In a Radar blog post, O'Reilly's Mike Loukides discusses the new tools and platforms (including Riffyn) which are seeking to update scientific methodology for the digital age and in doing so address the reproducibility problem.
Loukides notes the need to capture process details in a more structured way:
The best way to record the protocols isn’t by scribbling in lab notebooks (or their virtual equivalents)". Instead we need tools that will let us describe the process precisely and completely, in a standardized language that is meaningful in different contexts, different labs.
He also points out that we can and should be capturing, rather than discarding, far more of the data associated with an experiment:
We’ve automated some of the data collection, but we still don’t collect all (or even most) of the data that’s potentially available: intermediate results from each step, calibration data from each piece of equipment, detailed descriptions of the process, and the configuration of every piece of equipment. [...] Few scientists would consider the test tubes used, the pipettes, and so on, as part of the experimental data. That must change if we’re going to solve our problems with reproducibility.