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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 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.

Source: The Queensland University of Technology Management of research data policy.

Also include any information that gives the research data context, so it can be understood and reused. For example: how, when, where it was collected, instruments used, software code used to generate, annotate or analyse the data etc. 

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


    The University of Sydney

    The Benefits of Good Research Data Management

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

    Risk management: 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: comply 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.

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

    Manage Your Research Data Tool Kit

    Researcher Development

    Contact Us

    Contact a Subject Librarian
    Your first point of contact in the library for RDM guidance, training opportunities and practical support. Subject librarians also provide personal research help by email, phone, or appointment.

    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.


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