In response to “an extraordinary outpouring of discussions on open data and its place in scientific publishing” following a February 24 announcement about a new data policy at PLOS, the publisher has apologized and corrected the record.
The new policy — which was actually first announced on January 23, as we noted here — had led to criticism at the DrugMonkey blog, and a February 26 clarification seemed to do little to convince another critic. (Not all disagreed with the policy, however.)
In particular, there were objections to a section that began with
Data are any and all of the digital materials that are collected and analyzed in the pursuit of scientific advances.
We apologize for causing confusion
In the previous post, and also on our site for PLOS ONE Academic Editors, an attempt to simplify our policy did not represent the policy correctly and we sincerely apologize for that and for the confusion it has caused. We are today correcting that post and hoping it provides the clarity many have been seeking. If it doesn’t we’d ask you once again to let us know – here on the blog, by email at firstname.lastname@example.org, and via all the usual channels.
Two key things to summarize about the policy are:
- The policy does not aim to say anything new about what data types, forms and amounts should be shared.
- The policy does aim to make transparent where the data can be found, and says that it shouldn’t be just on the authors’ own hard drive.
We have struck out the paragraph in the original PLOS ONE blog post headed “What do we mean by data”, as we think it led to much of the confusion. Instead we offer this guidance to authors planning to submit to a PLOS journal.
The post continues with an example of how the policy would work. Here’s the struck-through paragraph:
What do we mean by data?
“Data are any and all of the digital materials that are collected and analyzed in the pursuit of scientific advances.” Examples could include spreadsheets of original measurements (of cells, of fluorescent intensity, of respiratory volume), large datasets such as next-generation sequence reads, verbatim responses from qualitative studies, software code, or even image files used to create figures. Data should be in the form in which it was originally collected, before summarizing, analyzing or reporting.
The move looks like the right thing to do. The problem seemed to have stemmed from how the policy was communicated, rather than what PLOS actually wanted to accomplish, which is better data sharing. In a time when reproducibility is a growing concern, the latter is a must.
We note that this is not the first time PLOS has run afoul of scientists after overstating — or at least not stating carefully — a new policy. Something similar happened in 2012 when the publisher tried to clarify its retraction policy. That led to a similar walk-back.