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Research Data Management: About Research Data Management

Guide on research data management, with resources and tools for data planning, data organization, data documentation, data sharing, data security, data analysis and visualization


This guide aims to support researchers to properly manage their data produced in research, or to openly share their data. 

This guide is collaboratively developed by NUS, NTU and SMU Libraries. 

Why manage data?

Practical Motivations

If you manage your data properly, there are practical benefits such as:

  • Improve your research efficiency through proper organization and maintenance of your data and records
  • Saving time and efforts in the long run, should you need to refer back to your data

If you go one step further to backup your data in a permanent online repository, such as the institutional repository at your university, you will:

  • Minimize the risk of data loss 
  • Increase the visibility and discoverability of your research
  • Opportunities for collaboration through sharing

For the Greater Common Good

  • Ensure research integrity and reproducibility
  • Others could reuse your data to avoid duplication of efforts
  • For public funded projects, there is somewhat a responsibility to make data openly accessible and in a format usable by other people

[Adapted from MANTRA]


Research Data Management (RDM) is how you look after your data throughout your project. It covers the planning, collecting, organising, managing, storage, security, backing up, preserving, and sharing your data and ensures that research data are managed according to legal, statutory, ethical and funding body requirements.

(Source: University of Hertfordshire)

In short, data management means all the processes and actions required to manage data using good practice throughout the research life-cycle for current and future research purposes and users.

(Source: Queensland University of Technology)

“Research data means data in the form of facts, observations, images, computer program results, recordings, measurements or experiences on which an argument, theory, test or hypothesis, or another research output is based. Data may be numerical, descriptive, visual or tactile. It may be raw, cleaned or processed, and may be held in any format or media”. [Queensland University of Technology Management of Research Data Policy]

“The recorded information (regardless of the form or the media in which they may exist) necessary to support or validate a research project’s observations, findings or outputs”. [University of Oxford Policy on Management of Research Data and Records]

[Adapted from Australian National Data Service]

In addition to research data, research data management also covers managing of research records both during and beyond the life of a project. Examples of such research records include:

  • Correspondence (electronic mail and paper-based correspondence)
  • Project files
  • Grant applications
  • Ethics applications
  • Technical reports
  • Research reports
  • Signed consent forms

[Adapted from Defining Research Data by University of Oregon Libraries]

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Data sharing and management

Check out this hilarious short video on the topic of data sharing, storage, documentation and file formats. As a researcher, you SHOULD NOT let this happen!  

Subject Guide

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Pin Pin Yeo
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Librarian, Scholarly Communication

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