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The FAIR guiding principles for data stewardship: fair enough?
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The FAIR guiding principles for research data stewardship (findability, accessibility, interoperability, and reusability) look set to become a cornerstone of research in the life sciences. A critical appraisal of these principles in light of ongoing discussions and developments about data sharing is in order. The FAIR principles point the way forward for facilitating data sharing more systematically-provided that a number of ethical, methodological, and organisational challenges are addressed as well.
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“The Global Indigenous Data Alliance developed the CARE—Collective benefit, Authority to control, Responsibility, and Ethics— Principles as a response to a movement towards FAIR—Findable, Accessible, Interoperable, Reusable—Principles, which are based on universalized access to data (Boeckhout, Zielhuis, & Bredenoord, 2018; GO FAIR, n.d.).”
From Addressing the need for indigenous and decolonized quantitative research methods in Canada (2021) · cites this paper as Boeckhout, Zielhuis, & Bredenoord, 2018
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The FAIR Guiding Principles for scientific data management and stewardship
Wilkinson, M. D., Dumontier, M., Aalbersberg, I. J., Appleton, G., Axton, M., Baak, A., Blomberg, N., Boiten, J.-W., da Silva Santos, L. B., Bourne, P. E., et al. (2016) · Scientific Data · doi:10.1038/sdata.2016.18 · Cited by 18,423
A manifesto for reproducible science
Munafò, M. R., Nosek, B. A., Bishop, D. V. M., Button, K. S., Chambers, C. D., Percie du Sert, N., Simonsohn, U., Wagenmakers, E.-J., Ware, J. J., & Ioannidis, J. P. A. (2017) · Nature Human Behaviour · doi:10.1038/s41562-016-0021 · Cited by 3,397
Bibliometrics: The Leiden Manifesto for Research Metrics
Hicks, D., Wouters, P., Waltman, L., de Rijcke, S., & Rafols, I. (2015) · Nature · doi:10.1038/520429a · Cited by 2,828
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Head, M. L., Holman, L., Lanfear, R., Kahn, A. T., & Jennions, M. D. (2015) · PLOS Biology · doi:10.1371/journal.pbio.1002106 · Cited by 1,388
Dynamic consent: a patient interface for twenty-first century research networks
Kaye, J., Whitley, E. A., Lund, D., Morrison, M., Teare, H., & Melham, K. (2015) · European Journal of Human Genetics · doi:10.1038/ejhg.2014.71 · Cited by 780
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Mons, B., Neylon, C., Velterop, J., Dumontier, M., Santos, L. O. B. D. S., & Wilkinson, M. D. (2017) · Information Services & Use · doi:10.3233/isu-170824 · Cited by 432
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Metadata
- Authors
- Boeckhout, M., Zielhuis, G. A., & Bredenoord, A. L.
- Affiliations
- University Medical Center Utrecht (NL)
- Radboud University Medical Center (NL)
- Corresponding author
- Boeckhout, Martin
- Venue
- European Journal of Human Genetics
- Published
- 2018-05-17
- Volume
- 26
- Issue
- 7
- Pages
- 931-936
- ISSN
- 1018-4813 (ISSN-L)
- 1476-5438
- PMC
- PMC6018669
- OpenAlex
- W2804142383
- Cited by
- 290
- References
- 27
- Citations by year
- 2026: 23 · 2025: 38 · 2024: 45 · 2023: 44 · 2022: 54 · 2021: 48 · 2020: 22 · 2019: 13 · 2018: 3
- FWCI
- 3.96
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- other-oa
- www.springer.com/tdm (tdm)
- Locations
- European Journal of Human Genetics (publishedVersion, other-oa)
- Europe PMC (PubMed Central) (publishedVersion)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- Utrecht University Repository (Utrecht University) (submittedVersion, other-oa)
- Radboud Repository (Radboud University) (submittedVersion)
- Utrecht University Repository (Utrecht University) (submittedVersion)
- Funders
- Nederlandse Organisatie voor Wetenschappelijk Onderzoek (184.033.111)
- Topics
- Physical Sciences › Computer Science › Information Systems › Research Data Management Practices
- Social Sciences › Sociology and Political Science › Data Analysis and Archiving
- Social Sciences › Decision Sciences › Information Systems and Management › Scientific Computing and Data Management
- Keywords
- FAIR principles, research data stewardship, data sharing, discoverability, accessibility, interoperability, reusability, research data management, biology research, data ethics
- MeSH terms
- Biological Science Disciplines, Humans, Research, Databases, Factual, Information Dissemination
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