#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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Why don’t scientists always share their data?

Reproducibility is the cornerstone of science, and it can be compromised by insufficient data in peer-reviewed publications. Should scientists reveal everything?

Publishing Better Science through Better Data writing competition winner Emma Vander Ende.

One of the foundations of science is its reproducibility. Without it, results are not verifiable and are therefore not believable. But even if a published result is true, there is a chance it might not be reproducible, which introduces a plethora of problems for science.

Irreproducible experiments severely limit the ability of the scientific community to build on results and advance the field. This can happen when scientists don’t share enough data, or details of their experiments in papers, and it happens quite frequently.

So why might a scientist not share their data?

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