A data management plan is a document, usually only 2-3 pages, that outlines how you will manage (and share!) your research throughout the entire research project. This is typically completed at the beginning of a research project (or during a grant proposal) and encourages thinking about and planning early for research data management needs. They typically include essential information about how you will collect, store, describe, and share your data.
Benefits of a data management plan:
While a DMP can be beneficial to all researchers, they are required by many research funders, particularly federal research funders. See the links below for some of the most relevant research funders that require DMPs.
A checklist of elements to be included in a solid Data Management Plan.
|Did you include...
|Questions to consider
Types of data to be collected or created
|What type, format and volume of data?
Do your chosen formats and software enable sharing and long-term access to the data?
Are there any existing data that you can reuse?
Data collection method and organization
|What standards or methodologies will you use?
How will you structure and name your folders and files?
How will you handle versioning?
What quality assurance processes will you adopt?
Roles and responsibilities of project members
|Who is responsible for implementing the DMP, and ensuring it is reviewed and revised?
Who will be responsible for each data management activity?
How will responsibilities be split across partner sites in collaborative research projects?
Will data ownership and responsibilities for RDM be part of any consortium agreement or contract agreed between partners?
|Is additional specialist expertise (or training for existing staff) required?
Do you require hardware or software which is additional or exceptional to existing institutional provision?
Will charges be applied by data repositories?
|Metadata and documentation
|What information is needed for the data to be to be read and interpreted in the future?
How will you capture / create this documentation and metadata?
What metadata standards will you use and why?
Storage and backup of data
|Do you have sufficient storage or will you need to include charges for additional services?
How will the data be backed up?
Who will be responsible for backup and recovery? How will the data be recovered in the event of an incident?
Access and privacy requirements
|What are the risks to data security and how will these be managed?
How will you control access to keep the data secure?
How will you ensure that collaborators can access your data securely?
If creating or collecting data in the field how will you ensure its safe transfer into your main secured systems?
|How will potential users find out about your data? With whom will you share the data, and under what conditions?
Will you share data via a repository, handle requests directly or use another mechanism?
When will you make the data available?
Will you pursue getting a persistent identifier for your data?
How will the data be licensed for reuse?
|Data Sharing Restrictions
|What action will you take to overcome or minimize restrictions?
For how long do you need exclusive use of the data and why?
Will a data sharing agreement (or equivalent) be required?How will you protect the identity of participants if required?
Are there any restrictions on the reuse of third-party data?
Will data sharing be postponed / restricted e.g. to publish or seek patents?
Archiving plans for project completion
What data must be retained/destroyed for contractual, legal, or regulatory purposes?
|Long-term preservation plans
|Where e.g. in which repository or archive will the data be held?
What costs if any will your selected data repository or archive charge?
Have you costed in time and effort to prepare the data for sharing / preservation?
How will sensitive data be handled to ensure it is stored and transferred securely?
Adapted from DCC. (2013). Checklist for a Data Management Plan. v.4.0. Edinburgh: Digital Curation Centre. Available online: http://www.dcc.ac.uk/resources/data-management-plans