Third CHALLENGE: Publication bias

This is the third challenge at the DDA Winter School for postdocs. Studies with successfully proven hypotheses are considered worthy of publication and are greatly represented in scientific literature (85% of data papers on pubmed are ‘positive-data-biased’; Mlinaric et al., 2017). This publication trend is in stark contrast to unexpected results that ‘failed’ to prove the hypothesis, delivering so called ‘negative data’. Negative or less-than-dramatic findings are currently viewed as boring for editors, a costly waste of resources, and a culprit of ‘ruining one’s career’, collectively causing an enormous demotivation among junior scientists. Under-reporting and filing away of negative results significantly impacts science and research culture by skewing the view of reality, as well as by affecting our career paths. Surely, pursuing risky hypotheses costs resources and time; however, would publishing negative data help the scientific community increase data reproducibility and optimize the current measures of our productivity?