Data Management Plans

A data management plan (DMP) is a structured document that helps researchers systematically describe how data will be handled during and after their research project. DMPs outline methods for collecting, documenting, storing, securing, sharing, and preserving data, ensuring that the information is managed responsibly and remains useful in the long term.

Why can DMPs help?

• Clarity and compliance: DMPs help clarify responsibilities and ensure compliance with institutional and funder requirements, such as the need for data to be findable, accessible, interoperable, and reusable (the FAIR principles)1.

• Long-term value: By specifying procedures for data preservation and sharing, DMPs maximize the value and usability of research outputs and reduce the risk of data loss.

• Transparency and collaboration: DMPs foster transparency within research teams and facilitate collaboration and data sharing, which strengthens scientific integrity and supports reproducibility.

• Efficient workflows: Structured planning improves efficiency in data handling, saving time and resources over the course of a project.

Most importantly, creating a DMP enables proactive planning and anticipation of issues in data handling and sharing. When starting a new research project, researchers are trained to consider various aspects of their work plan, including the experiment’s layout, technical feasibility, control groups, and data endpoints, to draw conclusions about their research question. However, there is a risk of overlooking challenges in data handling along the way. This might be due to, e.g., unawareness of how proprietary file formats can be accessed, underestimating the data volumes generated (particularly in bioimaging experiments), and a lack of knowledge about best practices for sharing data alongside research results presented in a peer-reviewed publication.

Writing a data management plan helps to trigger these important considerations as part of your research work!

For whom are DMPs helpful?

• Individual researchers: DMPs help researchers stay organized, align with best practices, meet funder or publisher mandates, and preserve their own data for future use.

• Research infrastructures and consortia: Organizations like Euro-BioImaging emphasize that good DMPs support data interoperability and integration across sites and disciplines2.

• Core facilities and service providers: Practical guides show that service-oriented entities (like core facilities) benefit from using DMPs as a framework for handling complex workflows and ensuring clear data stewardship for all users3.

Getting started with DMPs

Numerous templates and tools to create a data management plan exist. For examples, templates might be tailored to a specific programme funding line like a Horizon Europe project call. If the goal is to submit a DMP along with such a proposal, these templates help to guide through the relevant questions.

Find an overview of DMP tools in the ELIXIR RDM kit.

Data management planning for bioimaging projects

If you’re looking for a DMP template tailored to bioimaging projects, Euro-BioImaging’s DMP template with fillable fields and pop-up information might be of great help (Kemmer et al., 2024, Zenodo):

Importantly, DMPs are not rigid documents that are written for administrative reasons. They can serve as living documents to review at each step of the data lifecycle to ensure good RDM practices are considered. That means, DMPs might also be changed and versioned, since RDM tools, standards, and services evolve over time, too.

A DMP should be regarded as your helpful guidance for RDM along the way of performing your research.