This bothered me for a while because I'm not sure what you mean. I can take it three ways.
1. Negative means data that contradicts the popular hypothesis. This is frequently reported very prestigiously, though sometimes care has to be taken depending on just how deeply held the refuted belief is.
2. Negative means data that is highly inconclusive. This data is often non-reported since people continue experiments until they have a story or just drop inquiry. It should still (in some cases) be reported along with the final, telling data but probably isn't.
3. Negative means data that supports already "known" beliefs. Totally "uninteresting" results which just serve to give us the tiniest greater justification to believe what we do. Rarely reported.
I can see (2) but mostly (3) being suitable targets, but you might have a different idea in mind for what negative data is. In the end it sounds like a need to make big advances in meta-analysis in order to have data reported against a more quantified context.
Global, public, and automatic meta-analysis of the state of scientific belief is a hard problem I would love to see solved.