figshare help

Guide to sharing NSF-funded research on

Researchers with National Science Foundation (NSF) funding are invited to use Figshare to make all the products of their research publicly available, reusable, and citable when a discipline-specific repository is unavailable. is free for researchers to use and provides free, open access for others to view and download your research. Any type of data can be shared and many file types can be previewed in the browser. Also, many other products of your research beyond data can also be shared including code and software, multimedia files, figures, protocols, workflows, posters, presentations, and papers. Figshare+ is a repository that allows for openly sharing big datasets (over 20GB), more files, and larger files together with more license and metadata options than as well as expert support and dataset review. Figshare+ has a one-time data publishing fee based on storage amount, which may be an allowable cost on an NSF grant. Sharing all of the results and components of your research can make it more transparent, reproducible, reusable, and impactful and planning how to share your work in a trusted repository like Figshare from the beginning of a project can help you comply with funder policies, including NSF policies, for data management and sharing as well as journal policies for data availability.

Here we outline how to share NSF-funded scientific research on, including some best practices to make your work as discoverable and reusable as possible. 

To get started, sign-up for a free account or get started with a Figshare+ dataset. Then upload, describe, and publish your data. Here are a few things to think about when sharing your NSF-funded research.

1. Include data sharing in your Data Management Plan (DMP) when submitting NSF grant proposals - Plan your data sharing from the start of your grant or project including what research products will be made publicly available, which repositories you will deposit them in, and how they will be licensed for reuse. 

  • NSF’s requirements for data dissemination and sharing of research results and Data Management Plan requirements are quite specific and are an excellent opportunity to design your project’s workflows and documentation with open access in mind from the start. 
  • The DMPTool NSF Templates provide ways to get started with this planning including how to comply with DMP requirements by NSF Directorate
  • As a generalist data repository recommended by funders and publishers, Figshare provides a repository to archive the data, code, and any other products of your NSF-funded research that do not have an appropriate discipline-specific repository. Figshare can be included in your DMP as the public repository for any research product to be shared publicly at any stage of the project. 
  • Figshare endorses the TRUST principles for digital repositories and has adopted the FAIR open data principles. All items published on include standardized, machine-readable metadata, licenses, and version-controlled, citable DOIs, are discoverable via search engines like Google, and have openly tracked metrics for views, downloads, and citations. Figshare provides secure, long-term storage of data in the cloud including file back-up and security as well as preservation and continuity of access for all of the publicly accessible, final products of your research. 
  • Include data management and sharing costs in grant proposal budgets including for data curation and data publishing. For sharing larger datasets, Figshare+ pricing is transparently listed so you can plan ahead for data sharing costs. 

2. Items and Collections - When uploading files to share on Figshare, group your research products into “items” as you would want them to be cited. If you have a research project with multiple data files or outputs, you can choose to create multiple items with just 1 or 2 files each or you can create a single item with many files. How you choose to group these should depend on how similar the items are, if they are the same type, and if you wish to apply the same licenses. You can also create a Collection to group together any public items published across Figshare portals - a collection offers a way to point to all of the outputs associated with a specific paper, project, grant, or research group with a single DOI and citation. 

3. Sharing large or complex data - 

  • To publish datasets larger than 20GB (up to many TBs) or files larger than 20GB (up to 5TB), please consider Figshare+, our Figshare repository for FAIR-ly sharing big datasets. There is a one-time cost associated with Figshare+ to cover the cost of storing the data persistently that may be an allowable cost on your NSF grant. Find out more about Figshare+ features including transparent pricing based on storage or get in touch at with the storage amount needed and we will find the best way to support your data sharing.
  • For complex hierarchical data you may wish to upload zipped or compressed files to preserve the file structure. The file names within these, but not the files themselves, will be previewable and it’s recommended to group data into files of less than 10GB to facilitate downloading. 
  • You can use the Figshare FTP or API to upload files.
  • You can also use the Figshare API to upload and download data and metadata. 
  • You can link a GitHub repository to publish releases to Figshare. See all Figshare integrations

