Data Management Resources

The tabs to the left will walk you through the foundational aspects necessary for adopting data management practices, but below are some quick tips. The best practice when starting to practice data management is to have a plan of action and create a habit. 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 Organization
  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.  
• Collaboration
  Have roles and responsibilities clearly defined up front. Make sure you save new versions of files when changes are made. 
• Document Your Data Using ReadMe Files, Codebooks 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 Backing up 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. Zero 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.
• Archiving Data for Preservation
  Use sustainable file formats whenever possible and migrate your data to new media every 3-5 years.

This workshop recording will teach the foundational principles of good research data management. If you struggle with file naming, understanding your files after time has passed, or planning your research process, give it a listen! 

Learners will be able to diagram a data lifecycle of their research process, learn how to develop a file naming process, and learn how to construct documentation for their research. This session is suited for graduate students and faculty conducting research, though advanced undergraduates will also find it helpful. Lesson materials are publicly available for download and viewing. 

This guide, the included recordings, and the included materials that are produced by Lauren Phegley of the University of Pennsylvania are licensed Attribution-NonCommercial 4.0 International (CC BY-NC 4.0).