Two Dutch biomedical researchers discuss how they are trying to move their institution away from mere quantity of research and citations, and toward real clinical impact: “Do our measures of academic success hurt science?”. They begin their essay with a scenario that reminds me of human evolution research:
A Ph.D. student wants to submit his research to a journal that requires sharing the raw data for each paper with readers. His supervisors, however, hope to extract more articles from the dataset before making it public. The researcher is forced to postpone the publication of his findings, withholding potentially valuable knowledge from peers and clinicians and keeping useful data from other researchers.
I agree with much of what they say in this essay. But I think their opening scenario doesn’t really express a trade-off they are trying to illustrate between an artificial measure of “impact” and real impact.
What we keep finding in human evolution research is that sharing the data leads to higher impact. Papers are published faster, they are cited more widely, and they lead to career advancement for the authors.
It is true that some scientists try to keep datasets private so that other researchers cannot replicate their work. But that is counterproductive to their own research, not only to the field. Researchers who are publishing slowly, not distributing data in a way that can be inspected and used, are not achieving publications, citations, or “impact” even in the artificial, publication-oriented sense.
Using open approaches is not just the way to advance science and its impact on the public, it is also the way to advance careers. There is no trade-off here, not that I’ve experienced at least.