Here you will identify the data that will be collected or used to answer your research question, and will plan for data management throughout the lifecycle. A key component of this step is to start a Data Management Plan. Many public funders of research, as well as ethic committees ask for a data management plan to be submitted as part of their application.
| Data Management Plan (DMP) |
A Data Management Plan or DMP is a document that specifies how research data will be handled both during and after a research project. The DMP is a very useful planning tool and you should write your DMP as early as possible in the research project, as it will help you to plan for processes such as ethical approval, data protection requirements, short and long term storage of the data and future data sharing, publishing and re-use.
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Treat your DMP as a living document. Create it before or in the early stages of research, and update it where necessary during the project. You may not know all the answers at the start of your project and it can be updated periodically as the project progresses, or if there are any significant developments. |
Many public research funders and ethics committees (including CDU HREC) require a data management plan to be submitted as part of their application.
What to include in DMP
A good DMP takes into account the applicable regulations and data policies and considers the whole research data lifecycle.
It typically addresses the following topics:
✦ What data will be collected, and how.
✦ How data will be documented.
✦ How any ethical and legal issues will be dealt with.
✦ How data will be stored and backed up during research.
✦ Any plans for preserving (some of the) data beyond the project's end.
✦ Any plans for sharing or providing access to (some of the) data.
✦ Who will be responsible for data management, and what additional resources may be required.
✦ What to cover in your DMP may also depend on your funder, who may provide their own DMP template.
It can be difficult to start with an empty page, but luckily recommended by CDU DMP Tool, contains a DMP template and provides guidance on what to describe in each section. To get access the CDU version of DMP Tool, you need to create an account using a CDU email. Instructions to sign up and log are included below.
Charles Darwin University recommends completing the RDM and Primary Materials Checklist as part of the DMP and provides a full DMP template
Reusing Existing Data
If you consider using secondary data in your research, it will also need to be outlined in your Data Management Plan.
Secondary data are intellectual property belonging to another party, so they may only be used with that party's permission and subject to any terms specified by the provider.
You will also need to consider issues of data management, as you would for primary data, such as:
It is recommended that as part of your data management planning you:
Why reuse existing data
For example, because it:
How to find existing research data?
Finding research data can prove challenging given the amount of data that is currently available and the diversity of possible data sources and formats.
Research data that are shared following the FAIR principles (with a persistent identifier and rich metadata online in a searchable resource) are more easily findable than data published on personal websites or data included as supplementary material to a journal article. Datasets that follow FAIR principles usually published in Government and Subject Data Repositories.
For more information refer to the 'Find Open Datasets' guide.
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RDM and Primary Materials Checklist |
This checklist will help you create a data management plan to manage the data and primary material needs of your research project.
Data management needs vary between projects depending on their discipline and scope.
Use this checklist as guidance to assemble your plan in a document you can share with your supervisor.
For help with completing the checklist and assembling your plan, contact your supervisor (if you're an HDR student) or your project lead (if you're a staff researcher). Alternatively, speak to a Research Data Librarian for further assistance.
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