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Research Data Management : Planning

An introduction to research data and research data management (RDM) for researchers at Murdoch University

Data Management Plans

Why is data management planning important?
It is good research practice to manage your research data and this begins with planning. Data that you create, compile or collect during your research is a valuable asset that needs to be cared for over long periods of time. Planning at the start of a new research project will save time and resources. Funding bodies, government and research institutions, and publishers may require researchers to provide details of their data management plan or to share their data, and this may be mandated in the future.

Creating a data management plan will also:

  • Document your research data management activities
  • Identify areas of potential difficulty or conflict that need to be resolved with your supervisor or chief investigator
  • Identify data management services and tools available and outline how to access them

What is a data management plan?
A data management plan is a document that describes the data that will be created, the policies that will apply to the data, who will own and have access to the data, the data management practices that will be used, the facilities and equipment that will be required, and who will be responsible for each of these activities.

What should be included in a data management plan?
A data management plan should consider the following:

Project information The data to be generated or collected during the research project and who is responsible for the collection and management of the data, as well as documentation and metadata.
Intellectual property Ownership, copyright and intellectual property in relation to the data.
File formats and standards The volume of data may need to be considered.
Storage and backup The storage of both digital and physical data during the project.
Sharing and reuse Confidentiality and privacy requirements in relation to the data and any ethical requirements.
Retention, archiving and disposal The retention period for the data,  post-project storage, and access to and re-use of the data including potential repository and archival storage.
Repurposed data Sourcing and managing data used but not created by the project.
RDM plan and your discipline How can your RDM plan be adapted to the requirements of a specific discipline (where necessary) ?

The ANDS website has further information on data management planning, as well as links to examples of plans from other research institutions. 

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