Here's a very interesting article: Writing in Wired, Jonah Lehrer on the neuroscience of screwing up. An excerpt:
How did the researchers cope with all this unexpected data? How did they deal with so much failure? Dunbar realized that the vast majority of people in the lab followed the same basic strategy. First, they would blame the method. The surprising finding was classified as a mere mistake; perhaps a machine malfunctioned or an enzyme had gone stale. “The scientists were trying to explain away what they didn’t understand,” Dunbar says. “It’s as if they didn’t want to believe it.”
The experiment would then be carefully repeated. Sometimes, the weird blip would disappear, in which case the problem was solved. But the weirdness usually remained, an anomaly that wouldn’t go away.
This is when things get interesting. According to Dunbar, even after scientists had generated their “error” multiple times — it was a consistent inconsistency — they might fail to follow it up. “Given the amount of unexpected data in science, it’s just not feasible to pursue everything,” Dunbar says. “People have to pick and choose what’s interesting and what’s not, but they often choose badly.” And so the result was tossed aside, filed in a quickly forgotten notebook. The scientists had discovered a new fact, but they called it a failure.