You are a very busy, very important professor publishing very important work. Do you
a) just publish the code and data along with the paper because you know your work will survive close scrutiny and you have better things to do
b) spend your time handling individual data requests, negotiating over the scope of data shared, and re-describing individual analysis steps that are unclear in the methods
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@jonny "why wouldn't you just dump whatever you have on zenodo and remove an easy avenue for someone to dismiss your work?"
Because the company the data is from will sue you out of a job for... ever.
I know you will not like this answer, but I've been there, done that. Working with *some* insurance and/or finance data will make you jump some hoops no scientist should have or want to jump, but it is my conviction that in some cases there *is* something to learn from the exercise.
@jonny If you want to disregard the papers of mine that follow this reasoning, be my guest.
I will certainly not blame you or anybody and I will have a clear conscience about it.
I have seen scientist code so gnarly, data formatting so chaotic, that you simply cannot [edit: faze*] me. I know how that goes, grad students get no training in any of that. That's my baseline expectation, your code and data simply can't be bad enough that I would care about how bad you think it is - I would rather have an incomprehensible jumble of notebooks and .mat files than nothing at all, and if its in a repo I can pull into, I'll help you clean it up along the way. There is no downside to posting code and data.
*but also you cannot phase me and cause me to shift into a different state of matter or shift my relative synchronization with anything either
If it didn't mean that I would become a pariah and be the end of my career, I would have submitted a paper with absolutely zero experiments or data underlying it where the paper is the sole artifact and you have to just take my word for it years ago just to prove a point. Without code and data, there is no difference between high-concept science fiction with very strong Academic Genre trappings and actual science. Convincingly faking a paper at the figure level is easy, convincingly faking a paper all the way down to the raw data and the commit history in an analysis repo is hard. You are making a claim about how the world works, and it is your responsibility to convince me, not my responsibility to believe you.
@jonny Stay unfazed as long as you can!
@jonny c) ignore all requests
@fancysandwiches
Everyone should have the pubpeer extension installed for these cases
My flow chart for reading a paper is like
Abstract -> Data availability
Why would you pique suspicion in your reader and signal something all may not be as it seems by not publishing the data? Why would anyone believe a paper that doesn't have code & data? You claim to have gotten a bunch of data and done a bunch of things to it in code, and you had to have done that in an organized enough way to yield a paper, so even if its not pretty, why wouldn't you just dump whatever you have on zenodo and remove an easy avenue for someone to dismiss your work?
Edit: clearly, caveats apply like if the data is privacy-sensitive health/PII or data under a strict license where you'd get sued if you post it. That's not what I'm talking about, and its fine if you explain that and post whatever derived data you can ethically and legally post. I'm talking about most primary research in my field which has no such limitations.