Introduction to Research Data Management (RDM)

Research Data Management (RDM) involves making decisions about how you will collect and look after your digital and physical research data, and putting those decisions into action. It covers:

  • Data organisation and description
  • Storage and backup
  • Preservation
  • How you make it available to others (where appropriate).

Watch this video to get a brief overview of RDM.

What is Research Data?

Research data is anything that forms the basis of your research output. The types and forms of research data vary between disciplines, however, this general definition is helpful:

Research data: Data are facts, observations, or experiences on which an argument, theory or test is based. Data may be numerical, descriptive or visual. Data may be raw or analysed, experimental or observational. Data includes: laboratory notebooks; field notebooks; primary research data (including research data in hardcopy or in computer readable form); questionnaires; audiotapes; videotapes; models; photographs; films; test responses. Research collections may include slides; artefacts; specimens; samples.
Source: University of Melbourne  Management of Research Data and Records Policy

Provenance information about the data might also be included: the how, when, where it was collected and with what (for example, instrument). The software code used to generate, annotate or analyse the data may also be included.

Research Data Management at Massey University

Here is Massey University Library's guidance and advice for good research data management.

    Manage Your Research Data

    Publish and Share Your Research Data

    Preserve Your Research Data

    Updates on Massey University RDM initiatives are posted on the eResearch Community Blog.

    Research Data Life Cycle

    Some universities use a research data life cycle. The University of Sydney's research data life cycle looks like this:

    Research Data Life Cycle

    Source:

    The University of Sydney https://library.sydney.edu.au/research/data-management/research-data-management.html

    The Benefits of Good Research Data Management

    Watch this 4-minute cartoon to learn about some of the problems that can arise in the absence of good data management practices.

    Increased research efficiency:  you can find, understand and use data when you need it      

    Risk reduction: protects your data against loss, deterioration or privacy and copyright breaches

    Quality: helps to verify research findings over time

    Reputation: shared data enhances research visibility and increases citations

    Compliance support: complies with ethical codes, data protection laws, journal requirements, funder policies.

    Poor management can lead to catastrophes like the loss of data, or the violation of people’s privacy.

    Manage Your Research Data Tool Kit

    Researcher Development

    Contact Us

    Research Data Management Librarian
    Guidance, training opportunities and practical support.

    Research Development Team
    Data management (funder retention requirements) advice for current and future research projects.

    Information Technology Services (ITS)
    Data-related services and advice on storage, backup, security, data quality, and metadata identification. Limited software for home installation.

    Contact a Subject Librarian
    Personal research help by email, phone, or appointment.

    Acknowledgements

    These guidelines are informed by information provided under open licenses by other organisations including:

    Massey Contact Centre Mon - Fri 8:30am to 5:00pm 0800 MASSEY (+64 6 350 5701) TXT 5222 contact@massey.ac.nz Web chat Staff Alumni News Māori @ Massey