I still think the answer is not in any particular standard in any particular field, rather it's outputting the final, worked datasets. Making the numbers thems

I still think the answer is not in any particular standard in any particular field, rather it's outputting the final, worked datasets. Making the numbers themselves available and usable to the 'reader' or scientist following up will immediately clear up issues of reproducibility or not meeting statistical thresholds. If I see the same data, run it through my own processes and it looks like noise I'm likely to discount the results moving forward. There's nothing inherently wrong with saying 'look, I did this once, and this is what I saw'. And many times it's useful. It's less useful, but still reasonable in certain circumstances to say, 'look, I did this a hundred times and I saw this once'. There are occasions when the experiment cannot reasonably have more than a statistically insignificant 'n' - but it still might be useful to see what happens. What is not reasonable is to say, 'this is what I (sometimes) see always (trust me)' and hide your data behind a 'representative' jpg and a 'statistically significant' p-value. As I scientist who has worked with both rich, and poor datasets from standard and invented datatypes, I'd just say, "let me see the data".