Content is adapted from the Love Your Data website.

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As we reach the last few days of Love Your Data Week, let’s talk about a harder topic – data sharing. Sharing is a great way to give and get credit – it’s also required by some federal funding agencies. Today’s post will introduce you to key components of sharing and provide an activity to help you become comfortable with it. If you have any questions or want to let us know how you shared your data, reach out to us on Twitter!

Respect Your Data – Give & Get Credit

Data are becoming valued scholarly products instead of a byproduct of the research process. Federal funding agencies and publishers are encouraging, and sometimes requiring, researchers to share data that have been created with public funds. The benefit to researchers is that sharing your data can increase the impact of your work, lead to new collaborations or projects, enables verification of your published results, provides credit to you as the creator, and provides great resources for education and training. Data sharing also benefits the greater scientific community, funders, the public by encouraging scientific inquiry and debate, increases transparency, reduces the cost of duplicating data, and enables informed public policy.

There are many ways to comply with these requirements – talk to your local librarian to figure out how, where, and when to share your data.

Good Practice

  • Share your data upon publication.
  • Share your data in an open, accessible, and machine readable format (e.g., csv vs. xlsx, odf vs. docx, etc.)
  • Deposit your data in a subject or institutional repository so your colleagues can find and use it.
  • Deposit your data in your institution’s repository to enable long term preservation.
  • License your data so people know what they can do with it.
  • Tell people how to cite your data.
  • When choosing a repository, ask about the support for tracking its use. Do they provide a handle or DOI? Can you see how many views and downloads? Is it indexed by Google, Google Scholar, the Data Citation Index?

Things to Avoid

  • “Data available upon request” is NOT sharing the data.
  • Sharing data in PDF files.
  • Sharing raw data if the publication doesn’t provide sufficient detail to replicate your results.

Today’s Activity

Take the plunge and share some of your data today! Check out the list of resources below, or contact your local librarians to get started.

If your data are not quite ready to go public, go check out 1-2 of the repositories below and see what kinds of data are already being shared.

If you have used someone else’s data, make sure you are giving them credit. Take a minute to learn how to cite data: