A new model for publishing

Two months ago in a guest editorial for DSWeb (see here), I expressed some dismay that while we have had great inovation in many aspects of our work lives, the current (broken) publication model has remained relatively unchanged.  Now my colleagues at NIH – Dwight Kravitz and Chris Baker have published a stimulating and provocative article (see here) highlighting the many problems with the current situation, especially with the wasteful treadmill of trying to get something into a “high impact” journal, and propose a new model.  Although this will mostly have salience for people in fields that try to publish in journals like Nature and Science, I recommend that anyone who publishes should read the paper and form their own opinion.  Here is mathematician Kreso Josic’s take on the paper.

From my view as a physicist cum mathematician cum biologist, I’ve seen publishing from several perspectives.  The theoretical physics/applied math world seems to have a good system already in place where everyone posts their papers on the arXiv and then publish in an “obvious” physics or math journal like one of the Physical Review or SIAM ones.  These journals are fairly low cost for the authors, if you don’t want colour figures or physical preprints (but not cheap), and they have a nice system of transferring to sister journals if you are rejected automatically so the review process is efficient.  However, publishing in the biology world is more of a nightmare that is well documented by Dwight and Chris in their paper.  Here, getting into a high impact journal like Nature or Science can make or break your career and the chances of getting in are slim.  Authors spend a lot of their time and energy trying to get their work published and if you have little name recognition in a field it is extremely difficult just to get your paper reviewed by the more prestigious journals. Dwight and Chris have some excellent ideas of how to fix this system, which  I think have a lot of merit.  The one thing I would like to see is to make the cost for authors be as low as possible so that it doesn’t impede low funded labs.