Should You Share Pre-Published Data?
A Logical Solution?
In the face of significant advantages in digital technology, the pace of academic publishing has remained frustratingly slow. Other than embracing email as a replacement for “snail mail,” the submission and peer review processes remain fundamentally unchanged. Legacy journals continue to dictate the time from submission to possible publication (assuming there is no additional delay to revise and resubmit) and then keep that information behind pay walls that often exceed the budgetary capacity of many institutions.
Open access has re-oriented that model with a pay-for-publication approach and faster time to publication. Results have been mixed, with concerns over questionable peer reviews and predatory journals that appear to be willing to publish anything for a price. However, the model does at least leverage the available technology.
Moving Beyond the Cloud
Until recently, frustrated researchers who were eager to get their research out into the field while waiting for the traditional journal publishing process, were faced with offering files on their own websites as downloadable content from cloud-based servers. Some included explanatory material to ensure that the data was interpreted and incorporated correctly, but others simply took the “take-it-for-what-it-is” approach. As long as the files were clearly labeled as “pre-print” or “pre-publication”, all parties, it was assumed, understood the rules. There had been no third party peer review, and the data should be used accordingly.
The ad hoc system of individual researchers offering pre-print data on their own terms has become more formal with the arrival of pre-print servers such as F1000 Research, PeerJ, Figshare, and ArXiv. Advocates have welcomed a broader accessibility, but critics have expressed concerns about the creation of digital “islands of misfit toys,” where unpublishable material is abandoned. That concern seems extreme when you consider the strict submission process that these server companies have in place to verify funding and authorship of the data before acceptance. The initial employee review is no doubt far less detailed than a peer review, but the servers are clearly no academic dumps.
Consider Your Motivation
When you intend to share pre-publishing/pre-print research data, your expectations should be weighed against your motivation. If all you are looking to do is circumvent the sclerotic traditional publishing cycle and get your pre-print (and pre-peer review) data out there, you can achieve that objective after filling in some paperwork, but you are missing a tremendous opportunity.
If you present your pre-print research data as an open invitation for discussion, critique, and productive feedback, you can gain valuable insights from your fellow researchers, and perhaps even catch errors before they reach the peer review committee and prompt a rejection or “revise and re-submit.”
The spirit of collaborative discussion that pre-print servers encourage does not appear to have reached many of the traditional journal publishing houses. Rather than observing the trend and looking internally to come up with a solution that minimizes the delays in publication, several journals have taken the opposite path and started to refuse to accept manuscripts that have been made available as pre-prints prior to submission. Even though open dialogue over data that everyone understands is likely to have rough edges and flaws, it could catch errors prior to peer review in a formal submission, thus contributing to a faster review process.