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US Funder user guide

All researchers with US federal funding are invited to use Figshare to make the products of their research publicly available, reusable, and citable when a discipline-specific repository is unavailable.

Figshare.com 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 Plus 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 figshare.com as well as expert support and dataset review. Figshare Plus has a one-time data publishing charge based on storage amount, which may be an allowable cost on your 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 both funder data management and sharing policies, including NIH and NSF, and journal policies for data availability.

Here we outline how to share your federally funded research on figshare.com and Figshare Plus, including writing Figshare into your data management plan and some best practices to make your work as discoverable and reusable as possible.

Include Figshare in your data management plan

As recognition of the importance of data management and sharing grows, it is increasingly common that funders of research and institutions require a data management plan (DMP) to be created for grants and projects. In the US, many federal funders require DMPs at the time of grant submission including the National Science Foundation (NSF) and the National Institutes of Health (NIH).

Overall, a DMP asks the researcher to consider how data and associated products of research such as code or other files, will be handled across the life span of a project and beyond. This includes how the data will be stored, secured, accessed, documented, formatted, and versioned. The plan should also include where and when data will be shared, if it will be made publicly available, how it will be licensed for reuse, and how and for how long data will be archived.

If there is a repository that is specific to your research discipline or methodology, it is recommended and sometimes even required (e.g. genomic data), that appropriate data be deposited there to facilitate discovery and reuse. However for all other data and research materials for which a discipline-specific repository does not exist or isn’t appropriate, trusted generalist repositories are a suitable choice for sharing data responsibly.

Figshare.com is an appropriate repository for researchers to permanently store the datasets and other materials produced from their research and to include in their data management plans submitted to funders.

How to describe sharing your data in Figshare in a data management plan:

When you describe sharing your data in Figshare in your data management plan, the following details should be noted:

  • Where the data will be made publicly available (i.e. published on Figshare)
  • What data will be shared in Figshare (e.g. raw data, processed data, de-identified data, data supporting publications, null results, etc.)
  • When the data will be made publicly available
  • What file formats the data will be shared in so that they can be reused.
  • What documentation will be included with the files to provide context and enable reuse such as a README file, data dictionary, or codebook.
  • What other materials will be shared (e.g. code, software, images, video, workflows, anything)
  • How the data and other materials will be licensed for reuse
  • How the data will be described so that it can be discovered
  • How long the data will be preserved

Example Text for Your DMP

  • Where the data will be made publicly available: Research data from the project will be deposited in Figshare, an established data repository that makes the results of research discoverable and freely available to view, download, and reuse. Figshare maintains a digital repository infrastructure dedicated to data preservation and continuity of access, data integrity, and security, and has endorsed the TRUST principles for digital repositories.
  • When the data will be made publicly available: Data will be deposited in Figshare and made publicly available at the time a preprint or peer-reviewed publication associated with the data is published. New releases of the data will be published as subsequent versions of the same DOI if additional analyses are shared. Unpublished data including null results will be made open at the end of the award period.

How the data will be described so that it can be discovered: Each dataset published in Figshare will be assigned a unique permanent identifier, a DOI (Digital Object Identifier) that is version controlled and can be cited and tracked. All files published in Figshare will also include metadata that conforms to community standards for DataCite DOIs. This includes a title, authors, description, keywords, categories, a machine-readable license, item type, funding sources including grant IDs, associated publications, and references.

DMP Resources

At academic institutions, support for data management including guidance on creating DMPs is often available from experts such as data librarians, so we recommend checking the websites of the library and the research office at your institution to get assistance.

There are also resources such as DMPTool and DMPonline that track funder requirements for DMPs and offer both examples of DMPs and templates to write your own DMP according to the funder’s requirements.

DMPTool List of Funder Requirements
DMPonline List of Funder Requirements

You may also find our guide to Best practice for managing your outputs on Figshare helpful.

Publishing your data with Figshare

To get started, sign-up for a free figshare.com account (view the Getting Started section of this guide for more) or submit a Figshare Plus order request form. Then upload, describe, and publish your data.

Here are a few things to think about when uploading and sharing your US federally funded research to figshare.com or Figshare Plus. We also encourage you to seek out data sharing guidance that is specific to your funding agency and/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.

Items and Collections

Before you begin, decide how you will organize your dataset. Group research products as you would want them to be cited and as they support specific publications. If you have a research project with multiple data files or outputs, you can choose to create multiple items. An item in the repository represents a unique page with files, a description, metadata, a citable DOI (digital object identifier), and openly tracked metrics of views, downloads, and citations. Each item can contain anywhere from one file up to 500 files.

How you choose to group files into items should depend on how similar they are, if they are the same type of research output, and what licenses you wish to apply to which outputs. Figshare offers a variety of item types based on the research product you are sharing.

