Abstract: Neuroimaging methods such as magnetic resonance imaging (MRI) involve complex data
collection and analysis protocols, which necessitate the establishment of good research
data management (RDM). Despite efforts within the field to address issues related to rigor
and reproducibility, information about the RDM-related practices and perceptions of neuroimaging
researchers remains largely anecdotal. To inform such efforts, we conducted an
online survey of active MRI researchers that covered a range of RDM-related topics. Survey
questions addressed the type(s) of data collected, tools used for data storage, organization,
and analysis, and the degree to which practices are defined and standardized within a
research group. Our results demonstrate that neuroimaging data is acquired in multifarious
forms, transformed and analyzed using a wide variety of software tools, and that RDM practices
and perceptions vary considerably both within and between research groups, with
trainees reporting less consistency than faculty. Ratings of the maturity of RDM practices
from ad-hoc to refined were relatively high during the data collection and analysis phases of
a project and significantly lower during the data sharing phase. Perceptions of emerging
practices including open access publishing and preregistration were largely positive, but
demonstrated little adoption into current practice.
Links below point to open access published paper, dataset, and survey instrument.
History
Publisher Statement
Published in PLoS ONE July 16, 2018
Citation: Borghi JA, Van Gulick AE (2018) Data management and sharing in neuroimaging: Practices and perceptions of MRI researchers. PLoS ONE 13(7): e0200562. https://doi.org/10.1371/journal.pone.0200562