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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 is used for your research.
As this data is critical for your research, it is important to plan and document how you will manage it. The process of creating a Data Management Plan 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.
UWA Library has created a Data Management Planning tool in Qualtrics that you can use to create your own Data Management Plan.
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:
- Metadata standards which will be used for data formats.
- Classification and sensitivity of your research data.
- Storage and backup procedures and provisions.
- Future access to the research data for sharing and/or reuse.
- Retention and disposal procedures and provisions.
- Ownership and protection of intellectual property.
- Documentation describing all of the above.
Many research funders and research policies require that a Research Data Management Plan has been completed.
UWA researchers can use our Data Management Plan template to create their plan. The tabbed pages on this Guide will assist you to complete each section of the Plan:
- Data collection - 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.
- Ethics & Legal Compliance - this plart 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.
- Sharing/collaborating - 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.
- Storage & Backup - 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.
- Publication - determine how your data will be published, e.g. in the UWA Profiles and Research Repository.
Example Data Management Plans
Example DMP child allergies study
Example DMP for a research project gathering samples and medical history data from children. Highest level of data sensitivity is Highly Restricted, & data is gathered on specialist medical equipment.
Example DMP endangered frogs study
Example of a Data Management Plan for a research study investigating endangered species population levels. The highest level of sensitivity of gathered data is Confidential Restricted, & the study requires a large quantity of data storage.