I understand why a “normal” scientist might not want to see this. Imagine: you’re 40, you went from college in 1994 straight to grad school, graduated in 2000 with your PhD, postdoc til 2005, just got an assistant professorship and a piece of a lab to call your own, and your first NIH R01 grant last year. Now suddenly you have to deal with big data everywhere?
But it’s the pundits that are the worst. Like retail politicians and baseball scouts, regular scientists will hop on board fast with using data, as soon as it’s shown to work better than ignoring data. It’s the elite that will change the slowest. They’re the ones with the most to lose with a change to the status quo because they are already in charge.
The journal editors. The old guard. Those who treasure their hypotheses as precious snowflakes never to be shared, unaware that their ideas often exist in a matrix of data that can be generated as a commodity, findable via algorithm, and often disprovable through algorithm. They have the most to lose in the transition. And they clearly see themselves as the shoulders in the Newtonian equation when we transfer to data.