Research Data Management (RDM) refers to the organization, storage, preservation, sharing, and documentation of data collected and used in a research project. It encompasses the entire data lifecycle, from planning and collection to analysis, sharing, and long-term preservation. RDM ensures the accuracy, reliability, and accessibility of research data, and ultimately benefits the discoverability and longevity of your research.
More funding agencies and academic journals also require the submission of research data along with data management plans to promote open access and reproducibility of research. RDM's structured approach to managing data is the success factor to fulfil the funders' and journal publishers' requirements and to align with the FAIR (Findable, Accessible, Interoperable, and Reusable) Principles.
In the following sections - Overview and the Four RDM Stages, we will cover the key concepts of RDM and explain why it is an indispensable element for a research project. Also, we will elaborate on the components of Data Management Plan and share the best practices for developing a robust and pragmatic DMP. Lastly, we highly recommend the CityUHK customized online DMP Writing Platform - DMPTool@CityUHK to you, the smart assistant for developing DMPs with ease and efficiently.
For enquiries, please contact the Library's Research Data Management Services of the Research Support and Scholarly Communication Section at lbrdms@cityu.edu.hk
