#scidata16: Work reproducibly for the sake of your career

Making sure others can do your experiments doesn’t just help them — it’s good for you, too.

Publishing Better Science through Beter Data writing competition Jonathan Page

A core tenet of science is reproducibility: the results of one scientist must be able to be reproduced by another, lest the findings be dismissed as a fluke or even fraudulent. In today’s data-driven realms of research, ‘reproducibility’ doesn’t simply mean publishing methods, many journals now require that datasets, and the code used to analyse them, be published too. This requirement ensures that both data, and methods, can be scrutinised. If other researchers can’t reach the same results, the study will need to be treated with caution. In doing this, scientists avoid damaging their reputation by publishing flawed studies, and journals avoid publishing bad science. It’s a win-win situation.

So why don’t scientists always work reproducibly?

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Jonathan Page

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How is the rise of data-intensive research changing what it means to be a scientist?

Research involving vast quantities of data may be changing the image of scientific research, but is it changing the image of scientists too?

Scidata publishing better science through better data competition winner Jonathan Page.

An intrepid, khaki-clad explorer, machete in hand, cutting their way through some undiscovered wilderness. A bespectacled, grey-haired academic in a white coat, supervising some elaborate experiment in a lab, illuminated by glowing lights and flashing buttons. These are the classical images sometimes conjured when the word ‘scientist’ is mentioned.

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Horace B. Carpenter as Dr. Meirschultz, a scientist attempting to bring the dead back to life in the 1934 film Maniac

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