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Research Data Management (RDM): What is Research Data Management

One stop shop for all things related to Research Data and how to manage your data throughout its entire lifecycle


Research data management (RDM) is about collecting, caring for, using, preserving and sharing the data supporting your research. It encompasses all practices and actions to ensure that research data are secure, sustainable, easy to find, understand and reuse.

Key elements of RDM include:

  • how to store your data and back them up effectively so that they are protected against corruption and loss
  • how to organise your data, using meaningful file names and logical folder structures and applying version control to modified files
  • how to document your data, so that you (and others) can understand what the data are, how they were collected/generated, and how they have been processed and analysed
  • how to process personal and confidential data, to ensure that sensitive data is protected
  • how to preserve and share your data so that they can be consulted and re-used by other researchers, usually by using suitable data repositories

RDM starts with data management planning. A number of funders ask for a data management plan (DMP) to be completed as part of a grant application, and it is always advisable to create a DMP for any research project involving the collection of primary data.

RDM is especially important when applied to primary data, i.e. new data collected or generated in the research activity. Because these are new and, in many cases, are essential to validating your research findings, it is important to ensure they are properly curated from the beginning.

While you are not responsible for the preservation and sharing of secondary data that you use in your research, you will still need to consider a number of issues, including: how and on what terms are the data to be accessed and used; where and how any copies of data will be stored; and whether the data provider allows copies of the data or derived data to be distributed.


Importance of RDM

  • Helps to maintain reliable and accurate data throughout the research process 
  • Facilitates data reproducibility and reuse after completion and validation of results, making the best use of public resources  
  • Helps to provide clarity for everyone involved – who owns the data, who is responsible for managing the data during and at the end of the research 
  • Communicates research results responsibly, enabling others to replicate outcomes and reducing duplicate data collection 
  • Helps to increase the impact and visibility of your research 
  • Enhances data security and minimizes the risk of data loss  
  • Meets publisher and funder requirements for access to data 
  • Well-described and shared data can increase collaboration, citation and opportunities for funding. 

  • Meets organisational custodial and curatorial responsibilities for research data  
  • Helps researchers to comply with Institutional data management and storage policies.

Benefits of RDM

Implementing good RDM practices takes effort and time. But it also yields significant benefits for yourself, the research community, and society at large.

No wonder RDM is increasingly considered an essential part of good research practice!


  • Enhances the visibility, citations and impact of your research
  • Enhances data security and minimising your risk of losing valuable data
  • Increased your research efficiency
  • Opportunities for collaboration
  • Career recognition
  • Decreases risk of non-compliance


  • Facilitates data finding and re-use
  • Prevents duplication of effort by enabling others to use your data
  • Ensures research data and records are accurate, complete, authentic and reliable
  • Enables new research and new insights into the data
  • Valuable data is protected
  • Supports and reinforces research quality, integrity and reproducibility


  • Efficient use of public resources
  • Better quality research can lead to better decision making
  • Opportunities for citizen science
  • Increased transparency and trust in science

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