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Research Data Management: 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

Introduction

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]

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

  • Improved research efficiency through proper organization of data and records
  • Savings in time and efforts in the long run
  • Ensure your research is reproducible and able to withstand scrutiny 

You are also encouraged to share your data in an established data repository, in order to reap the following benefits: 

  • Minimize the risk of data loss 
  • Increase the visibility and discoverability of your research
  • Opportunities for collaboration through sharing
  • Uphold research integrity and reproducibility
  • Others could reuse your data to avoid duplication of efforts
  • Some funders may require researchers to make data openly accessible and in a format usable by other people

[Adapted from MANTRA]

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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!  

Librarian, Scholarly Communication

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