Nature Methods has long been an advocate of the value of community experiments (or competitions/challenges) to assess and compare the performance of algorithms and software tools. In 2008 we discussed the value of these competitions and advocated that they also be used to assess the performance of less widely used algorithms such as those used for single particle tracking. Such an experiment for assessing single particle tracking was run in 2012, although the results are still awaiting publication.
Publication of such work has often been confined to more specialized journals but in 2012 Nature Methods started publishing manuscripts emanating from these competitions with a manuscript assessing the performance of gene regulatory network inference methods based on results of one of the DREAM5 challenges.
In recognition of the profound value such challenges provide to the wider scientific community the Nature journals will now be publishing manuscripts describing the results of these challenges under a Creative Commons attribution-noncommercial-share alike unported license. This is the same license we use for publishing first genome papers, standards papers and white papers. The first example of this is an Analysis article published in Nature Methods yesterday describing the results of the first large-scale community-based critical assessment of protein function annotation (CAFA) experiment.
Publication of such community experiments will necessarily be highly selective and likely increasingly so as such challenges become more prevalent, as illustrated by the explosion in the number of Grand Challenges in Medical Image Analysis. But these community experiments provide invaluable information on the performance of methods that are otherwise difficult to objectively compare. We hope that the potential for publication in a Nature journal and the open access provided by a creative commons license helps encourage broader participation in these efforts and visibility of the results.
Update: February 12
We just published another manuscript describing a community experiment. This Analysis article presents the results of the first FlowCAP challenge that assessed the performance of flow cytometry automated analysis methods.