This document discusses strategies for effective data sharing. It recommends that researchers publish data papers to get credit for sharing complex datasets. Data papers describe the acquisition methods and quality of metadata in detail through a peer review process. Several journals are identified as options for publishing data papers. The document also provides tips for organizing and sharing data, such as preparing consent forms in advance, choosing appropriate repositories, and working with anonymized data when possible to improve data sharing.

1. Making data sharing count
Chris Gorgolewski
Department of Psychology
Stanford University

2. Data sharing?

4. Credit where credit’s due
MAKING DATASHARING COUNT

5. Motivation
• Share
your
stat
maps!
vs.
institutions scientists

6. Quality control
• Share
your
stat
maps!
Complex datasets require
elaborate descriptions

7. Solution – data papers
• Authors get recognizable credit for their
work.
– Even smaller contributors such as RAs can be
included.
• Acquisition methods are described in
detail.
• Quality of metadata is being controlled by
peer review.

8. Gorgolewski, Milham, and Margulies, 2013

9. Where to publish data papers?
• Neuroinformatics (Springer)
• GigaScience (BGI, BioMed Central)
• Scientific Data (Nature Publising Group)
• F1000Research (Faculty of 1000)
• Data in Brief (Elsevier)
• Journal of Open Psychology Data (Ubiquity
press)

14. What makes a good data paper?
• Clear and accurate description of the
acquisition protocol.
• Good data organization
• Ease of access to data
• Data quality description
• Fair credit attribution

15. How to improve the impact of your
dataset?
• Provide preprocessed data
• Reach out to your peers
– …and people outside of your field (ML)
• Build a community around the data

16. StudyForrest.org

17. Repositories
• Field specific
– OpenfMRI.org (task based fMRI)
– FCP/INDI (resting state fMRI)
– Neurobiological Image Management System (local;
MRI data)
• Field agnostic
– Stanford Digital Repository (local)
– DataVerse (Harvard)
– Figshare (only small datasets)
– DataDryad (fees may apply)

18. Prepare in advance
• Make sure your consent form includes data
sharing
• Decide which database you want to send
your data to in advance
– Organize your data according to their
requirements
• Work on anonymized data as much as you
can

19. Data sharing small and big
Scientific Data has published as many papers
about datasets that are less than 200MB as
those that are bigger than 200MB

20. Neuroimaging data sharing
hierarchy
Poldrack and Gorgolewski, 2014

21. NeuroVault.org
Gorgolewski, et al., submitted

22. If I haven’t convinced you yet
• Why to share data:
– It’s the ethical thing to do.
– The journal might require it (PLoS).
– Your funders might require it (NIH).
– Track record of data sharing can improve your
chances of getting your next grant.