Research data management (RDM) involves organizing, documenting, storing, archiving, and sharing both digital and physical research data. Data management is essential across the entire research data life cycle. RDM aims to ensure the reliability of research results and encourages new and innovative research based on existing information. RDM is integrated into the research process to enhance efficiency. Data management applies throughout the entire research data life cycle, which is visualized in the cycle below.
Image from Pao Yue-kong Library, RDM Libguide.
![](https://d2jv02qf7xgjwx.cloudfront.net/accounts/349379/images/Screenshot_2024-06-05_150029.png)
This LibGuide provides guidance on research data management planning, including strategies for data storage, protection, archiving, and other related resources. The Data Management Plan outlines the execution of these activities throughout the research project.
While research projects have their own lifespan, research data can have a life beyond its' original project. Managing your research data during collection, storage, analysis, publication and making provision for access to it after the conclusion of your project is crucial to the scientific community.