Is there a term for the fact that research is done only with the means available?

Question

It could also be placed on https://english.stackexchange.com/, but I feel it is more suitable here. So: Is there a term for the (trivial) fact that research is done only with the means available?

For example a mineralogist won't study stones from the Moon if s/he doesn't have one. More specifically to my case: I am looking for a term that describes the problem of researchers who want to do something, but cannot do it by hand and not even by computers due to lack of suitable software/hardware (e.g. inverting very large matrices); and as a consequence they don't do it. (And in a verly last step, I want to find out whether there is research done about the consequences on science due to lacking software/hardware.) Is it simply called "lack of technology" or something similar?

Answer 1

"practical limitations" could cover just about any type of situation where you don't have the means to do what you'd ideally like to do.

"resource limitations" could cover not having enough time, money, or trained people to do the work, not having the right equipment, and a lot of other things.

"equipment limitations" could cover not having enough equipment, or the equipment you have can't do what you need.

Answer 2

In my university, people often call limitations as 'constraints'.

I have heard them saying:

"resource constraints" - availability of computers and machines, people

"financial constraints" - Money

"space constraints" - Physical space (room), lab etc.

Answer 3

I would lean towards words like tractability/intractability to describe problems. A problem that is intractable can, in theory, be done but, in practice, is not possible. For instance, you mention inversion of a matrix - in theory, the steps and processes required to invert a matrix of any size are clearly defined - it just is a matter of resources and time. However, in practice, the amount of resources and time required are unacceptably large.

Wikipedia has this to say about the matter:

A problem that can be solved in theory (e.g. given large but finite resources, especially time), but for which in practice any solution takes too many resources to be useful, is known as an intractable problem.[13] Conversely, a problem that can be solved in practice is called a tractable problem, literally "a problem that can be handled". The term infeasible (literally "cannot be done") is sometimes used interchangeably with intractable,[14] though this risks confusion with a feasible solution in mathematical optimization.[15]

which seems to reasonably approach what you are trying to express.

Answer 4

The problem you're describing at the end of your question could be considered a specific case of the streetlight effect:

The streetlight effect is a type of observational bias that occurs when people are searching for something and look only where it is easiest.

This term is derived from a joke:

A policeman sees a drunk man searching for something under a streetlight and asks what the drunk has lost. He says he lost his keys and they both look under the streetlight together. After a few minutes the policeman asks if he is sure he lost them here, and the drunk replies, no, and that he lost them in the park. The policeman asks why he is searching here, and the drunk replies, "this is where the light is".

Usually this term is used to criticize over-reliance on convenience samples, but it can apply equally to convenience methods. Only studying the phenomena that you have the technology to study effectively (and therefore missing potentially important insights that would have required better technology) could be considered an instance of this phenomenon, albeit a very understandable one (you're not just looking where it's easiest, you're looking where you have the technology to look).

Answer 5

The angle that I immediately thought of before reading your example of limitations of compute power was limitations in available data. The phrase to describe that is found data or observational data. For example, you can't intentionally infect a person with a known fatal disease to study it, so there are fundamental limitations on the research, and it can only be done with the observed historical data available.