct a scoping review to identify concepts, approaches, implementation experiences, and lessons learned in FAIR initiatives in the health data domain.MethodsThe Arksey and O'Malley stage-based methodological framework for scoping reviews will be used for this review. PubMed, Web of Science, and Google Scholar will be searched to access relevant primary and grey publications. Articles written in English and published from 2014 onwards with FAIR principle concepts or practices in the health domain will be included. Duplication among the 3 data sources will be removed using a reference management software. The articles will then be exported to a systematic review management software. At least two independent authors will review the eligibility of each article based on defined inclusion and exclusion criteria. A pretested charting tool will be used to extract relevant information from the full-text papers. Qualitative thematic synthesis analysis methods will be employed by coding and developing themes. Themes will be derived from the research questions and contents in the included papers.ResultsThe results will be reported using the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-analyses Extension for Scoping Reviews) reporting guidelines. We anticipate finalizing the manuscript for this work in 2021.ConclusionsWe believe comprehensive information about the FAIR data principles, initiatives, implementation practices, and lessons learned in the FAIRification process in the health domain is paramount to supporting both evidence-based clinical practice and research transparency in the era of big data and open research publishing.International registered report identifier (irrid)PRR1-10.2196/22505.

Dataset Information

"Be sustainable": EOSC-Life recommendations for implementation of FAIR principles in life science data handling.

Publications

"Be sustainable": EOSC-Life recommendations for implementation of FAIR principles in life science data handling.

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