Supporting open science practices: Why share your research data?
Open data is fast becoming an essential component of scholarly communication. Our latest State of Open Data report suggests that open data is on the brink of becoming a standard, recognised and supported scholarly output, globally, and that sharing data helps to create a more equitable, fairer, and less wasteful research ecosystem. Here, we look at why sharing your research data benefits you and the wider scientific community, and we offer practical tips on where to begin.
The foundation of robust, transparent research
We believe that sharing all outputs of research helps advance discovery by making research more transparent, more robust, and by accelerating research progress. In our ongoing open science blog series, we’ve looked at a number of different open science practices, including sharing protocols and code, and how we are actively enabling open science practices across our portfolio.
Sharing your data is a foundation of open science. But what exactly do we mean by data? Depending on the type of research you conduct and the discipline you work in, data can mean nearly any type of file, including text, audio, or images. Data can be qualitative, quantitative, analogue, or digital. Any output that underpins your research is valuable data.
Data management and sharing is increasingly following what are known as the FAIR principles to make data genuinely useful to others. By making data findable, accessible, interoperable (or machine readable) and reusable increases the transparency and reproducibility of your work, reduces duplication and wasteful repetition of research results, and ultimately increases trust in science.
Researchers worldwide are linking publications to datasets
The State of Open Data survey shows that the number of researchers who share data is steadily growing. Importantly, the report also shows that Springer Nature’s research articles are increasingly published with data availability statements. These statements offer clear descriptions of how researchers have made their data available, enabling others to understand how to find, use, and re-use their data. They may also include links to publicly available data, if it is available in a repository. Linking your open data to a published article enables more researchers to explore, validate and build on your work, strengthening credibility.
Credit for open data
Beyond supporting other researchers, openly sharing data offers you many direct benefits. Data sharing via repositories has been shown to increase citations for both the paper and its datasets. The State of Open Data found that citations remain one of the top reasons why researchers share their data. There are a number of suggested reasons for this citation benefit: the public availability increases visibility and engagement with your work, which in turn increases the potential for reuse, making the research more likely to be cited. Also, when the data is openly shared, it may signal to other researchers that it can be trusted. Through repositories or data publication, open data also includes persistent identifiers (PIDs) which make it possible to track metrics such as reuse and impact, making it possible to assign credit to all individual contributions to research.
Funders and journals with requirements for data sharing
Funder policies are increasingly requiring grantees to share their data (see for example, NIH, or Wellcome). These requirements are also driving data sharing practices. For example, the State of Open Data shows that countries with established policies (such as across Europe) have higher levels of sharing.
The State of Open Data also recommends that, for publishers, combining policy with an easy to action workflow is essential if we want more researchers to share their data. That’s why we created our unified data policy for all journals and books, making it simple for our authors to know what is expected of them.
Springer Nature’s data policy – what you need to know
- All original articles must include a data availability statement explaining where and how to access the data (and here’s more on how to do it).
- We encourage you to share your data in a repository. There is guidance on what to consider when selecting a repository, for example some disciplines have a dedicated repository that is recognised within the community, while others may require a generalist repository. A key note is that good repositories should provide a PID which can also be cited by others, giving you more credit for your work.
- We recommend that data is as open as possible and as restricted as necessary. It isn’t always appropriate to publish your data openly, for example when it is sensitive (such as human data) or proprietary. You should always apply appropriate restrictions before sharing data. You can find more guidance on sensitive data sharing.
Top tips for getting started with data sharing
Whichever route you choose, sharing your data is a vital step toward a more transparent, trustworthy research ecosystem. Here are our three top tips to get you started:
- Plan early. It’s important to think about how you’ll manage, document, and share research data as early as possible during your research, and certainly well ahead of publication.
- Ensure data is available for peer review: reviewers and editors may request to see your data as part of the peer review process to inform their evaluation of your work.
- Check which repository is most appropriate for your work.
For support and advice, check out our research data community site, or contact our Data helpdesk.
Related content
- This blog is part of an open science blog series. Find out more about open code and open protocols.
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