4. Data sharing considerations and best practices - see our Guide to Best practices for managing your outputs on Figshare for important considerations including: 

  • Ethical considerations - consent to share, human subjects data, and personally identifiable information (PII). Note that only fully deidentified data without PII should be shared on Figshare. 
  • Copyright - Do you have the right to distribute this work? How should the work be licensed for future reuse? 
  • Make your data FAIR (Findable, Accessible, Interoperable, Reusable)
  • Opt for open and preservable file formats that can be used without proprietary software when possible, even if it requires posting the same data in multiple formats.
  • Use a consistent and descriptive file naming convention.
  • Include documentation that would be needed to understand and reuse the data as a file together with the dataset such as a README text file, a code book, or a data dictionary. 
  • Include descriptive metadata to enhance the discoverability of the work and provide context to the research study. 
  • Include discipline or method specific metadata and adhere to data standards for your research community when possible.
  • Select an appropriate license for reuse paying particular attention to which licenses are best suited to different output types such as data, code, or written text. 

5. Title - Include a meaningful title for your items as you would for any other research work such as a paper or presentation so that the title provides context about the research question and method. If the data supports a specific publication you might wish to include the paper title in the item title as well.

6. Description - In the “description” metadata field for each item be sure to include a description of the specific research items shared as well as description of the research methods used and the research study as a whole. This is important if someone discovers the research independent of any other description. This is similar to the caption you might write for a figure and the abstract you would provide for a paper. 

7. Related publications - link to related publications and edit your item to add publications if they are published later. Include the full citation to a related journal article or preprint in the description field and include the article title and article DOI (DOI only starting with “10.”, not the complete URL) to the published paper in the ‘Resource’ title and DOI fields. You can also use the ‘References’ field to link to other related resources such as: research materials shared in Figshare or another repository, a project or lab website, a GitHub repository, or a registration or other study registration. You can add a DOI or a URL to the References field and can include multiple links by entering return to generate a new text box. 

8. Funding - In the funding field, list all supporting funding with each funding source or grant entered separately. You can search for these by grant title or number. For NSF funding, enter the award number in the ‘Funding’ field - this will pull from the Dimensions grant database and should show you the title of the grant in a dropdown, which you can click to add. You can also add NIH funding (see NIH Data Sharing Guide) by entering the activity code (e.g. R01), the institute code (e.g. EY), and the grant 6 digit serial number.  Add funding from any other source by searching or entering as free text into a funding field.

9. Each item you publish on Figshare will have a DOI, a Digital Object Identifier, which is a globally unique, persistent identifier that is version controlled. You can view the DOI and full citation for any public item by clicking on the Cite button. The DOI will be live once the item is published but you can also reserve the DOI in advance to include it in manuscripts. The DOI should be used whenever you cite the item so citation metrics can be collected including when pointing to the data in related publications or data availability statements. You can also include these DOIs in reports to NSF to demonstrate publicly available research products of funding. For datasets supporting a publication shared in the NSF Public Access Repository (NSF PAR), the dataset DOI from Figshare may be included in the publication record metadata as well.

10. You can edit your published research items at any time to update the files or description and DOIs will be versioned to reflect substantial changes

Other NSF data sharing resources:

NSF Dissemination and Sharing of Research Results

NSF Dear Colleague Letter: Effective Practices for Data

NSF Dear Colleague Letter: Open Science for Research Data

DMPTool Data Management Plan Templates including for NSF Directorates

NSF Public Access Policy for peer-reviewed articles to be deposited in the NSF Public Access Repository (NSF-PAR)

We encourage you to seek out data sharing guidance that is specific to your supporting NSF Directorate or your field of research as well as to seek support from your institution that may be available from the library or office of research.

Writing a Data Management Plan? See our Guide to including Figshare in your Data Management Plan.

Share this article: