This is ‘Love Your Data‘ week, and each day we’ll be sharing a post about one or more fundamental data management practices that you can use. Part 4 of 5. Parts 1, 2, 3, 4, and 5
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.
- 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 repository or our institutional repository so your colleagues can find and use it.
- Deposit your data in the UO repository (Scholars’ Bank) 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 via PDF files.
- Sharing raw data if the publication doesn’t provide sufficient detail to replicate your results.
If your data are not quite ready to go public, go check out the ones listed below under Resources, or this list of repositories 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. Check out our information on how to cite data, or look at these resources:
- DataCite: Format your citation (tool)
- DataONE Data Citation one-page handout
- APA 6th Style: How to cite data
- Other examples from Michigan State University
How was the deposit process? Easier or harder than you expected?
What do you need to do before you can share your data?
What do you like or dislike about the repository?
Are people sharing data that is similar to yours?
- NIH Data Sharing Repositories
- Open Access Directory: Data Repositories
- Joint Declaration of Data Citation Principles