I won't say any of those are perfect. But there's at least a little more effort toward responsible data analysis in academia. The FDA brings an interesting example to mind. Take a look at how, on paper, drugs suddenly magically became less effective when the FDA started requiring clinical trial pre-registration in 2007.
It's also worth noting that, over the past few decades, most academic fields have been getting increasingly skeptical of the value of correlative research on pre-existing data sets. Even among people who have been extensively trained in how to do it properly. And yet, the vast majority of big data business plans I've seen in practice boil down to "collect a huge data set and then let people do correlative research on it."
It's also worth noting that, over the past few decades, most academic fields have been getting increasingly skeptical of the value of correlative research on pre-existing data sets. Even among people who have been extensively trained in how to do it properly. And yet, the vast majority of big data business plans I've seen in practice boil down to "collect a huge data set and then let people do correlative research on it."