Best 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.  
   
• 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 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 "best 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.

Also search Research DataQ for answers

Resources

Funding Agency Public Access Plans (CENDI.gov)

Funding Agency Public Access Plans (SPARC)

Links to School-specific guidance on data management

• SEAS
• SAS

Additional Learning Opportunities

• Research Data MANTRA - free online course for those who manage digital data as part of their research project
• Reseach Data Management and Sharing - Free course offered through Coursera
• Data Management Education Modules from DataOne
• Mozilla Labs Open Data Primers - great resource with even more advice on making your data open

• Statistical Software Overview
• Workshops on Data Management (COMING SOON!)

Workshop Series

All sessions are at 12pm in the WIC Seminar Room 124 in Van Pelt

Sessions are all stand-alone - you do not have to go to them in order. All sessions encourage discussion and questions. You're welcome to bring your lunch.

September 12

DMP Best Practices
Data management plans (DMPs) are becoming common requirements when applying for funding. This session will teach you what DMPs are asking of you, why they're more than a burdensome requirement, and how to follow the plan you create.

September 26

File Management: Keeping it all together
Learn about file naming and organization best practices and sustainable file types. You'll leave knowing best practices for naming and organizing files in ways that work for you.

October 10

Documenting Your Data for the Future
Learn how ReadMe files, code books, data dictionaries can help you make sense of your data in the future and how more formal metadata can be beneficial as well. You'll leave being able to decide which documentation practices exist, and which will work best for you, to describe your data better, and work more knowledgeably with metadata.

October 24

Other People's Data: What even is this?
Learn about reusing and interpreting other people's data. You'll leave knowing how to look for an employ data documentation and do some basic data cleaning for reuse.

November 7

Storage & Backup for Your Data
Learn about storage and backup best practices and why preservation and archiving might also be useful in ensuring access to your data for the long term. You'll leave knowing better habits for backing up and storing your data and understanding the differences between backup, storage, preservation, and archiving.

November 28

Data Visualization Best Practices
Learn about some basic things to keep in mind when creating visualizations of your data. You'll leave knowing how to make your visualizations accessible and more understandable. This is a very basic tips session on chart choice, color selection, and common mistakes that take away from meaning.

December 5

Ethical Considerations When Working with Data
Hear some classic data horror stories about personally identifying information being shared and other unethical practices for data researchers. Learn how to avoid making the same mistakes.

Consultations and workshops are available upon request. Contact mjanz@upenn.edu to discuss needs.