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Research Data Curation and Management: Home

This guide is intended to support researchers to effectively manage their data and to help them in fulfilling data management and sharing requirements from grant funding agencies. This is collaboratively developed by NUS, NTU and SMU Libraries

About Research Data Management

RDM - Research Data Management - 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. [University of Hertfordshire]

The Queensland University of Technology Management of research data policy states:

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.

Research data represents significant value to researchers and the University, and good stewardship of research data is necessary to validate the outcomes of research, and maintain the integrity of research results.

The benefits of managing your data include:

  • Ensuring research integrity and reproducibility.
  • Increasing your research efficiency.
  • Ensuring research data and records are accurate, complete, authentic and reliable.
  • Saving time and resources in the long run.
  • Enhancing data security and minimising the risk of data loss.
  • Preventing duplication of effort by enabling others to use your data.
  • Complying with practices conducted in industry and commerce.
  • Facilitating the analysis of change, by providing data with which data at other points in time can be compared.
  • Meeting funding body grant requirements (if applicable)

[Source: MANTRA]

It is universally acknowledged that researchers are interested in data of all kinds, regardless of origin or type. This presents a challenge to the institution developing policies around the management of research data, both digital and non-digital. What should be included? Can anything be excluded?

Below are some of the recognised definitions of research data:

“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”.

[The 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”.

[The University of Oxford Policy on Management of Research Data and Records]

 

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Research records to manage

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 the University of Oregon Libraries.]

Importance of data management

Professor Lynn Jamieson, Centre for Research on Families and Relationships, University of Edinburgh, talks about the importance of data management in research.

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