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Separating the facts from fiction – It is time to silence the myths and shine a light on the truth about data sharing. In this piece, part of the #ECROpenData campaign and published on Wellcome Open Research (a partner platform with F1000Research) we cover all angles on the forms and types that data exists as; show you that help is available and who you can turn to for information and guidance; and how data sharing actually establishes and confirms ownership of your data via authorship.

We’ve broken down the myths and truths into handy sections to help you more easily find the information that you’re looking for. We hope this brings you closer to realising the diversity, richness and quantity of data this approach provides.

Me, my data and I – setting the record straight on the wide range of data types and formats to be aware of

‘I don’t have any data!’

Where data cannot be easily digitised in a way that maintains its usefulness for others, you can still ‘share’ the data by creating an extensive metadata record describing the object, where it is stored, and how to access it.

Depositing this metadata record openly in a repository will allow others to find it. You can cite the metadata record in any associated articles (and vice-versa) in order to establish linkages between the published work and the dataset.

Where published work genuinely has no data associated, it’s best to indicate this clearly in a data availability statement. This confirms the absence of data to readers, rather than the absence of data sharing.

‘Data sharing isn’t a thing in my field’

For inspiration, see discipline-specific case studies as part of Wellcome Open Research’s Early Career Advisory Board Data Sharing Campaign.

You are not alone – help is at hand to guide you through the process of sharing your data

‘Data sharing is too hard’

Data stewards can help with expert disciplinary guidance for data sharing and facilitate early planning using a data management plan. Numerous funders also offer services to their grantees to promote data sharing (for example, Wellcome’s Research Data Service pilot with Springer Nature).  Beyond this, many funders have started allowing data management to be included in project budgets. It’s important to allocate resources for research data management in future proposals.

 ‘I’m not sure I have the rights to share my data’

Setting aside your concerns on data misuse and how sharing your data gives you ownership and credit

 ‘My data is too sensitive to share’

Still can’t share your data? 

Then, share your metadata! You can openly publish a description of your data (known as a ‘metadata record’). This helps others to discover your data and provides essential information about how the data can be accessed and cited.

For example, you could post a “data codebook” or “data dictionary” in a repository that describes the variables used in your dataset. In this document, you can cite the article in which it appears in order to connect the data description to the paper. Similarly, you can cite the metadata record in your article as part of a data availability statement, which should also include the conditions under which your data can be accessed.

 ‘My data will be misinterpreted’

‘My data will be reused inappropriately’

‘I am concerned my research will be scooped if I share my data’

It’s time to think big – FAIR data is important and here’s how it can benefit researchers and the community

‘My data isn’t useful to anyone else’

‘Sharing my data now will impact my ability to publish later’

‘Sure, I can share my data.  I’ll include it as a supplementary file, post it on my webpage, or have others request my data via email’

‘It does not hurt my research career if I do not share my data’

Plus, with the drive towards Open Science incentive structures are changing.  Sharing your data now may be valuable to your career in time.