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), which recently released a new policy requiring Data Management and Sharing Plans beginning in January 2023. The requirement for DMPs and data sharing is similar with national research funders in many countries as well as with private funders; A few examples include: Canadian Institutes of Health Research and Canadian funders, China, European Research Council, Qatar National Research Fund, Swiss National Science Foundation, Swedish Research Council, UK Medical Research Council, UK Economic and Social Research Council, Australian National Health and Medical Research Council, Wellcome Trust, Moore Foundation, and Gates Foundation). Even if a DMP is not required by a funder or institution, considering plans for data management and sharing proactively at the start of a project is an excellent research practice.
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. Both general best practices for data management and archiving, should be considered as well as any discipline-specific practices for file formats, metadata, and documentation that would support discovery and reuse of the data. If your research involves human subjects or other sensitive information, ethics, consent, and de-identification of data should also be addressed.
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.
You may also find our Guide to Best practice for managing your outputs on Figshare helpful.
The use of an established repository (see Re3data for information on more than 2,000 research data repositories), whether discipline-specific, general, or institutional, has many benefits over sharing data via a website or a link to a file in the cloud. Established data repositories follow community standards for metadata, indexing, security, and preservation so that researchers can share their data following these best practices without having to worry about this infrastructure. This allows open data in a repository to be more FAIR (findable, accessible, interoperable, and reusable) and to have a greater impact including to be downloaded, reused, and cited so researchers can get credit for their shared data.
Some funders recommend a variety of data repositories or repository characteristics for researchers to consider (e.g. NIH, DOT, Gates, Wellcome). If there is a repository that is specific to the 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 like Figshare 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. Figshare’s repository infrastructure is trusted by over 150 research institutions to make their research openly available. Since its founding in 2011, Figshare has provided a way for researchers to openly publish all of the results of their research, including everything from tabular data to images and video to articles to software and code. Figshare makes it easy to share your data in a way that is discoverable and reusable and to get credit for all of your work.
Figshare offers several key advantages for data sharing:
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