And we had a feature last year on the problem of computational reproducibility, which this really sort of feeds into. So much research right now involves manipulating data, and it’s possible to open up your data files in Excel and work with them in a programme that has like a point-and-click interface and manipulate them and there’s nothing wrong with doing that.īut the trick is that if you go through a whole bunch of steps and figure out a way to do something and then you really like it and then you want to do it again because you do the same experiments a month later and you say I want to make that same graph again, that’s hard.Īnd one of the things that to me makes coding so powerful is that instead of using that point-and-click interface, if you figure out how to do those manipulations by basically writing programming scripts to do them for you, then all you have to do to run them again is change the name of the file that you’re working on.

So, I asked Jeff Perkel, the Nature technology editor, why he thought that being able to code was a useful skill for a scientist. In this episode, we’re going to go back to basics and look at why a skill like computer coding is so vital for any researcher in academia, ranging from the biological sciences to agricultural studies and even to Old English literature. In the first episode, we heard all about artificial intelligence from Mark Dodgson and Lee Cronin and how it may or may not change the way that universities operate. This is the second part of our series all about technology, and we’re exploring how the technologies are affecting scientists, research and universities. Hello, I’m Julie Gould and this is Working Scientist.

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