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Data Management Plan

A data management plan (DMP) helps you manage your data, in terms of organisation, storage and preservation.

Taking the time to write a good DMP gives you an opportunity to think through many of the issues covered in this guide, and usually saves time and effort later on in the process.

Increasingly, funders require a DMP as part of the application for research funding. For instance, as of 2017, a DMP is required for applications to Horizon 2020. As for Sweden, The Swedish Research Council requires a DMP for those projects who reward a grant as from 2019, and who generates research data. The DMP shall describe how data will be managed, during the course of the research as well as afterwards, focusing on central parts described by the Council. You don´t need to send them any documentation, however, the administrating organization (the University) must confirm that a data management plan will be in place at the start of a project, and also that the plan will be maintained. SUHF, The Association of Swedish Higher Education Institutions, have agreed on a recommendation for data management plan (PDF, only in Swedish).

Central parts described by the Swedish Research Council

Recommendation for data management plan (PDF, 179 kB , new tab, only in Swedish)

A DMP is truly useful when it is a living document that is updated throughout the project.

A DMP should include answers to questions such as:

  • What kind of data will you collect or create?
  • How will the data be collected or created?
  • Which documentation and what metadata will accompany the data?
  • Are there ethical issues that need consideration?
  • How will you manage copyright and Intellectual Property Rights (IPR) issues?
  • How will data be handled to insure it is stored and transferred securely?
  • How will the data be backed up during the projects?
  • Which data should be retained, shared, and/or preserved?
  • What is the long term preservation plan?
  • How will you share the data? Are there any restrictions on data sharing?
  • Who will be responsible for data management?
  • Can the resources required be specified and what costs are involved? For instance, personal resources, software and hardware.