You can also create and publish 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. Published collections have their own descriptions, DOIs, and usage metrics.

Uploading your files

Files can be added to your items by dragging and dropping them into the upload box via the browser, browsing on a local drive, or by using the Figshare FTP or API (recommended for large files or many files). Documentation on how to use Figshare’s API can be found at https://docs.figshare.com/ along with some examples on our API Guide.

Sharing big datasets

To publish datasets larger than 20GB (up to many TBs) or files larger than 20GB (up to 5TB), please consider Figshare Plus, our Figshare repository for FAIR-ly sharing big datasets. There is a one-time cost associated with Figshare Plus to cover the cost of storing the data persistently that may be an allowable cost on your grant.

Find out more about Figshare Plus features including transparent pricing based on storage or get in touch at review@figshare.com with the storage amount needed and we will find the best way to support your data sharing.

Sharing complex datasets

If you have complex hierarchical data, Figshare supports folder upload, which allows the relationship between files to be maintained when viewing an item. Please organize your files into folders before uploading the top level folder(s), as files cannot be moved between folders after upload.

If you have large files or more than 500 files to share in a single item, you may wish to upload zipped or compressed files as archives. You can upload one or many zipped files (archives) to an item. The file names within these archives, but not the files themselves, will be previewable.

You can also link a GitHub repository to publish releases to Figshare. See all Figshare integrations.

Data sharing considerations

See our guide to best practices for managing your outputs on Figshare for important considerations including:

  • Make sure that you have given full consideration to research ethics, e.g., consent to share, human subjects data, and personally identifiable information (PII). Note that only fully deidentified data without PII should be shared on Figshare.
  • 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.
  • Provide 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.

Prepare high quality metadata

Include both descriptive metadata to enhance the discoverability of the work and provide context to the research study and discipline or method specific metadata to adhere to data standards for your research community when possible.

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 may include the paper title in the item title, but they should not be exactly the same (e.g. “Dataset supporting Paper Title”).

Author Information

Uploading authors are expected to sync their ORCID iD with their Figshare user profile. ORCID iDs enable unique author identification and allow for recognition of all types of research contributions. Please refer to our guide How to connect your ORCID profile for instructions on syncing your ORCID iD so it is included with your Figshare published research. Note that for co-authors without a Figshare account, you can also add an ORCID manually when adding the co-author by name.

Description

Include a description of the specific research items shared as well as a 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 captions you might write for a figure or the abstract you would provide for a paper. You might also wish to note related materials including publications, code, data, or webpages.

Funding

In the funding field, list all supporting funding with each funding source (grant, award, contract, or intramural project) entered separately. You can search for these by grant title or number, select the appropriate grant that will appear in the auto-populating search field from the Dimensions grant database.

For example, for NIH funding, enter the activity code (e.g. R01), the institute code (e.g. EY), and the grant 6 digit serial number in the ‘Funding’ field.

Funding information can also be added as free text in these fields for any support not found via the search function.

Related Materials

Add linkages to other research objects using Related Materials and provide information on the relation types. Figshare uses DataCite’s standard relation types. Common relation types are IsSupplementTo and IsReferencedBy. Both of those relation types are interpreted as a citation for the dataset in DataCite’s event data.

For example, to add the DOI for a paper that uses the dataset, add the title of the paper in the title field, add the paper’s DOI, select DOI from the identifier type list, and choose IsSupplementTo as the relation type. If you want to link to a related dataset or a Figshare Collection, use the IsPartOf relation type.

License

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 as well as any other restrictions that may accompany the research. CC0 licenses may be useful for data to allow for the broadest reuse without restrictions. CC-BY licenses require attribution and are recommended for text materials as well as other research outputs.

Digital Object Identifiers (DOIs)

Each item you publish on Figshare will have a Digital Object Identifier (DOI), 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 your funder or publisher to demonstrate publicly available research products. For datasets supporting a publication indexed in a federal full-text archive like PubMed Central, the dataset DOI from Figshare may be included in the publication record metadata as well.

Editing and Versioning

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

Note that some changes will result in a new version of the item that will be reflected with an appended version number at the end of the DOI – these include edits to title, authors, and files. The base DOI will resolve to the newest version and all previous versions will also remain publicly available.‍

US Federal Data sharing resources

SPARC – Data Sharing Requirements by Federal Agency

DMPTool – A free, community-supported service that makes it easier to create machine-actionable data management and sharing plans (DMSPs) that meet funder requirements and follow open science best practice.

FAIRsharing Assistant Beta – This Assistant will help you find the standards, databases and policies you need to help make your data FAIR.

NIH data sharing resources

NSF data sharing resources

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

Preparing Your Data Management and Sharing Plan
NSF Proposal & Award Policies & Procedures Guide (PAPPG)

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