A review of journal policies for sharing research data Heather Piwowar, Wendy Chapman Department of Biomedical Informatics University of Pittsburgh ELPUB 2008
Jan 27, 2015
A review of journal policies for sharing research data
Heather Piwowar, Wendy Chapman
Department of Biomedical Informatics University of Pittsburgh
ELPUB 2008
http://www.flickr.com/photos/cogdog/123072/
“An inherent principle of publication is that others should be able to replicate and build upon the authors' published claims. Therefore, a condition of publication in a Nature journal is that authors are required to make materials, data and associated protocols available in a publicly accessible database …” http://www.nature.com/authors/editorial_policies/availability.html
http://www.nature.com/nature/journal/v453/n7197/index.html
Benefits for journal – allows publications to be useful (and cited) in
additional ways – demonstrates commitment to quality research – discourages fraud
Drawbacks for journal – might decrease submissions – administrative burden
Prior work in this area
• McCain: 16% of 850 science+engineering journals have a policy about sharing RRI
• NAS: 53% of 38 life sciences journals
But these reviews are dated, consider a variety of resources, and don’t correlate policy to behaviour
McCain. Science Communication, Vol. 16, No. 4. (1 June 1995), pp. 403-431 NAS. Sharing Publication-Related Data and Materials. (2003), p. 33
• In this study, we looked at the data-sharing policies within Instruction to Author statements of 70 journals for a specific data type
• We look at themes within the statements
• We correlate the strength of the policy statements to the frequency with which the authors actually share their data
Data type: gene expression microarrays
http://en.wikipedia.org/wiki/Image:Heatmap.png
Three types of results
1. Themes within data sharing policies
2. Relative policy strength
3. Observed data sharing behaviour
Themes within data sharing policies • statements of policy motivation • datatype-specific policies • requested vs. required • data location • data format • data completeness • timeliness of sharing • consequences for not sharing • exceptions
Relative policy strength
• No applicable policy (43%)
• Weak policy (24%) – should, recommend, request – must, but without database accession number
• Strong policy (33%) – must, required, condition of publication – requires database accession number
High-impact journals tend to have
a strong data-sharing policy
What journal characteristics are associated with having a data-sharing policy?
Journal has a data sharing policy?
Impact Factor
Open Access?
Society Publisher?
Subdisciplines…
What journal characteristics are associated with having a data-sharing policy?
Journal has a data sharing policy?
Impact Factor
Open Access?
Society Publisher?
• Biochemistry &Molecular Biology • Oncology
Observed Sharing Behaviour
For each of the 70 journals, we measured % of papers with links to database
submission entries
% of submission links is our proxy for % of publications with shared data
Articles published in journals with a strong data-sharing
policy are more likely to have publicly available datasets
What journal characteristics are associated with data sharing behaviour?
% of articles with shared data
Impact Factor
Open Access?
Society Publisher?
Subdisciplines…
Having a data-sharing policy?
What journal characteristics are associated with data sharing behaviour?
% of articles with shared data
Impact Factor
Open Access?
Society Publisher?
• Genetics & Heredity • Multidisciplinary Sciences
Having a data-sharing policy?
Limitation
• Association does not imply causation
Take-home message
• Many, but not all, journals require sharing of microarray data. Very diverse policies.
• Stronger data-sharing policies: – high-impact journals – open-access journals – published by association
• Policy strength correlates with behaviour • Policies would benefit from
improved clarity, scope, and accountability
Future work
• Who shares data? • Who reuses data?
Hopefully the answers will inform our decisions about where to focus our energy to improve
policies, tools, and incentives
Thank you
Advisor: Dr. Wendy Chapman Funding: NLM for training grant, and
Pitt DBMI department for travel grant
My shared data: www.dbmi.pitt.edu/piwowar Share your research data too!
“Does anyone want your data?
That’s hard to predict […] After all, no one ever knocked on your door asking to buy those figurines collecting dust in your cabinet before you listed them on eBay.
Your data, too, may simply be awaiting an effective matchmaker.”
Got data? Nature Neuroscience 10, 931 (2007)