[donaldc]

One problem is that often the data is highly valued -- the team may have spent years building it.

That was clearly not the case with the flawed paper this OP is concerning itself with. So, not a valid excuse in this case.

At any rate, the team should learn to write papers as they build up the data set. That way they always have a little more data than anyone else working with it. Because without release of the data on which a given paper is based, there's no way to know if the paper is actually valid.

[danielweber]

A good data set can have incorrect analysis written about it. "Clearly not the case" doesn't apply.