Recently there was an issue of Science (December 2, 2011, Volume: 334, Issue: 6060) with a special section focusing on data replication and reproducibility in the sciences. It is about time that the big fish put this topic on the table.
Off-the-cuff, while Peng’s perspective on Reproducible Research in Computational Science is of particular interest to me the other accompanying perspectives are quite eye-opening to someone not doing empirical research. For example Tomasello and Call’s perspective on Methodological Challenges in the Study of Primate Cognition and Ryan’s Replication in Field Biology: The Case of the Frog-Eating Bat discuss challenges facing field research that I have never really spend much time thinking about (and which, if possible, gives me even more respect for people doing field work). Or as Ryan succinctly summarizes it
“Studies conducted in the field offer unique opportunities to observe nature, but achieving true replication under natural conditions is challenging.”
In light of this it is rather ironic that papers based on empirical work (field work in particular) often contain details that may be very difficult or impossible to reproduce while papers based on computational research typically omit details that would be straight forward to reproduce (e.g. computer code, random number generator seeds, etc.).
HT: Steph.
This is from the “Mario’s Entangled Bank” blog ( http://pineda-krch.com ) of Mario Pineda-Krch, a theoretical biologist at the University of Alberta.
And another “big fish” broaches the subject: http://www.nature.com/nature/journal/v482/n7386/full/nature10836.html?WT.ec_id=NATURE-20120223