Managing Research Data

What is research data?

Research data is a term used to describe a wide selection of different content developed and used throughout a research project. All disciplines use and produce research data. 

This could include 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. 

Below are some examples of the different types of research data you may use or create during your research.

This includes

  • any responses from focus groups, surveys, and questionnaires
  • laboratory notebooks
  • field notebooks
  • interview transcripts
  • sound recordings – Including music and interview recordings
  • video recordings
  • photographs
  • graphs
  • diagrams
  • maps
  • results from experiments
  • code for data analysis
  • code for data creation
  • instrument data
  • sensor generated data
  • plant samples
  • shells
  • artefacts from an archeological dig
  • biological samples
  • slides
  • Draft of creative written works
  • Sheet music prepared for a performance
  • Sketches created before a final visual piece is created.

What is a Data Management Plan and why do I need one?

Data Management Plans are living documents that are designed to help you manage your research data throughout your project and set guidelines for its usage and management after the project is completed.

CQUniversity requires a Data Management Plan (DMP) to be created for every research project undertaken by both staff and students. University policy also requires that plans are reviewed annually to ensure they are up to date. 

Data Management Plans are created using CQUniversity Data Manager.

Data Manager

Data Manager is the system used to help you manage your research data from the start of the project all the way through to publication. Data Manager includes two forms that will support different steps of your research journey: 

  • The Data Management Plan (DMP), a living document that will evolve as you work with your data - creating, manipulating or analysing it.
  • Dataset records will be made for distinct sets of data when they are completed. There may be a single dataset associated with the entire research project or multiple datasets over the project duration. The dataset record also allows you to publish a record of your dataset to CQUniversity's Institutional repository, aCQUIRe, directly through CQUniversity Data Manager.

Details on how to use Data Manager are available on the Research Data Management Library Guide.

RHD students please note: You will need to use your affiliate log in (your email) to access the system. 

Frequently Asked Questions

Prior to uploading the data to aCQUIRe you will need to create a Data Publication Record via CQUniversity Data Manager. Instructions on how to this are available from the Data Management library guide.

Once the Data Publication record has been submitted for review, add the files to aCQUIRe using the following steps:

  1. Go to aCQUIRe
  2. Click the red Log in link at the top right hand side of the screen.
  3. Enter your university assigned username and password and click Login. 
  4. Click on the Title of the dataset you need to add files to.
  5. Untick the metadata only checkbox at the top of the pop up.
  6. Upload your files. You can either:
    • Click the red browse link at the top of the page and select the files to upload.
    • or, drag the files onto the box with the dotted border at the top of the page.
  7. Wait for the files to upload. This may take some time. All files will be listed with their File Size next to their name.
  8. Tick Publish. You will be prompted to check the licence you've assigned and the terms of use.
  9. Click Save Changes. 

If you have any questions, please email

Research data can be published directly to CQUniversity’s institution repository, aCQUIRe, via Data Manager. When you publish a dataset to aCQUIRe it will receive a DOI (Digital Object Identifier) which will facilitate access to the data. Instructions on how to deposit datasets are available from the Research Data Management Library guide. 

There are 3 options available for publishing and sharing your research data.

  • Open Access – The simplest way to share your data. The data can be downloaded by anyone directly from aCQUIRe.
  • Mediated access – An option for publishing certain sensitive datasets. While not available to the public, researchers can contact you, the dataset creator, to request access to the dataset.
  • Citation Only – These records will include only the metadata about the dataset, but not the data itself. This option can be used to increase discoverability of your research through linked publications. Citation Only records are suitable for many types of sensitive data (medical/cultural/patented) or to link to datasets published on other platforms.

Instructions on where to select this type when publishing are available from Publishing Your Dataset on the Research Data Management Library guide. 

For data published via Open or Mediated Access a license must be applied to indicate how the data can be re-used. The most common license for datasets is the Creative Commons (CC) license. There are a number of different elements in a Creative Commons license, as outlined below.

The default element: CC-BY – The base for all licenses and the most open. Allows for reuse and adaptation with citation. 

Three other elements can be added to the CC-BY license in any combination: 

  • NC – Non-Commercial – The content cannot be used for any commercial purposes like resale or advertising.
  • ND – Non-Derivative – The content cannot be changed or modified in any way and must be used in its entirety, without the user obtaining additional permission from you. (This is NOT recommended for research data as it significantly limits the usability of the data for further study).
  • SA – Share Alike – Any work created using this content must also be shared under the same CC license.

Further information about these license options can be viewed at

For code and software datasets there are some other license types that may be more suitable. Click on any license to see more details about it: