5 ways sharing your research data could help enhance your career (and 3 ways to get started)
There’s increasing evidence that sharing the research data which underpins your published article can have tangible benefits for you, and for your research career.
Written by Rebecca Grant, Research Data Manager at Springer Nature
When you deposit your data in a repository and link it to your research article, it can be found, accessed and reused by researchers in different institutions, different regions, and even different disciplines. There are obvious benefits to science when researchers share data - but what specific benefits can you expect?
1. More citations of your published
research articles
When you share the dataset that underpins your article, it’s not just the article that might be reused or cited; data sharing is also associated with an increase in citations to your research article of up to 25%.*
2. Greater discoverability and enhanced visibility
Sharing data in a repository makes it visible, and easily found by researchers other than those reading the journal you’ve published in. Data repositories are increasingly searchable on Google and indexed in resources like Google Dataset Search. The metadata you add to your data’s repository record helps others to understand how it was generated and what it consists of.
3. Get credit for your work and gain recognition
Not content with just increased citations of your article? More and more journals allow authors to cite datasets in reference lists, so if someone reuses your data, you get an additional citation for it.
4. New opportunities for collaboration
When your data can be easily found, other researchers can reuse it; or they may wish to work with you collaboratively to build on the data you’ve already shared.
5. Improve the veracity, robustness and reproducibility of your results
Science is in the midst of a reproducibility crisis, and many researchers report that they can’t reproduce others’ research (or even their own) .** Sharing data openly can encourage studies which replicate studies, and allow others to test the validity of your results.
Get started with research data sharing
Want to try data sharing? There are a few simple steps you can take to get started. You’ll need to identify which parts of your data you want to share, decide where to share it, and write a data availability statement to ensure that others can find it.
If your research generated large volumes of data, or multiple versions, it might not be clear what data you’re meant to be sharing. You can check with the policies of your funding agency, or the journal you’re publishing in, to find guidance on what you should share.
There are literally thousands of data repositories available online, including repositories which are specifically for certain data types or research disciplines; those provided by your institution or funder; or some which accept data in any format. It’s beneficial to select the repository which is most commonly used in your discipline - reading how other researchers in your field share their data can help you to establish which repository that might be.
Data availability statements are the best way to link your research paper to your dataset. They’re a simple paragraph which outlines where your data are and how they can be accessed (ideally in a data repository!). Journals are increasingly encouraging authors to add this statement to submitted manuscripts.
Need more help sharing data?
Research Data Support
Springer Nature Research Data Support service is a curation service for any published researcher (or those who are in the process of publishing in a Springer Nature journal or book). Researchers that use the service may feel that they don’t have the time, expertise or knowledge needed to organise data in a useful way, meet funder or institutional requirements on data sharing and get more credit and readership of their data and associated publication.
Our team of expert research data editors do all the time-consuming work of creating high quality metadata records, making your research data understandable and easier to find and use by researchers in your field of study: time that you could use to carry out new research. We make sure that other researchers can find and cite your work, so that you get the credit you deserve.
Find out more about Research Data Support.
Data publishing
Data publishing supports researchers who want to share their datasets through peer-reviewed publications, without having to be at the stage of presenting further analysis and conclusions, as in a traditional research paper. Springer Nature supports and encourages data publications: we publish two dedicated data-publishing journals, Scientific Data and BMC Research Notes, and a number of our subject-specific academic journals offer article types suitable for data-only publications.
Our data papers put an emphasis on making data FAIR through recommended repositories, data citations and rapid publication.
To find out more, visit our research data publishing page, or get in touch directly via email.
*The citation advantage of linking publications to research data. Giovanni Colavizza,Iain Hrynaszkiewicz,Isla Staden,Kirstie Whitaker,Barbara McGillivray. https://doi.org/10.1371/journal.pone.0230416
** www.nature.com/news/1-500-scientists-lift-the-lid-on-reproducibility-1.19970
If you would like to learn more about research data, our upcoming free webinar on 8 December, Sharing Research Data: What Publishers Want Authors to Know, will provide an introduction to good practice in research data sharing and tips and guidance for getting started. Register here.
About the author
Rebecca Grant is Research Data Manager at Springer Nature, where she contributes to projects and services which support research data management and sharing, including the implementation of standard research data policies across Springer Nature journals. She leads the development of research data training as part of Nature Research Academies, and is a qualified data trainer certified by the Open Data Institute. Her doctoral thesis explored the connections between archival theory and research data management practice.
