F1000Research Joins Open Access Revolution

Contributor
Graduate Division

Science is fundamentally about increasing our knowledge of the world, but with increasing competition for funding and academic positions, the pressure to publish enormous, high-impact articles in prestigious journals is becoming counter-productive. How can we efficiently disseminate scientific information as publication requirements become ever more rigorous?

This is one of the key questions tackled by supporters of Open Access (OA). Open Access journals such as PLOS (originally known as the Public Library of Science), offer free and unrestricted access to the articles they publish, and the EMBO (European Molecular Biology Organization) Journal even publishes peer reviews of published papers.

F1000Research may become one of the most revolutionary yet, offering immediate publication and transparent post-publication peer review.  You may have heard of F1000 Prime, a directory of previously published articles on the life sciences with recommendations by experts in the field, many of whom are UCSF scientists.

F1000 Research also applies post-publication metrics to assess the quality of research, but it goes one step further, as a journal rather than a database.

Whereas most scientific journals publish one final version of a given paper, F1000 Research publishes every step of the research up to final acceptance, including reviewers’ comments, all revisions and even negative data.

Despite its deviations from the traditional model of publishing, F1000Research strives to uphold a high standard for the science it approves.  Its International Advisory Panel includes renowned scientists including top UCSF researchers such as Paul Volberding, Warner Greene and Bruce Miller, and more than 1,000 global experts sit on its Editorial Board.

F1000Research officially launched last month, after a six-month testing phase. Submissions have come from around the globe. Synapse had an opportunity recently to conduct a phone interview with Rebecca Lawrence, publisher at F1000Research.  Lawrence holds a PhD in Pharmacology from the University of Nottingham and has worked for other publishers, including Elsevier, for seven years.  Previously, she oversaw the launch of F1000 Posters, a repository of data gathered at scientific conferences.

What existing issues in science publishing prompted the launch of F1000Research?

Lawrence: F1000 founder Vitek Tracz wanted to tackle the outstanding issues of peer review — the huge delay before publication, problems with anonymous and potentially biased reviewers, and [the loss of] data. 

We started with F1000Posters, based on the observation that half the data presented at a conference never gets published. F1000Research is the formal publication of that otherwise lost data.

What makes F1000Research unique among supporters of OA?

Lawrence: (1) Peer review is after publication and completely transparent. We do an initial check to make sue an article is original, readable science with all the data included, and then it goes to four [non-anonymous] peer reviewers. Normally, peer review is anonymous and done before publication.

(2) Speed.  Most journals take at least two months, but we can publish a full PDF in under a week, and our peer review process is about two weeks.

If peer review occurs post-publication, are papers still available if they’re not approved?

Lawrence: Yes, and we include the referee status in the title (for example: Paper title. Not approved 1) and do not send these articles to Pubmed. I want to point out that “not approved” means it is bad science and should not be published.  Most articles would get published in some journal [even if they wouldn’t be approved here], so this helps prevent the propagation of poor science.

Why should researchers publish with F1000Research as opposed to submitting their work to a traditional high-impact journal?

Lawrence: The key for us is speed.  If you have a very high-impact article, you might want to get your paper out before your competitors and show that you did this first.  Also, because we publish more [of your data], you’re likely to get more citations and improve visibility. 

How do you think this will impact how science is conducted and published?

Lawrence:  I’m hoping it will speed science up.  It’s quicker to get findings out, so then people can see the data, actually replicate it, and work on the next step collaboratively.  It would also get people to publish smaller findings more often so we can add to the work as it’s done.  Writing papers [has become] such an enormous task, and it takes much longer than if researchers just wrote as they went along.