What is figshare?
figshare is a repository where users can make their research outputs available in a citable, shareable and discoverable manner. figshare is a part of Digital Science, a separate organisation to Springer Nature. figshare allows individual users to upload any file format, many of which can be previewed in the browser, allowing widespread dissemination of research. Springer Nature works with figshare to increase the discoverability of content while better serving end users and authors. Research data are as housed on springernature.figshare.com, a repository space managed by the Springer Nature team. figshare also embeds Altmetrics data on the item page.
Is there a cost for the service?
No - authors submitting to Springer Nature journals can deposit their data in springernature.figshare.com for free. Datasets over 50GB may incur a fee for additional storage (see figshare’s large data service, figshare +). Please contact email@example.com if you have questions on deposition of datasets over 50GB in size.
Is there a size limit on data submissions?
Datasets up to 50GB can be submitted via the manuscript submission system. However, upload time and capacity is dependent on internet connection. If you have a larger dataset you would like to share, this would have to be managed outside the integrated application and additional storage fees may apply (see figshare’s large data service, figshare +). Contact firstname.lastname@example.org for more details.
Will this impact the peer-review and publication timeline?
The figshare integration is designed to complement the editorial and review process without delaying progress on your manuscript. Some scope checks will be performed on your data alongside editorial checks on your manuscript.
Reviewers will be able to view submitted data with author names removed, avoiding the need to provide separate data access.
What checks are performed?
Technical and scope checks performed include completeness of files and metadata, presence of sensitive data and data that belong in a specialist discipline-specific repository (see our list of mandated data types that should not be submitted to figshare).
What licence should I use for my data?
We offer a number of open licences for data and code submissions, principally CC0 and CC BY, alongside a range of open software licences. For more information see our guide to licences available in the Springer Nature figshare repository.
Will I still own my data?
You retain ownership and rights over your data when submitting to figshare. You must apply an open licence to your data, and we set some criteria on what can be submitted, but we will not claim ownership over submitted data. If you are not the data owner you should ensure that you have the rights to share the data before submitting to figshare.
Should I share Source data underlying my figures in figshare?
A number of journals and article types request the submission of Source data underlying figures and graphs (see this guidance for more information). It is not a requirement to submit these to figshare and Source data should be submitted alongside the manuscript.
These include raw data underlying any graphs and charts, and uncropped versions of any gels or blots presented in the figures.
How do I de-identify participant data before sharing?
Methods include removal, replacement or obfuscation of key identifiers in the data, such as replacing the date of birth with an age range, removing names and other direct identifiers, or randomising attributed values. For guidance on anonymisation and management of clinical/sensitive research data see http://trialsjournal.biomedcentral.com/articles/10.1186/1745-6215-11-9 before submission. If sharing human data, you must have participant consent. You should then consider de-identifying or anonymising your data for public release.
What other types of data are sensitive aside from human data?
Other sensitive data types include but are not limited to: locations of endangered or threatened species, protected archaeological sites, rare specimens or collections, financial, restricted governmental or military data, passwords, API tokens or other account credentials.
Won’t this process take longer than just sharing data when requested?
Sharing your underlying research data in a repository is potentially much more efficient than putting it off. This is a one-time activity, ensuring its long-term preservation and availability. It is clear to a potential user what data are available in the repository, what licence they are available under and the context of the data from accompanying metadata.
Making data ‘available on request’ on the other hand, commits you to respond to every data access request over an unspecified time period, tracking down the right data from wherever it is stored, providing adequate context and overing usage terms each time you share your data.
I’m still not sure what data are eligible.
See our infographic on types of research data: https://researchdata.springernature.com/documents/infographic-what-are-research-data. In general you should aim to share data supporting any analysis or results reported in your research paper. These should be measurement-level as opposed to aggregate data like high-level graphs or tables often included in the manuscript itself.
What metadata will I need to provide?
Title: a brief name for your dataset. We encourage this to be specific to the data but the title of your paper is also acceptable.
Authors: again we advise to make this specific to the data creators, but the author list from your paper is acceptable.
Description: here you can provide more context for your data, that would allow a user to understand and use your data files. There is no minimum requirement but the more detail the better, for example you could outline the scope of the data (e.g. sample size, time period), its format, variables etc.
Keywords and Categories: search terms to make your data more accessible.
Licence: select from a list of open licences (see q. 5 above for more information).
Wouldn’t my data be better in a community repository?
If community repositories exist for the type of data you have generated, then we encourage you to use these. Community repositories use metadata that is specific to the community, thereby increasing searchability and interoperability of the data. Also, researchers investigating similar topics are more likely to be familiar with their community repositories. To search for community repositories, we recommend using https://fairsharing.org/ or https://www.re3data.org/.
If you have generated multiple types of data, it may be the case that these different types are best shared in different repositories.
Generalist repositories, such as figshare, are good solutions to data sharing when community repositories are not available.
Will I be able to remove my data after it has been published?
No. Once the data have been published, they cannot be unpublished except in special circumstances (for example, if the data contain sensitive human data for which no consent to publish was obtained). This is in-line with best practice for maintaining a consistent scientific record.