I'd also add that primary data collection is risky. You can spend months to years working to get data, only to end up with nothing---not even a null result---if the experiment itself goes south. I lost over a year of my PhD when an animal I had spent ages training fell while playing. A classmate had a virus wipe out her colony of genetically-engineered mice. Using someone else's data obviates these sorts of risks--while doing a better job preparing you for non-academic careers too!
As a result, I think it's not totally nuts for the original data collectors to maybe get some kind of "risk premium." I can imagine a lot of ways to do it, but early/exclusive access to data has been one of them.
A colleague of mine during graduate school who by consensus did everything right, and then just...no one in her cohort had the exposure she was interested in. To this day, no one is sure why.
The answer for a lot of this is to put in the hard work of building relationships with people who collect a lot of primary data, and make sure your work amplifies their work in a way that benefits you both. But that's a lot of effort, hard, and uncertain in its own ways.
I'd also add that primary data collection is risky. You can spend months to years working to get data, only to end up with nothing---not even a null result---if the experiment itself goes south. I lost over a year of my PhD when an animal I had spent ages training fell while playing. A classmate had a virus wipe out her colony of genetically-engineered mice. Using someone else's data obviates these sorts of risks--while doing a better job preparing you for non-academic careers too!
As a result, I think it's not totally nuts for the original data collectors to maybe get some kind of "risk premium." I can imagine a lot of ways to do it, but early/exclusive access to data has been one of them.