One of our favourite upgrades is how each of more than 24,000 journals are featured and displayed. Now it is possible for anyone to see what journals exist on our platform and how many articles are tracked for each one of them. That’s the first step. Try searching for your favourite journal, or even a journal you work for, and seeing what we have for it.
Last week, we kicked off a series interviewing some of the top ‘open scientists’ by interviewing Dr. Joanne Kamens of Addgene, and had a look at some of the great work she’d been doing in promoting a culture of data sharing, and equal opportunity for researchers. Today, we’ve got something completely different, with Daniel Shanahan of BioMed Central who recently published a really cool PeerJ paper on auto-correlation and the impact factor.
Hi Daniel! To start things off, can you tell us a bit about your background?
I completed a Master’s degree in Experimental and Theoretical Physics at University of Cambridge, but must admit I did my Master’s more to have an extra year to play rugby for the university, rather than a love of micro-colloidal particles and electron lasers. I have always loved science though and found my way into STM publishing, albeit from a slightly less than traditional route.
One main aspect of open peer review is that referee reports are made publicly available after the peer review process. The theory underlying this is that peer review becomes a supportive and collaborative process, viewed more as an ongoing dialogue between groups of scientists to progressively asses the quality of research. Furthermore, it opens up the reviews themselves to analysis and inspection, which adds an additional layer of quality control into the review process.
This co-operative and interactive mode of peer review, whereby it is treated as a conversation rather than a selection system, has been shown to be highly beneficial to researchers and authors. A study in 2011 found that when an open review system was implemented, it led to increasing co-operation between referees and authors as well as an increase in the accuracy of reviews and overall decrease of errors throughout the review process. Ultimately, it is this process which decides whether research is suitable or ready for publication. A recent study has even shown that the transparency of the peer review process can be used to predict the quality of published research. As far as we are aware, there are almost no drawbacks, documented or otherwise, to making referee reports openly available. What we gain by publishing reviews is the time, effort, knowledge exchange, and context of an enormous amount of currently secretive and largely wasted dialogue, which could also save around 15 million hours per year of otherwise lost work by researchers.