Benefits of data sharing for you

Ask not what you can do for open data; ask what open data can do for you

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It has been shown that research articles receive more citations when they have their underlying data openly linked to them. With this in mind, it’s time to consider not just the ideological reasons for making research data open, but the selfish benefits of openly sharing data that all researchers can (and should) be taking advantage of.

And as an increasing number of funders mandate data sharing, and publishers start implementing more consistent data policies at their journals, it is worth seriously considering how and why you should make the research data you generate more openly available.

But what is really in it for me and aren’t there risks as well?

If this was your first thought, you’re not alone. From the fear of ‘research parasites’ and ‘scooping’ to reports that the majority of scientists think openly sharing data is good, yet far fewer actually do it themselves (see here, here and here for such reports), there is still legitimate concern around openly sharing data.

But data sharing doesn’t need to be a risk or merely a necessary act of compliance with policy requirements. Far from disadvantaging your career, openly sharing your data in the correct way should improve it. And here’s how.

The myth of impacting publication

The vast majority of publishers (including Nature, Science, Biomed Central, Elsevier, PLOS and SAGE) don’t consider the publication of a dataset as a prior publication. This means pre-publishing data won’t jeopardise your ability to publish research articles later. Which in turn means you can even publish your data while you are still carrying out your research.

By doing so you will increase the visibility and discoverability of your research, confirm ownership of your data, and provide more opportunities for your research to be recognised and used – all this on top of increasing the potential for your articles to receive a higher level of citations.

This said, always check with any journals you plan on submitting to what their policy is before you publish your data.

Going from ‘scooped’ to ‘credited’

Many repositories now mint data deposited in them with Digital Object Identifiers (DOIs), meaning that if someone does use your data in their work you won’t be ‘scooped’ – you’ll be ‘credited’ in line with scholarly norms of citation. By openly sharing your data you‘ll get credit for all of your research, not just the bits that make it into an article. You’ll also increase your overall visibility and potentially open new doors for collaboration with those who find and use your data.

Imagine if Rosalind Franklin had deposited her data in a DOI minting repository – she could have received credit for her work on DNA structure at the time she carried it out! Instead, Franklin’s crucial contribution to the discovery of DNA was not acknowledged until after her death.

This demonstrates that beyond the clear citation, discoverability and usage advantages to depositing and sharing your data, there are potentially other far reaching implications of your data being available and properly accredited to you, which may not be immediately obvious to you when you are generating and collecting your data.

The majority of the repositories listed here provide DOI minting (along with a number of facilities that will ensure your data are well looked after) and so it is easy to find the right repository for you and ensure you get the credit you deserve.

Avert your own reproducibility crisis

In recent years there has been a growing concern about the reproducibility crisis in science. If experiments and results can’t be replicated then how can they be trusted?


1,500 scientists lift the lid on reproducibility, Nature (25 May 2016)

According to a recent survey, more than 70% of researchers have failed when trying to reproduce someone else’s experiments and more than 50% have failed to reproduce their own. In a world where this is the case, the need for quality data management has become paramount.

Standardising the practice of openly sharing your data as part of your research process will help you avoid your own reproducibility crisis. You’re unlikely to want to present something to the world that isn’t its best version and so, as Florian Markowetz makes clear in his talk ‘five selfish reasons to work reproducibly,’ if you know your data are going to be openly available, you add a compelling extra incentive to make sure they are as robust and reproducible as possible.

The Digital Curation Centre (DCC) provide a number of data management resources to help you best make sure your data are reproducible. And if you want more assistance you can always ask your librarian for guidance, or contact our dedicated Research Data Support Helpdesk.

By working reproducibly, which includes documenting, versioning and archiving data, you will also make it easier for reviewers, editors and other researchers to understand and engage with your research. Meaning it will be easier to present your research and results, easier to get published and easier to show everyone the great work you are doing.

In short: you’ll get better results and be better rewarded for them.

Too much data on open data? Here are the key points

How you will benefit from openly sharing data:

  • Gain the credit you deserve for all your research work
  • Increase the ability of editors, reviewers and researchers to understand your research
  • Improve the veracity, robustness and reproducibility of your results
  • Open up new opportunities for collaboration
  • Increase you and your research’s visibility and discoverability
  • Potentially improve the citation rate of your published research articles

Two actions to help ensure you best openly share your data:

  • Incorporate open data sharing as standard practice in your research cycle
  • Deposit data in a repository that provides DOI minting or other persistent identifiers

Hopefully you now see how openly sharing data can greatly benefit you and you’ll go forward collecting, minting and sharing your data as openly as possible!

[The original version of this article, published by Naturejobs, can be accessed here.]

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