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Research Data Management Toolkit: Data management

Best practices in Research Data Management promote research integrity and collaborative opportunities. A Research Data Management Plan ensures data security, accessibility and validation of results.

What is research data?

Research data comes in many formats - including some that you might not think of as 'data'. It might be in spreadsheets, interview transcripts, photographs or geological samples. It is any information that has been collected, observed, generated or created to validate original research findings.

As well organised data is critical for your research, and data sharing has advantages for both you and society, it is important to plan and document how you will manage it. The process of creating a Research Data Management Plan (RDMP) will enable you to understand the nature of your data and the requirements for its management both during and at the end of your research. 

Ensure that data management is funded in your project budget and, if you have a project team, assign a data management role from the start.

The UWA Research Data Hub is your new location for effectively managing your research data throughout your project’s research life cycle and where you can create your online Research Data Management Plan (RDMP). This new enhanced planning tool replaces the existing Research Data Management Plan (DMP) in Qualtrics and links with other UWA systems to streamline data storage requests for your active research data, funding and compliance applications and approvals, and retention and disposal requirements and processes. 

Why is it important to manage your research data?

Effective data management will ensure the responsible conduct of research in several key areas:

  • Compliance with codes of research conduct, funders' and publishers' mandates
  • Efficiency by improving data management, description and consistency
  • Security to safeguard against data loss, and ensure confidentiality and legal compliance
  • Access for verifying results, facilitating collaboration and future use, and preventing duplication of effort. Improving data access may lead to increased citations.
  • Quality in allowing for data replication/reproducibility, increasing reliability, and ensuring data integrity. 

The FAIR Principles are international guidelines to help researchers and data stewards maximise the value of their research data and comply with  mandates for data to be findable, accessible, interoperable and reusable (FAIR).

Why is a Research Data Management Plan important?

Developing a Research Data Management Plan before you commence your research project helps you to consider, document and establish:

  1. Metadata standards which will be used for data formats.
  2. Classification and sensitivity of your research data.
  3. Storage and backup procedures and provisions.
  4. Future access to the research data for sharing and/or reuse.
  5. Retention and disposal procedures and provisions.
  6. Ownership and protection of intellectual property.
  7. Documentation describing all of the above.

Many research funders and research policies require that a Research Data Management Plan has been completed. Some funder requirements are detailed on the Funder requirements tab.

The tabbed pages on this Toolkit will assist you to complete each section of the Plan:

  • Ethics & compliance - this part of the Plan documents if your data is sensitive (and if so, the classification), if there are relevant regulatory controls and who can access it. You also need to consider a data licence to determine how it can be used. 
  • FAIR  - Following FAIR principles ensures that your data is findable, accessible, interoperable and reusable (FAIR). 
  • Collect - you might be collecting your own data, or using another researcher's dataset. You will need to create metadata about this dataset and establish who has ownership of the data, as well as routine upkeep of the data such as version control and quality control.
  • Store active data - carefully consider where your data will be stored, considering the level of security, and where and when the data is backed up. You might also need to store copies of any software that is needed to view or edit the data.
  • Finalise dataset - make decisions about the retention and eventual disposal of your data.
  • Sharing and collaborate - you may need to share your data with your supervisors or collaborators (both at UWA and external), this part of the plan addresses how this will occur, which systems will be used and if there are any ethical considerations.
  • Publish - determine how your data will be published, e.g. in the UWA Profiles and Research Repository.

Contact for support

Email your questions to our friendly library staff.

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UWA Staff

More contact options are available on the Library Contact us page.

Webinar: Research Data 101

Research Data Management 101

This webinar provides an overview of research data management principles and some practical strategies for managing, organizing and preserving research data throughout the research lifecycle. View the recording - UWA login required. 


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