I have noticed that there are two major ways of thinking when it comes to exploring unknown problems (that is, scientific discovery) - (a) one is to gather as much data as possible by doing measurements and descriptions of the phenomenon at question, until its mechanisms start to reveal themselves and (b) another is to try to generate as many hypothetical models as possible and test which one would prove to be actually working in reality.
Let me give you an example. Let's go back in time, when the function of kidneys, let's say, had not been clear to medical and biological researchers. One approach would had been to get speciments from dissections and describe them in as deep detail, as possible. Another would be to try to guess the big picture at ones, by generating numerous hypotheses about the function of those organs and they checking experimentally which one holds true.
I have read a book about the discovery of DNA and as far as I can remember, they had researchers using the two approaches, and those using the model generating one finally "guessed" the helix structure of DNA.
My questions is:
- are there any specific terms for those two approaches of thinking?
- is there any research suggesting that one is more productive than the other?