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Research data management

Research data management covers the planning, collecting, organising, managing, storage, security, backing up, preserving, and sharing your project's data.

Working with data

Metadata is often referred to as "data about data". It is structured information used to describe your research data, making it easier to discover, retrieve and reuse. UQ Research Data Management policy requires appropriate metadata be collected and stored along with the research data.

Metadata is important for:

  • Discovery (title, keywords, project description)
  • Evaluation (methods, dates, etc)
  • Reuse (information on variables, software/hardware required, access and reuse conditions)

For a thorough overview of metadata creation and collection for research data read the ANDS Guide to Metadata

Establish whether any standards apply in your research area and collect appropriate metadata for your discipline. Journals and data repositories will also indicate what metadata they require, so check these before you collect your project's data.

Managing your project's data files is an important part of organizing, using, sharing and keeping track of your research. Decisions made about data files may impact how the data can be analyzed, stored or used in the future.  You will need to consider:

Data types and formats

Where possible choose data formats that are non-proprietary or open and sustainable, as this improves the chances of interoperability and re-use of the data in the future.

For more advice on formats read the ANDS Guide on selecting formats, or look at the UK Data Archive's table of recommended formats.

File naming conventions

File and folder naming conventions support efficient use of your project's data, and make the data accessible to researchers over time. Choose descriptive, meaningful file names  that can be clearly understood. Document the convention chosen and ensure it is followed consistently.

Version control

Research data can undergo a number of changes throughout a project, and managing the versions and iterations of your project's dataset is important to ensure the integrity and validity of your work. Document a system for tracking versions, updates, and changes made, and ensure it is followed consistently. Where possible, look at version control tools or software. Get more ideas on data versioning.

Researchers have a number of options for storing research data at UQ. Use the matrix below to assess which is best for your project's data.

UQ Research Data Storage Options




UQ Research Data Manager System Logo





Research Data Manager AARNET Cloudstor UQ OneDrive (or Google Drive) QRIScloud

Complies with UQ RDM Policy

yes no no yes
On-site yes no no yes
Off-site or multiple locations Yes Yes Yes No
Sensitive Yes Yes No No
Human Data Yes No No No
Share with UQ Researchers Yes Yes Yes Yes
Share with (Australian) external collaborators Yes Yes Yes Yes
Share with international collaborators Yes Yes Yes No
Collaborate Yes No Yes Yes
More than 1TB


No No Yes
Archive your data Yes No No Yes


Being sensitive does not necessarily prevent research data from being shared and re-used if appropriate steps have been taken. It does, however, require additional management to maintain privacy, confidentiality and avoid misconduct.

Sensitive data includes (but is not limited to):

  • Human health and personal data, including information about secret or sacred practices; or
  • Ecological data that may place vulnerable species at risk.

You will need to:

  • determine if data is sensitive by checking the ANDS definition, your ethics and consent documentation, and any legal obligations.
  • manage data appropriately by securing and backing up data, using access controls and protocols, documenting security guidelines and ensure they are followed.
  • take steps to prepare data for sharing such as de-identifying, anonymising, aggregating, and developing licensing and access protocols

  • Inform yourself on the ethics and best practice of sharing sensitive and confidential data


Just as researchers routinely provide a bibliographic reference to sources such as journal articles, reports and conference papers, Data Citation is the practice of providing reference to datasets. Citing data like other sources, also acknowledges the author, increases its validity and significance within the scholarly communications cycle and can be counted and tracked (in a similar manner to journal articles) to measure impact.

Making your project's data openly available may lead to an increased citation rate for your publications.

UQ researchers should aim to include data citation in their research practice:

The UQ Research Data Management Policy requires that researchers must retain Research Data in a durable, indexed and retrievable form, for at least as long as the relevant archives or records keeping acts, national codes or funding bodies require.

This ensures long term discoverability and access to the data. Appropriate curation ensures it can be re-used and reanalysed in the future. UQ's Research Data Manager system and the Library's eSpace repository are both able to preserve research data for the future. You can support the effective curation of data by choosing file formats that minimise digital obsolescence (usually open source), and providing appropriate metadata for your project's dataset.

How long should I keep my project's data?

Retention periods may be defined by the funding body, archives or record keeping Acts, or UQ policy. Refer to the following for detailed information:

UQ Research Data Management Policy 4.20.06

UQ Records Management Policy 1.60.04

Australian Code for the Responsible Conduct of Research

Queensland Archives University Sector Retention and Disposal Schedule

Not all research data is suitable to be retained, and the policies listed here will guide you on what data should be permanently destroyed.

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