Daily life in the Open Biologist’s second job, as a Data Curator

Livia C.T. Scorza, Tomasz Zieliński, Irina Kalita, Alessia Lepore, Meriem El Karoui and Andrew Millar
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Livia C.T. Scorza: The University of Edinburgh
Tomasz Zieliński: The University of Edinburgh
Irina Kalita: The University of Edinburgh
Alessia Lepore: The University of Edinburgh, LOB - Laboratoire d'Optique et Biosciences - X - École polytechnique - IP Paris - Institut Polytechnique de Paris - INSERM - Institut National de la Santé et de la Recherche Médicale - CNRS - Centre National de la Recherche Scientifique
Meriem El Karoui: The University of Edinburgh, LBPA - Laboratoire de biologie et pharmacologie appliquée - Université Paris-Saclay - CNRS - Centre National de la Recherche Scientifique - ENS Paris Saclay - Ecole Normale Supérieure Paris-Saclay
Andrew Millar: The University of Edinburgh

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Abstract: Background: Data reusability is the driving force of the research data life cycle. However, implementing strategies to generate reusable data from the data creation to the sharing stages is still a significant challenge. Even when datasets supporting a study are publicly shared, the outputs are often incomplete and/or not reusable. The FAIR (Findable, Accessible, Interoperable, Reusable) principles were published as a general guidance to promote data reusability in research, but the practical implementation of FAIR principles in research groups is still falling behind. In biology, the lack of standard practices for a large diversity of data types, data storage and preservation issues, and the lack of familiarity among researchers are some of the main impeding factors to achieve FAIR data. Past literature describes biological curation from the perspective of data resources that aggregate data, often from publications. Methods: Our team works alongside data-generating, experimental researchers so our perspective aligns with publication authors rather than aggregators. We detail the processes for organizing datasets for publication, showcasing practical examples from data curation to data sharing. We also recommend strategies, tools and web resources to maximize data reusability, while maintaining research productivity. Conclusion: We propose a simple approach to address research data management challenges for experimentalists, designed to promote FAIR data sharing. This strategy not only simplifies data management, but also enhances data visibility, recognition and impact, ultimately benefiting the entire scientific community

Keywords: Open science; FAIR; data sharing; data curation; repositories; reproducibility; accessibility; biological data; datasets; metadata (search for similar items in EconPapers)
Date: 2024
Note: View the original document on HAL open archive server: https://cnrs.hal.science/hal-05252424v1
References: View references in EconPapers View complete reference list from CitEc
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Published in Wellcome Open Research, 2024, 9, pp.523. ⟨10.12688/wellcomeopenres.22899.1⟩

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Persistent link: https://EconPapers.repec.org/RePEc:hal:journl:hal-05252424

DOI: 10.12688/wellcomeopenres.22899.1

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