PLoS is letting the inmates run the asylum and this will kill them

The latest round of waccaloonery is the new PLoS policy on Data Access.

I’m also dismayed by two other things of which I’ve heard credible accounts in recent months. First, the head office has started to question authors over their animal use assurance statements. To fail to take the statement of local IACUC oversight as valid because of the research methods and outcomes. On the face of it, this isn’t terrible to be robustly concerned about animal use. However, in the case I am familiar with, they got it embarrassingly wrong. Wrong because any slight familiarity with the published literature would show that the “concern” was misplaced. Wrong because if they are going to try to sidestep the local IACUC and AAALAC and OLAW (and their worldwide equivalents) processes then they are headed down a serious rabbithole of expensive investigation and verification. At the moment this cannot help but be biased- and accusations are going to rain down on the non-English-speaking and non-Western country investigators I can assure you.

The second incident has to do with accusations of self-plagiarism based on the sorts of default Methods statements or Introduction and/or Discussion points that get repeated. Look there are only so many ways to say “and thus we prove a new facet of how the PhysioWhimple nucleus controls Bunny Hopping”. Only so many ways to say “The reason BunnyHopping is important is because…”. Only so many ways to say “We used optogenetic techniques to activate the gertzin neurons in the PhysioWhimple nucleus by….”. This one is particularly salient because it works against the current buzz about replication and reproducibility in science. Right? What is a “replication” if not plagiarism? And in this case, not just the way the Methods are described, the reason for doing the study and the interpretation. No, in this case it is plagiarism of the important part. The science. This is why concepts of what is “plagiarism” in science cannot be aligned with concepts of plagiarism in a bit of humanities text.

These two issues highlight, once again, why it is TERRIBLE for us scientists to let the humanities trained and humanities-blinkered wordsmiths running journals dictate how publication is supposed to work.

Data depository obsession gets us a little closer to home because the psychotics are the Open Access Eleventy waccaloons who, presumably, started out as nice, normal, reasonable scientists.

Unfortunately PLoS has decided to listen to the wild-eyed fanatics and to play in their fantasy realm of paranoid ravings.

This is a shame and will further isolate PLoS’ reputation. It will short circuit the gradual progress they have made in persuading regular, non-waccaloon science folks of the PLoS ONE mission. It will seriously cut down submissions…which is probably a good thing since PLoS ONE continues to suffer from growing pains.

But I think it a horrible loss that their current theological orthodoxy is going to blunt the central good of PLoS ONE, i.e., the assertion that predicting “impact” and “importance” before a manuscript is published is a fool’s errand and inconsistent with the best advance of science.

The first problem with this new policy is that it suggests that everyone should radically change the way they do science, at great cost of personnel time, to address the legitimate sins of the few. The scope of the problem hasn’t even been proven to be significant and we are ALL supposed to devote a lot more of our precious personnel time to data curation. Need I mention that research funds are tight and that personnel time is the most significant cost?

This brings us to the second problem. This Data Access policy requires much additional data curation which will take time. We all handle data in the way that has proved most effective for us in our operations. Other labs have, no doubt, done the same. Our solutions are not the same as people doing very closely the same work. Why? Because the PI thinks differently. The postdocs and techs have different skill sets. Maybe we are interested in sub-analysis of a data set that nobody else worries about. Maybe the proprietary software we use differs and the smoothest way to manipulate data is different. We use different statistical and graphing programs. Software versions change. Some people’s datasets are so large as to challenge the capability of regular-old, desktop computer and storage hardware. Etc, etc, etc ad nauseum.

Third problem- This diversity in data handling results, inevitably, in attempts for data orthodoxy. So we burn a lot of time and effort fighting over that. Who wins? Do we force other labs to look at the damn cumulative records for drug self-administration sessions because some old school behaviorists still exist in our field? Do we insist on individual subjects’ presentations for everything? How do we time bin a behavioral session? Are the standards for dropping subjects the same in every possible experiments. (answer: no) Who annotates the files so that any idiot humanities-major on the editorial staff of PLoS can understand that it is complete?

Fourth problem- I grasp that actual fraud and misleading presentation of data happens. But I also recognize, as the waccaloons do not, that there is a LOT of legitimate difference of opinion on data handling, even within a very old and well established methodological tradition. I also see a lot of will on the part of science denialists to pretend that science is something it cannot be in their nitpicking of the data. There will be efforts to say that the way lab X deals with their, e.g., fear conditioning trials, is not acceptable and they MUST do it the way lab Y does it. Keep in mind that this is never going to be single labs but rather clusters of lab methods traditions. So we’ll have PLoS inserting itself in the role of how experiments are to be conducted and interpreted! That’s fine for post-publication review but to use that as a gatekeeper before publication? Really PLoS ONE? Do you see how this is exactly like preventing publication because two of your three reviewers argue that it is not impactful enough?

This is the reality. Pushes for Data Access will inevitably, in real practice, result in constraints on the very diversity of science that makes it so productive. It will burn a lot of time and effort that could be more profitably applied to conducting and publishing more studies. It addresses a problem that is not clearly established as significant.