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Data Management Plan (DMP)

In line with the principles of good academic practice, researchers should ensure that they pay sufficient attention to and thoroughly discuss numerous aspects of research data management at the beginning of a project. These aspects include the documentation of the data, their archiving, and their long-term availability after completion of the project, as well as a clarification of the responsibilities and duties of the academics involved.

Recommendations for preparing a data management plan (DMP):

The following points present the essence of a data management plan:


Inspired by: [WissGrid, ANDS, RDM University of Oxford]

1. Description of the project:

General information on the planned project such as goals, funding, and duration

2. Existing types of data:

Description of existing data that can be reused for the project and how their integration could look

3. Data to be created in the project:

Details on the types of data and formats and the estimated amount of data that will be used and created, along with further information on the process of creating the data and quality assurance (such as documentation and validation measures)

4. Data organisation:

Details on consistent data organization within the project (e.g. for data storage, data names, synchronization, versioning, and other collaboration workflows)

5. Administrative and legal aspects:
  • Funding and legal requirements: Taking account of the funders’ and data providers’ requirements and complying with policies (e.g. on data storage in repositories, selecting data)
  • Copyright/Data owner: Defining who is interested in the created data
  • Access and use: Defining access rights and target groups as well as specifying reuse restrictions (both technical and organizational)
  • Data protection: Ensuring data protection for sensitive and personal data and taking account of obligations towards third parties
  • Data security and backup:Defining how data protection will be ensured and giving details on the backup strategy
6. Archiving, sharing, and publishing data::

Which data will be shared? How will data be shared? Information on the planned interoperability with external discipline-specific data services

7. Responsibilities and duties:

How are the responsibilities for data management defined and distributed within the project?

8. Costs and resources:

Reports on the costs and the personnel expenditure for maintaining the data management plan and running costs for data curation, production of metadata, archiving, etc.