Behind every great research project is great data management
Behind every great research project is great data management
Research data management (RDM) is the cornerstone of a successful research project, and yet it often remains an underappreciated art that gets overlooked in the hustle and bustle of everyday project management even when required by funding bodies. If researchers are to strive for reproducible science that adheres to the principles of FAIR, then they need to manage the data associated with their research projects effectively. It is imperative to plan your RDM strategies early on, and setup your project organisation before embarking on the work. There are several different factors to consider: data management plans, data organisation and storage, publishing and sharing your data, ensuring reproducibility and adhering to data standards. Additionally it is important to reflect upon the ethical implications that might need to be planned for, and adverse issues that may need a mitigation strategy. This short article discusses these different areas, noting some best practices and detailing how to incorporate these strategies into your work. Finally, the article ends with a set of top ten tips for effective research data management.
Data ethics, Data management plans, Data organisation, Data sharing, FAIR data, Reproducibility, Research data management
Kanza, Samantha
b73bcf34-3ff8-4691-bd09-aa657dcff420
Knight, Nicola
fbc21e18-095e-4c1a-a4bf-6277debf5c4b
21 January 2022
Kanza, Samantha
b73bcf34-3ff8-4691-bd09-aa657dcff420
Knight, Nicola
fbc21e18-095e-4c1a-a4bf-6277debf5c4b
Kanza, Samantha and Knight, Nicola
(2022)
Behind every great research project is great data management.
BMC Research Notes, 15 (20), [20].
(doi:10.1186/s13104-022-05908-5).
Abstract
Research data management (RDM) is the cornerstone of a successful research project, and yet it often remains an underappreciated art that gets overlooked in the hustle and bustle of everyday project management even when required by funding bodies. If researchers are to strive for reproducible science that adheres to the principles of FAIR, then they need to manage the data associated with their research projects effectively. It is imperative to plan your RDM strategies early on, and setup your project organisation before embarking on the work. There are several different factors to consider: data management plans, data organisation and storage, publishing and sharing your data, ensuring reproducibility and adhering to data standards. Additionally it is important to reflect upon the ethical implications that might need to be planned for, and adverse issues that may need a mitigation strategy. This short article discusses these different areas, noting some best practices and detailing how to incorporate these strategies into your work. Finally, the article ends with a set of top ten tips for effective research data management.
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Published date: 21 January 2022
Additional Information:
Funding Information:
This work was funded by EPSRC through grants EP/S000356/1-AI3SD Network+ (Artificial Intelligence and Augmented Intelligence for Automated Investigations for Scientific Discovery) and EP/S020357/1-PSDS (Physical Sciences Data science Service).
Publisher Copyright:
© 2022, The Author(s).
Keywords:
Data ethics, Data management plans, Data organisation, Data sharing, FAIR data, Reproducibility, Research data management
Identifiers
Local EPrints ID: 454440
URI: http://eprints.soton.ac.uk/id/eprint/454440
ISSN: 1756-0500
PURE UUID: 586d6964-49a6-47e5-a607-bca26b2f6509
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Date deposited: 09 Feb 2022 17:40
Last modified: 06 Jun 2024 02:06
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Author:
Nicola Knight
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