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Data Management: Sharing

This guide serves as a starting point for UNR faculty, students, and staff interested in research data management.


There's lots of reasons to share your data, including furthering scientific research, reducing the cost of redundant data collection, promoting innovation, increasing the impact of your research, and getting credit for your work through data citations. Sometimes grant funders, including the U.S. government, requires you to share your data. More scholarly journals are also starting to require or request that you share your data.

You also have lots of options in deciding where you will share your data, including various data repositories and even data journals. The University of Minnesota suggests considering eight factors when deciding on a home for your data:

  • Cost to access - Does the repository charge any costs to access your data?
  • Certification - Is the repository certified by external organizations?
  • File format - Does the repository allow the file format that your data is most useable in?
  • Preservation - Does the repository take steps to preserve your data for the long term?
  • Persistence - Does the repository provide either a permalink or digital object identifier (DOI) that allows others to cite and find your data without fear of broken links?
  • Longevity - How long will the repository retain your data? Is the repository grant funded? If so, how long will it be funded?
  • Curation - Does the repository provide support for documenting and depositing your data?
  • Rights - Does the repository make your rights as a depositor clear? Is it clear about which rights and licenses can be applied to your data?

Data Repositories

At the University of Nevada, Reno

General Data Repositories

Subject-Specific Repositories

Citing Data

Data citations help give credit to those who collected and shared the data while also providing transparency about where data came from and what version it is. Some of the data repositories generate citations in different styles for their datasets. If you're not sure how to cite a dataset, follow the general rules of whatever style you're using and include this information as applicable:

  • Creator
  • Publication Year
  • Dataset title
  • Version number
  • Publisher (can be name of the archive or repository where the data is stored)
  • Identifier (DOI or permalink)


Data Journals

Some journals publish data papers, which describe a particular dataset vs. drawing conclusions from data. Many of these journals are also peer reviewed. Check out Katherine Aker's post for a list of data journals or contact your librarian if you would like help finding one.