The history of science has tons of examples of the same thing being discovered multiple time independently; wikipedia has a whole list of examples here. If your goal in studying the history of science is to extract the predictable/overdetermined component of humanity's trajectory, then it makes sense to focus on such examples.
But if your goal is to achieve high counterfactual impact in your own research, then you should probably draw inspiration from the opposite: "singular" discoveries, i.e. discoveries which nobody else was anywhere close to figuring out. After all, if someone else would have figured it out shortly after anyways, then the discovery probably wasn't very counterfactually impactful.
Alas, nobody seems to have made a list of highly counterfactual scientific discoveries, to complement wikipedia's list of multiple discoveries.
To that end: what are some examples of discoveries which nobody else was anywhere close to figuring out?
A few tentative examples to kick things off:
- Shannon's information theory. The closest work I know of (notably Nyquist) was 20 years earlier, and had none of the core ideas of the theorems on fungibility of transmission. In the intervening 20 years, it seems nobody else got importantly closer to the core ideas of information theory.
- Einstein's special relativity. Poincaré and Lorentz had the math 20 years earlier IIRC, but nobody understood what the heck that math meant. Einstein brought the interpretation, and it seems nobody else got importantly closer to that interpretation in the intervening two decades.
- Penicillin. Gemini tells me that the antibiotic effects of mold had been noted 30 years earlier, but nobody investigated it as a medicine in all that time.
- Pasteur's work on the germ theory of disease. There had been both speculative theories and scattered empirical results as precedent decades earlier, but Pasteur was the first to bring together the microscope observations, theory, highly compelling empirical results, and successful applications. I don't know of anyone else who was close to putting all the pieces together, despite the obvious prerequisite technology (the microscope) having been available for two centuries by then.
(Feel free to debate any of these, as well as others' examples.)
I am also not sure how useful it is, but I would be very careful with saying that R programmers not using it is strong evidence that it is not that useful. Basically, that was a bit the point I wanted to make with the original comment. Homoiconicity might be hard to learn and use compared to learning a for loop in python. That might be the reason that people don't learn it. Because they don't understand how it could be useful. Probably actually most R users did not even hear about homoiconicity. And if they would they would ask "Well I don't know how this is useful". But again that does not mean that it is not useful.
Probably many people at least vaguely know the concept of a pure function. But probably most don't actually use it in situations where it would be advantageous to use pure functions because they can't identify these situations.
Probably they don't even understand basic arguments, because they've never heard them, of why one would care about making functions pure. With your line of argument, we would now be able to conclude that pure functions are clearly not very useful in practice. Which I think is, at minimum, an overstatement. Clearly, they can be useful. My current model says that they are actually very useful.
[Edit:] Also R is not homoiconic lol. At least not in a strong sense like lisp. At least what this guy on github says. Also, I would guess this is correct from remembering how R looks, and looking at a few code samples now. In LISP your program is a bunch of lists. In R not. What is the data structure instance that is equivalent to this expression:
%sumx2y2% <- function(e1, e2) {e1 ^ 2 + e2 ^ 2}
?