Why share data? Lessons learned from the fMRIDC
John Darrell Van Horn1, Michael S Gazzaniga
1Laboratory of Neuro Imaging (LONI), Department of Neurology, David Geffen School of Medicine, University of California Los Angeles, 635 Charles E. Young Drive SW, Suite 225 Los Angeles, CA 90095-7334, USA. jvanhorn@loni.ucla.edu
The fMRI Data Center (fMRIDC) was developed to address underdeveloped data sharing in cognitive neuroscience. This initiative gathered and shared functional magnetic resonance imaging (fMRI) data, enabling new research and informing future data archiving strategies.
Area of Science:
- Cognitive Neuroscience
- Neuroimaging
- Data Science
Background:
- Neuroimaging and cognitive neuroscience have advanced collaboratively.
- Despite progress, data sharing practices in these fields are not well-established.
- Open sharing of neuroimaging data is crucial for scientific reproducibility and advancement.
Purpose of the Study:
- To describe the development and operation of the fMRI Data Center (fMRIDC).
- To highlight the importance of curating and openly sharing functional magnetic resonance imaging (fMRI) data.
- To discuss considerations for successful neuroimaging data archiving and dissemination.
Main Methods:
- Established the fMRI Data Center (fMRIDC) to collect and curate data from published fMRI brain activation studies.
- Documented the operational aspects and sociological reactions to the data sharing initiative.
- Provided examples of studies utilizing the archived fMRIDC data.
Main Results:
- The fMRIDC successfully gathered and shared complete datasets from numerous fMRI studies.
- Archived data facilitated novel research, demonstrating the value of open data access.
- Sociological reactions to data sharing varied, highlighting cultural challenges.
Conclusions:
- Successful neuroimaging databasing requires careful consideration of data curation and accessibility.
- Open data sharing is essential for the continued growth and integrity of cognitive neuroscience research.
- The fMRIDC serves as a model for future efforts in archiving and disseminating valuable neuroimaging data.
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