Research requires the collection of thousands of pieces of data, produced in multiple forms, and collected and stored over years. That collection needs to be secure and accessible at every stage of the research process. During research, it is never too late or too early to address most aspects of research data management. However, it is best to plan for data management before starting your project to avoid problems later. Data at UQ has valuable guidance on your responsbilities and data.

Before you start gives an overview of what you need to consider for managing your research data, even before starting your project. 

  • During research has the next steps for storing, securing and analysing your research data during the project
  • Ongoing looks at sharing and re-using your research data once your project is completed

1. Grant applications

Australian funding agencies

Australian funding agencies have guidelines and requirements relating to research data management. The National Health and Medical Research Council (NHMRC) requires researchers to address how they plan to manage or share their project's research data as part of their funding agreements. The Australian Research Council (ARC) asks researchers for a data management plan (See section 3 for more details).

You will need to address how you will:

  • plan your research data management
  • store and secure your project's data
  • disseminate and share your project's data
  • make your project's data available for re-use.

Use the UQ Research Data Manager to meet ARC and NHMRC requirements, retrieve storage provisioning for your project and document key elements of your data management plan.

International funding agencies 

Many of the key international funding agencies have very detailed requirements for research data management, with a strong emphasis on sharing,  open, and F.A.I.R data. To improve your chances of success you will need to prepare a research data management plan.

See funding agency requirements for:

Use the UQ Research Data Manager to help you meet funder requirements. Along with provisioning your project with storage, the system allows you to share your project's data with collaborators.

FAIR Data Principles

The FAIR data principles are designed to support knowledge discovery, and promote the sharing and reuse of research data. To gain the most benefit from a dataset it should be:

  • Findable – published with rich, descriptive metadata and with permanent DOIs.
  • Accessible –  through machine readable metadata records online, with open protocols to download datafiles.
  • Interoperable – data uses standard vocabularies/ontologies, and data is stored in open standard formats for reused and integration.
  • Reusable – datasets have clear license conditions for access and use, and well described provenance on where the data came from. Dataset can be cited.

Both ARC and NHMRC policies refer to and support the FAIR principles, and you should consider how you will adopt and apply them to any datasets you generate. The following sections on UQRDM and Data Management Planning will help guide you.