Research Data Management

This guide provides an introduction to research data management (RDM), including best practices for managing files, documentation and metadata, storage, sharing, reproducibility and preservation. It provides information on creating data management plans, citing data and more.  If you have questions, please contact your liaison librarian or the Library's Research Data Services team.

There are many reasons to have good research data management habits. Most federal funding agencies and more and more publishers are requiring that research data be made publicly available. That's much easier to accomplish if you know where your data is and where you can share it. It's also important to understand your own data over the years and through various lab staffing situations. Organization and documentation of your data and code makes this possible. Backing up your data and storing it in appropriate places helps ensure your data doesn't get accidently deleted during or after a project.

In short, managing and sharing research data helps you get funding, keep funding, and avoid retractions. It aides consistency in data collection and analysis, helps make your data make sense to your future self and colleagues, and helps advance science through replication and enabling new discoveries.

Good data management includes: 

• assigning responsibilities to research group members
• collecting data in a consistent and easily understood way
• follow good file naming conventions
• using standard and non-proprietary file formats
• documenting your data thoroughly and consistently
• backing up data regularly
• making & following through with plans for storage of data for the long term

The Research Data Services Team is happy to help, please visit our site or contact us at tul-rds@temple.edu. We will consult with you or connect you to the right person, resource or service on campus. 

Research Data Services team: