I've Found (and Uploaded) 10,000 Ways that Won't Work
While this data might not be generated with the same precision as publication-grade data, it may serve as a valuable early-warning system for results from confounding variables. Requiring cataloguing of "failed" trials would also provide some resistance against publication bias. By adding incentives for sharing experimental data and also metadata ("left the plates out in the hot sun" or "had the crazy undergrad do that experiment") we can recapture all of that experimental data acquired (and discarded) in the pursuit of those positive, published results.
NIH is the one handing out the money. It has both the power to reward experiments in reproducibility and also the ability to dictate what happens to the data produced.
Just as steam cogeneration allows us to capture energy that would otherwise be dissipated, full and open reporting of results allows capture of data that would be lost to the filing cabinets. Whether it's heat or data, an investment in infrastructure is necessary to mediate that capture.
For the experiments, that would be a versatile and accountable database where labs can easily upload the raw data acquired on the path to publication. Everything (margin scrawl included) would be acceptable, encouraged, but not necessarily required. The data would be linked to the relevant subjects by a couple of tags, many of them automatically filled-in.
For instance, if you were to upload a Western blot from a knockdown experiment, the database upload tool would remember what cell line you said you were using, which lab, and which location. It's more than an open notebook; imagine trying to find three labs' experiences with the same protein, when they all made their own plasmids to express it. The same thing could be called pAH007 or pBjh1601CK-znr104b depending on the lab. Maybe one lab had a mutation in their plasmid and didn't notice; how could you find a consensus? It's also more than a new journal just for errors, because its links run deeper than citations.
So how do you build such a thing? I can think of only one organization that can: the NIH's National Library of Medicine, or really its subdivision NCBI. NCBI brought us PubMed, Entrez, and Genbank. Perhaps it's time to ask them to finish the job. The task of building such a database—to address the myriad forms of research data, file formats, and link everything together—is a Herculean effort. But the alternative—i.e., the status quo—is a Sisyphean ordeal.