What is it?

A Data Management Plan (DMP) describes the data management life cycle for the data to be collected, processed and generated by a Horizon project.

It is a document that describes
1/ what data will be generated by the project,
2/ whether and how it will be exploited or made accessible for verification and re-use, and
3/ how it will be curated and preserved. 

The DMP should therefore include information a) on the handling of research data during & after the end of the project, b) on what data will be collected, processed and/or generated, and c) on which methodology & standards will be applied. It goes without saying that the plan needs to be specific and adapted to the nature of the data. 

A DMP is a living document. Typically you would indicate the outline (core vision/choices you'll follow) in the proposal. Next, a first version needs to be developed during the initial project months (e.g. as a project deliverable in the dissemination WP). This document will need regular updates, especially when significant changes occur (e.g. new datasets, changes in policy). It can be also a best practice to provide an update along with the periodic reporting. A final version needs to be on the list of end-of-project deliverables.

Why is it needed?

A DMP fits in the movement of making research data FAIR: Findable, Accessible, Interoperable and Re-usable. This can be seen as an improvement (because: more nuanced) of open data.

Since EU grants are financed by public funds, beneficiaries are expected to disseminate their project results. In this way, the projects can benefit a larger group of persons and reach wider target groups.

How to create a Data Management Plan?

In most cases, you create a DMP by filling out a template or by answering questions from a checklist.

There exists an official generic template from the European Commission(version of 2021-05-05 also attached to this info sheet) that  describes in 10 (sub)sections the topics that need to be covered.

For more background and additional help, we refer to the OpenAIRE project. Though this is written within the context of the Horizon 2020 Open Research Data Pilot, the main content remains valid and relevant. You'll also find there 8 other guides, dealing with specific issues (e.g. raw data, non-digital data, sensitive data, ...) and the broader context (e.g. assess RDM costs, repositories, ...)

There exist software tools (e.g. DMP online, DMPTool, ...) that help you create a DMP. Typically you'll have to select the appropriate template, after which guidance is provided in the form of a limited set of relevant questions.

Further reading

• You might also want to look at the DCC checklist for a DMP, which is a handy extra tool (based on many best-practices) to review your work.
• PLOS, a nonprofit Open Access publisher, has a journal article on "Ten Simple Rules for Creating a Good Data Management Plan".
• Want to learn from best practices? Check out Data Management Plans in Horizon 2020: what beneficiaries think and what we can learn from their experience, an article by Daniel Spichtinger.
• Also Science Europe crafted an overview page on Research Data Management with information and links.