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Recommended Practices in Data Management
The best practice is to have a plan. If these recommendations seem like too much, try to adopt one new good habit every month.
- Writing a High Quality Data Management Plan
Read your funder requirements carefully and address everything they ask you to. Then follow your plan.
- File Management
Have a consistent system and make sure everyone knows it. Don't use spaces or special characters in file names.
- Creating and Using Spreadsheets or CSV Files
Columns are for variables, rows are for records. Label your columns and use consistent terms between records. Don't use color or leave cells blank.
Have roles and responsibilities clearly defined up front. Make sure you save new versions of files when changes are made.
- Document Your Data Using Codebooks, ReadMe Files, and Data Dictionaries
Give at least enough information that future you, a new lab member, or another researcher could make sense of your data.
- Security & Privacy
Password protect and/or encrypt sensitive files. Follow Penn's guidelines for saving sensitive data on PennBox and visit SAS's pages on sensitive data and encryption.
- Data Sharing
Share! And share your documentation so the data is useful. Repositories are the most effective way to share. Find an appropriate repository here or ask us!
- Storing and Backingup Data
Follow the 3-2-1 Rule: 3 copies of your data stored on 2 different types of media with 1 copy in an offsite location. (0 of these copies should be on a flash drive) Want to know more? Watch one of these videos from Explaining Computers or University of Wisconsin Milwaukee's Data Librarian
- Archiving data for the long haul
Use sustainable file formats whenever possible and migrate your data to new media every 3-5 years.
These pages offer some of the recommended practices for managing your data, but -of course- every project and study is different and some practices might not work best for you. Please ask us questions, attend workshops, or set up consultations to figure out how to do best by your data.
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