Skip to main content

Research Data Management

Research Data Management (RDM)

Responsible data management has increasingly become an expected element of high quality research.

Discussing what is to be collected, the amount being collected (size of files), security of data collected, ownership, responsibility, etc., are issues important not only to the the individual researcher but also to the institution where the research is taking place. Funding body mandates both nationally and internationally are also considering these issues and have placed emphasis on researchers providing evidence of appropriate provision for data management and curation in grant applications.

Why Do Researchers Need Research Data Management?

What is Research Data?

Author/Copyright holder: Ian. Copyright terms and licence: CC BY-NC-ND 2.0

  • Research data could be anything that may be needed to validate the results of research. Not only is it the product of research, it could also be the starting point for new research
  • The format that research data comes in include images, sound/video recordings, artifacts, surveys, questionnaires, interview transcripts, statistical data and analyses, measurements, fieldwork notes
  • Additional definitions of what constitutes data are found on the ANDS (Australian National Data Service) website

What are Research Records?

  • Research Records are the paperwork surrounding and supporting research projects include items such as administrative and research correspondence, forms, clearances, reports, master lists, etc. Records such as these are important to manage during and after the project.

What is Metadata?

Metadata can be described as structured information that describes, explains, locates, or otherwise makes it easier to retrieve, use, or manage an information resource (National Information Standards Organization (NISO). Understanding metadata)

  • Descriptive metadata describes a resource for purposes such as discovery and identification. It can include elements such as title, abstract, author, and keywords, for tables: column and row names, etc.
  • Structural metadata indicates how compound objects are put together, for example, how pages are ordered to form chapters.

  • Administrative metadata provides information to help manage a resource, such as when and how it was created, file type and other technical information, and who can access it.

What Should Data Management Plans Consider?

Basic research data management is required by the Australian Code for the Responsible Conduct of Research. Compliance with the Code is already a requirement for ARC and NHMRC funding and is likely to be mandated by other funding bodies, government and research institutions in the near future.

On the practical side, a data management plan assists in maintaining the longevity and accessibility of your research outputs.

The Research Data Itself:

  • what sort of data do you intend to collect and generate?
  • how will you collect & generate this data?
  • volume of data?
  • any software required?
  • confidentiality and privacy requirements (need to de-identify participants?)
  • quality control considerations?

The ownership, copyright, licensing & intellectual property, sharing of data:

  • who does the data belong to (especially in collaborative projects)?
  • who will have access to the data?
  • intended use of data collected
    • personal use only
    • can the data be sold?
    • intend to share data with other researches through an Open Access Data Repository?
      • apply a Creative Commons license?
      • available after an embargo period
      • available by application (mediation)
      • data completely/partially available

Organising and documenting the data:

  • file formats and version control
  • naming protocols for file names
  • describing data collected (metadata) so it makes sense later on
    • what, where, why,who, how, etc.
    • FAIR concept
      • Findable
      • Accessible
      • Interoperable
      • Re-usable
  • who is responsible for collecting what data
  • quality control

Storage of data and administrative paperwork (preservation):

  • during collection - where will you store the data & the backup copies?
  • post-project storage of data - long term copy, for how long?
  • long term access to data and software to view data
  • ECU Records and Archives Management Services

Compliance with:

  • institutional policies and legislation requirements
  • funder's policies and legislation requirements 
  • standard industrial practices

Possible Sharing of Data:

  • data is collected, organised, and stored keeping in mind it's possible re-use


Finding or Publishing an Open Dataset

Enhance the visibility of your research - publish your Research Datasets on ECU's Research Online Repository.

Open Access Options: What data would you like to share, with whom, when and how (open, mediated, restricted).

Datasets listed on Research Online will:

FAIR: Findable, Accessible, Interoperable and Reusable

The Australian Research Data Services have designed a FAIR self-assessment tool prompts the user with questions related to the principles underpinning Findable, Accessible, Interoperable and Reusable

Books on Research Data Management

Some Tips on How to Create Good File Names

Sharing Open Access Datasets



The FAIR Guiding Principles:

To be Findable

To be Accessible

To be Interoperable

To be Reusable