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A practical guide to data management and sharing for biomedical laboratory researchers.

Authors :
Fouad K
Vavrek R
Surles-Zeigler MC
Huie JR
Radabaugh HL
Gurkoff GG
Visser U
Grethe JS
Martone ME
Ferguson AR
Gensel JC
Torres-Espin A
Source :
Experimental neurology [Exp Neurol] 2024 Aug; Vol. 378, pp. 114815. Date of Electronic Publication: 2024 May 16.
Publication Year :
2024

Abstract

Effective data management and sharing have become increasingly crucial in biomedical research; however, many laboratory researchers lack the necessary tools and knowledge to address this challenge. This article provides an introductory guide into research data management (RDM), and the importance of FAIR (Findable, Accessible, Interoperable, and Reusable) data-sharing principles for laboratory researchers produced by practicing scientists. We explore the advantages of implementing organized data management strategies and introduce key concepts such as data standards, data documentation, and the distinction between machine and human-readable data formats. Furthermore, we offer practical guidance for creating a data management plan and establishing efficient data workflows within the laboratory setting, suitable for labs of all sizes. This includes an examination of requirements analysis, the development of a data dictionary for routine data elements, the implementation of unique subject identifiers, and the formulation of standard operating procedures (SOPs) for seamless data flow. To aid researchers in implementing these practices, we present a simple organizational system as an illustrative example, which can be tailored to suit individual needs and research requirements. By presenting a user-friendly approach, this guide serves as an introduction to the field of RDM and offers practical tips to help researchers effortlessly meet the common data management and sharing mandates rapidly becoming prevalent in biomedical research.<br />Competing Interests: Declaration of competing interest ARF: Consulting: Santa Clara Valley Medical Center (Biostats Consultant), Neuronasal Inc. (SAB), SpineX Inc. (DSMB), Industry Collaboration (non-financial): DataRobot: AI for Good program. MEM and JG: Co-creator of SciCrunch, a platform to create data and resource sharing communities. ATE: co-owner of YEG scientific, a company producing behavioral research tools for animal models of disease. All other authors have nothing to declare.<br /> (Copyright © 2024. Published by Elsevier Inc.)

Details

Language :
English
ISSN :
1090-2430
Volume :
378
Database :
MEDLINE
Journal :
Experimental neurology
Publication Type :
Academic Journal
Accession number :
38762093
Full Text :
https://doi.org/10.1016/j.expneurol.2024.114815