Data sharing 101: a principled approach to transparency in (psychological) science by Olivier Klein (ULB)

1. (DATA) SHARING 101:A PRINCIPLED
APPROACHTOTRANSPARENCY IN
(PSYCHOLOGICAL) SCIENCE
Olivier Klein, Université Libre de Bruxelles
oklein@ulb.ac.be
Open science Webinar, October 24, 2018
@olivier_klein

2. https://www.collabra.org/
articles/10.1525/collabra.158/

3. WHY SHARE DATA?

4. • Trust
• Reusability
• Data loss
• Selfishness
Reasons for engaging in transparent research practices

5. INCREASES IN…
• Citations
• Media Attention
• Job Opportunities
• Funding
• Potential collaborators
McKiernan, E. C., Bourne, P. E., Brown, C.T., Buck, S., Kenall,A., Lin, J., et al. (2016). How open
science helps researchers succeed. eLife, 5, 1–19.

6. Piwowar, H.A., Day, R. S., & Fridsma, D. B. (2007).
Sharing detailed research data is associated with
increased citation rate. PloS one, 2(3), e308.
Piwowar, H.A., &Vision,T. J. (2013). Data reuse and the
open data citation advantage. PeerJ, 1, e175.

7. Your closest collaborator is you 6
month ago but you don’t respond to
emails

8. WHY NOT?
Houtkoop, B. L., Chambers, C., Macleod, M.,
Bishop, D.V., Nichols,T. E., & Wagenmakers, E. J.
(2018). Data Sharing in Psychology:A Survey
on Barriers and Preconditions. Advances in
Methods and Practices in Psychological
Science, 1(1), 70-85.

9. WHY NOT

10. WHY NOT

11. WHY NOT

12. HOWTO SHARE?

13. Formulation of
Data Management
plan
Preregistration:
Hypotheses / Materials
placed on public
repository (with optional
access control)
Full accessibility of
preregistration, scripts
and data
Preregistered
information + Script +
Data on Public
Repository (accessible at least
to editors and reviewers & cited in
the paper)
Planning
Data
Collection
Paper Submission
Paper Publication
Ethical Approval
A transparent workflow

14. WHATTO SHARE
• Hypotheses
• Ethics forms
• Detailed Study protocol
• Materials
• Report / Article
• Data

15. DATA
Raw Processed
Meta-data
Transformation
Code / Analysis
procedures
Analyses

16. META-DATA
Kai Horstmann,
Humboldt University
Source: https://osf.io/azppp/

17. WHERETO STOREYOUR
STUFF ?
OSF.io

25. • Use stable identifiers
• Allow licensing
• Control access
• Have some persistence
• Respect local legislation
• Have large storage
capacity
• Ethical financial model
• Track re-use
• Be easy to use
• Yes (URLs or DOI)
• Choose your license
• Private vs. Public Project
• 50 year preservation funds.
• Compliance With GDPR
• Max 5GB per file but adds-ons.
• COS
• Stats
• Demonstration
A repository should……

27. @olivier_klein oklein@ulb.ac.be
Slides here: osf.io/
v5nzf