The argument against this, and I make this as a jaded and struggling graduate student so accept that bias, is that there is no acceptable outlet for negative results. There is also no acceptable outlet for those who consistently produce negative results and so, as I'm sure everyone understands, there is tremendous pressure to produce positive and interesting results. We hear about the times that this is forced due to manipulation and falsification and this is never okay, but there are a great many times where it falls into a nebulous gray area. We double and triple check our code, verify simulation results, and run down the checklists but that never guarantees that we do not have such "excel column errors".

If data and code are open this is fantastic for science and progress because errors do not replicate and permute but it can be terrible for individual scientists and graduate students. As always, it comes down to money. If we are forced to correct or even worse retract a scientific publication, the community (both local and worldwide) bares down on you like a knife. The stakes are so high that not only is falsification lethal, in many cases honest mistakes can be lethal as well. Conversely one cannot take eternity flipping every stone to bulletproof every possible single problem and it can be very hard to identify which stones to check!

This is not a defense of closed work and closed data, but it's a realization that opening data and code is not a simple and straightforward process. There are severe and deeply embedded cultural problems that make post-publication sharing difficult.