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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.
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Livia Scorza
University of Edinburgh
T. Zieliński
Poznań University of Economics and Business
Irina Kalita
Loewe Center for Synthetic Microbiology
Wellcome Open Research
Centre National de la Recherche Scientifique
University of Edinburgh
École Polytechnique
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Scorza et al. (Thu,) studied this question.
synapsesocial.com/papers/68e58b97b6db643587526e26 — DOI: https://doi.org/10.12688/wellcomeopenres.22899.1
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