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Research Data Management

Data Management Planning

A Data Management Plan (DMP) contains all the information related to managing the data for your project. Many funders and institutions require a data management plan to be attached with the funding application. Individual funders may have different requirements, but generally the DMP describes:

  • Which data will be collected, processed and/or generated
  • The stakeholders and roles in the data collection, processing etc. during the project
  • The handling of the data during the project and the long-term archiving solutions
  • Sharing, ownership and privacy aspects

A typical DMP contains the following sections:

Section Typical content

General description of the dataset

 What kinds of data are you using? How will it be collected or produced? What's the estimated size of the data?

Documentation and metadata (formats, standards)

 How do you ensure that your data is FAIR? What kind of formats, standards and documentation are you using? Do you have a field-specific vocabulary, for example? What kind of software or tools are needed to access the data?

Ethics and legal compliance

 How do you comply with laws and regulations? How do you protect confidentiality? Required especially if you are handling personal or otherwise sensitive data

Access, sharing and privacy during the project

 Which platforms and tools are you using to store and access the data? How will it be backed up? Who can access the data during the project?

Reuse and redistribution of data after the project

 Which part of the data will be published and where? What kind of license will be used?
Roles, responsibilities and resources Who will be responsible for different aspects of the data management? Who is paying the cost?

Tools for Data Management Planning

The most commonly used tools for DMPs are DMPTool and DMPonline. Both are free tools that include a variety of templates and guidelines based on funder and institutional requirements. You can also view published plans and share your plans with others.

How to create a brilliant DMP?

An ideal plan…

  • Has a clear structure and is easy to understand
  • Presents the value and usefulness of the dataset
  • Considers risks and risk management
  • Focuses on data management instead of research methods
  • Explains relevant legislation
  • Describes ownership of data
  • Has a clear plan for data sharing and future usage
  • Describes backups, access control and responsibilities
  • Prepares for the selection of data to be archived and proper destruction of unnecessary data
  • Includes the costs of RDM

Source: Think Open Blog by University of Helsinki

See also Digital Curation Centre’s Checklist for a Data Management Plan

Example Data Management Plans