The perils of sharing data

One of the cardinal principles of reproducible research is the sharing of data.  Making data (not just a summary of results) available is just as important for disclosure as the study design, and materials and methods.  Disclosure of the actual data permits others to confirm the analysis of the original authors, or conduct alternative analyses.

Last week's issue of Nature had an editorial outlining the perils of sharing data.  Of greatest concern:  once a data set is published, it is easy for an armchair analyst to take it and run with it, possibly depriving the original investigators the opportunity to publish findings based on a very hard won data set.  Publication of a data set does not have the same status and prestige as publishing scientific findings from the data.

I join with Nature in encouraging discussion and debate within the scientific community to resolve these issues.  The interests of the innovators -- those who design studies and collect the data -- need to be considered before rushing into a mandatory data disclosure policy.  The article talks about the possibility of inviting the original authors to be co-authors on works derived from their data by others.  This is one of many possible options.  The infrastructure of science, including funding, tenure, and promotion policies, needs to change to accommodate and encourage data sharing.  I don't have any answers, and I suspect each field will have to structure a customized solution to suit its own situation.