Incentives: Spend five years doing difficult / expensive / dangerous research, gathering data that demonstrates X. The data set is vast, and you can get ten papers out of it, one every six months with some awesome collaboration and possibly tenure.
Do you do that or
publish all your data in the first paper and watch a dozen grad students publish your next nine papers in three weeks ?
Incentives matter yes. Science and data should be free and transparent. But if we pay peanuts and expect the monkeys to appreciate the applause of publication, we need to change our incentive structure.
The reasons AI / ML researchers don't mind publishing the data early is because they already get 500k salaries and equity.
Then there is a huge problem with how we publish Science... Decades ago, sharing all these huge datasets would have been quite difficult if not uneconomical.
But nowadays there is no reason left for not publishing the data and hopefully get academic rewards for that...
I have seen huge amounts of data not being digitized and lost because of this ownership mentality...
It is not a 'mentality' issue. It's a systemic issue. Researchers need to eat too, and it's already difficult enough that few are willing to sacrifice much for the sake of morals.
publish all your data in the first paper and watch a dozen grad students publish your next nine papers in three weeks ?
The way I would expect this to work is, the grad students give you credit for gathering the data, which allows you to share in the prestige associated with all of their projects.
That's like someone releasing a CGI TV series called "Woody and Buzz in the toy store" with exact copies of the digital models. And not expecting Disney to say "we spent 1 BN promoting this brand, we expect a cut / control / story approval / your heart on a plate " [#]
[#] I believe that last one is in actual fact the Disney legal teams' opening gambit in all copyright negotiations. Then the gloves come off.
If graduate students can publish papers based on your data three weeks after they first see your data, then surely you are slacking off if you can only publish one paper every 6 months.
More plausibly, if your data is that apparent,
- you publish your first paper with your data, this takes 6 months from submission to publication
- you submit a paper every three weeks (also with your data) during that 6 months. that totals 8 papers before your article and data hit the press
- after your paper is published, it is 6 weeks before anybody fully gets the data
- during that time you submit your other two papers
- the grad students you mentioned now submit 8 papers, but are forced to cite your work
You now have 10 papers submitted before the competition and have 10-20 papers being submitted that cites your data and work. Total elapsed time = 14 months.
sorry, citing by other people do not have value equal to publish article on first author... and just do experiment should spend very very time and money, e.g., "if I add this compoment to cultured cells" just spend one day and then spend half of year to add component to cell each day and collect results...
You seem to be forgetting that many western groups are very small: 1 senior (often not even tenured) and 1-2 grad students, with not even a lab manager in sight.
In those conditions, going slower than a 50-grad-student chinese lab is not slacking off.
Do you do that or
publish all your data in the first paper and watch a dozen grad students publish your next nine papers in three weeks ?
Incentives matter yes. Science and data should be free and transparent. But if we pay peanuts and expect the monkeys to appreciate the applause of publication, we need to change our incentive structure.
The reasons AI / ML researchers don't mind publishing the data early is because they already get 500k salaries and equity.