Posts about popular news (old posts, page 4)

Unconditional data sharing, plus peer review transparency, is key to research reproducibility

Only mandatory Open Data, not Gold Open Access, will lead to more honest and more reproducible science. Open Science is these days largely about mandatory publishing in Open Access (OA), regardless of the costs to poorer scientists or the universities which already struggle to pay horrendous subscription fees. Meanwhile, publishers openly declare that the so-called Gold (author-pays) OA will be much more expensive than even current subscription rates, yet wealthy western institutions like the Dutch university network VSNU or the German Max Planck Society do not seem troubled by this at all. They seriously expect the publishing oligopoly of Elsevier, SpringerNature and Wiley to lower the costs for Gold OA later on, out of the goodness of their hearts (as this winter’s invitation-only Berlin12 OA conference suggests).

It bears repeating: how scientists are addressing the 'reproducibility problem'

Recent reports in the Washington Post and the Economist, among others, raise the concern that relatively few scientists' experimental findings can be replicated. This is worrying: replicating an experiment is a main foundation of the scientific method. As scientists, we build on knowledge gained and published by others. We develop new experiments and questions based on the knowledge we gain from those published reports. If those papers are valid, our work is supported and knowledge advances. On the other hand, if published research is not actually valid, if it can’t be replicated, it delivers only an incidental finding, not scientific knowledge.

Cancer Research Is Broken

There’s a replication crisis in biomedicine—and no one even knows how deep it runs. Many science funders share Parker’s antsiness over all the waste of time and money. In February, the White House announced its plan to put $1 billion toward a similar objective—a “Cancer Moonshot” aimed at making research more techy and efficient. But recent studies of the research enterprise reveal a more confounding issue, and one that won’t be solved with bigger grants and increasingly disruptive attitudes. The deeper problem is that much of cancer research in the lab—maybe even most of it—simply can’t be trusted. The data are corrupt. The findings are unstable. The science doesn’t work.