Data management plan template

The Swedish Research Council and the Association of Swedish Higher Education Institutions, SUHF, have developed this template with six central parts that a data management plan should cover. The summary is a partially reworked version of Science Europe’s "Core Requirements for Data Management Plans".

Template

In addition to the central documentation below, a data management plan should also include basic administrative information, such as project title, project leader, registration number or corresponding, date and version of the data management plan.

1. Description of data – reuse of existing data and/or production of new data

  • How will data be collected, created or reused?
  • What types of data will be created and/or collected, in terms of data format and amount/volume of data?

2. Documentation and data quality

  • How will the material be documented and described, with associated metadata relating to structure, standards and format for descriptions of the content, collection method, etc.?
  • How will data quality be safeguarded and documented (for example repeated measurements, validation of data input, etc.)?

3. Storage and backup

  • How is storage and backup of data and metadata safeguarded during the research process?
  • How is data security and controlled access to data safeguarded, in relation to the handling of sensitive data and personal data, for example?

4. Legal and ethical aspects

  • How is data handling according to legal requirements safeguarded, e.g. in terms of handling of personal data, confidentiality and intellectual property rights?
  • How is correct data handling according to ethical aspects safeguarded?

5. Accessibility and long-term storage

  • How, when and where will research data or information about data (metadata) be made accessible? Are there any conditions, embargoes and limitations on the access to and reuse of data to be considered?
  • In what way is long-term storage safeguarded, and by whom? How will the selection of data for long-term storage be made?
  • Will specific systems, software, source code or other types of services be necessary in order to understand, partake of or use/analyse data in the long term?
  • How will the use of unique and persistent identifiers, such as a Digital Object Identifier (DOI), be safeguarded?

6. Responsibility and resources

  • Who is responsible for data management and (possibly) supports the work with this while the research project is in progress? Who is responsible for data management, ongoing management and long-term storage after the research project has ended?
  • What resources (costs, labour input or other) will be required for data management (including storage, back-up, provision of access and processing for long-term storage)? What resources will be needed to ensure that data fulfil the FAIR principles?

PublISHED ON 27 November 2020

UpDATED ON 27 November 2020

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