This guide was adapted with permission from Temple University's Research Data Management Guide.
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.
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. 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.