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Seven common objections to data sharing
1. Data Archiving and Networked Services
DANS is an institute of KNAW en NWO
Data Archiving and Networked Services
Seven common objections to data
sharing… and how to overcome them
Peter Doorn, director DANS
2. To share or not to share...
What is in it for the researcher? Benefits:
• Visibility
• Citation: researchers who share data
are cited more often than others
Piwowar, H., & Vision, T. J. (2013). Data reuse and the open data
citation advantage. PeerJ PrePrints, 1:e1.
doi:10.7287/peerj.preprints.1
”[…] we find a robust citation benefit from open data […]
there is a direct effect of third-party data reuse that persists for years […]
a substantial fraction of archived datasets are reused, and the intensity of
dataset reuse has been steadily increasing since 2003."
3. Seven common objections to data sharing...
and how to overcome them (1-4)
Why not share? How to overcome?
1. No one else can understand the
complexity of my data
Document the data, describing the
conditions of the research
2. If someone else analyzes my
data, they may come up with a
different answer disproving my
perspective
By considering different perspectives on
the same data set, we will come closer to
the “right” answer
3. Someone else may find
something new in my data that I
did not see
Finding something new in an existing
data set will increase the return on
investment in the data collection
4. I have not finished analyzing my
data, and I will make it available
once my analysis is complete
Research is a never-ending story… A
published paper suggests that the data
have been substantially analyzed; thus
sharing at this point seems appropriate
Adapted from Stephen H. Koslow (2000)
4. Seven common objections to data sharing...
and how to overcome them (5-7)
Why not share? How to overcome?
5. It is my data that I worked very
hard to collect, and no one else
has the right to it.
Publicly funded data should be publicly
available. A publication implies that
research results are to be shared.
Reviewers and readers should have
access to the primary data on which
publications are based.
6. I cannot trust or understand the
data produced in another
laboratory
If this is not possible, how can we trust
the scientific literature? This is the mirror
image of 1.
7. Documenting my data for
others costs me time for which I
get no credit
You will be rewarded by more citations;
your work will be more visible and your
data will be cited as well.
Adapted from Stephen H. Koslow (2000), ‘Should the neuroscience community
make a paradigm shift to sharing primary data?’, Nature America Inc., 3:9
(September), p. 863-865.
5. Data Archiving and Networked Services
DANS is an institute of KNAW en NWO
Thanks for viewing!
www.dans.knaw.nl
www.narcis.nl
peter.doorn@dans.knaw.nl
twitter: @pkdoorn
http://youtu.be/HJbo-OAaJ1I
The work DANS does
summarized in a 4 minute
video, introduced by
Neelie Kroes
![To share or not to share...
What is in it for the researcher? Benefits:
• Visibility
• Citation: researchers who share data
are cited more often than others
Piwowar, H., & Vision, T. J. (2013). Data reuse and the open data
citation advantage. PeerJ PrePrints, 1:e1.
doi:10.7287/peerj.preprints.1
”[…] we find a robust citation benefit from open data […]
there is a direct effect of third-party data reuse that persists for years […]
a substantial fraction of archived datasets are reused, and the intensity of
dataset reuse has been steadily increasing since 2003."](data:image/gif;base64,R0lGODlhAQABAIAAAAAAAP///yH5BAEAAAAALAAAAAABAAEAAAIBRAA7)