Manage & Share Research Data

Data management is the sum of a number of small practices that add up to being able to find and use data when you need it. Like taking care of our bodies, preventing problems is easier than fixing problems after the fact.

Consider these foundational practices [1]:

1. Keep sufficient documentation - consider what you, your supervisor, or team members may need to know in a year
2. Organize files and name them consistently - there is no ideal system, just a best system for you and your project
3. Version the files - keep distinct copies of data files as they change over time, manually or through the magic of version control software like Git and Github
4. Create a security plan, when applicable - check out SecureMyResearch
5. Define roles and responsibilities - even if you are working alone, talk with your advisor to make sure you are doing all the necessary work to meet project and degree requirements
6. Back up the data - the best way to prevent data loss is to follow the 3-2-1 Rule: three copies of the data, two geographically separate locations, and more than one type of storage device
7. Identify tool constraints - think about what tools you have to use and investigate what requirements they have for your data input and output; sometimes, applicable data protections like FERPA and HIPAA factor in here, too
8. Close out the project - identify, prepare, and collocate key files to maintain provenance and make it easy to find what you need in the future
9. Put the data in a repository - turn it over to specialists who can ensure discovery and long-term access
10. Write these conventions down in a Data Management (& Sharing) Plan (or readme or the preferred format in your field) - use your plan, review it regularly, and update it as necessary

Some other good practices:

• Make sure the data you plan to collect will answer your research questions. Ask for help with statistics or other analytical techniques so you don't waste time, resources, and data.
• Use common, open file formats whenever you can, like txt, csv, odf, png
• Identify your ethical and legal obligations for handling your research data
  • Intro to the Responsible Conduct of Research
  • SOP for Human Subjects Research

1. Briney, K., Coates, H., & Goben, A. (2020). Foundational Practices of Research Data Management. Research Ideas and Outcomes, 6, e56508. https://doi.org/10.3897/rio.6.e56508

It can be helpful to document your thinking on paper, so you can visualize gaps and get feedback from your faculty advisor. Take some time to write down your research questions, describe the data needed to answer them, and note the characteristics and standards that those data need to meet in order to produce valid answers. You can document this in our Data Outcomes Mapping template (below) or in your preferred tool.