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Data Management Plan

A Data Management Plan (DMP) is a formal document that outlines how research data will be collected, organized, documented, stored, preserved, and shared during and after a research project. It is a crucial component of current research practice and is often required by funding agencies as part of grant applications. A funder-approved DMP is often also a requirement to obtain the first round of funding for a research project.

Data Management Plans are essential tools for promoting best practices in research data management, increasing the value of research outputs, and ensuring compliance with funder requirements. A DMP helps you at an early stage to plan how to make your research data FAIR and your research reproducible. It can also help you to comply with data protection laws and protect the privacy of data subjects. Furthermore, a DMP can increase the impact of your research and make it more efficient.

A DMP is a living document: you write it before a research project starts and keep updating it throughout the research project. You may not know all the answers at the beginning, and circumstances may change. The data management plan must be updated during the course of the project if there are significant changes, such as: new data, changes in the guidelines of the consortium (e.g. new innovation potential, decision for patent application) or changes in the composition of the consortium (e.g. entry of new consortium members or departure of old members).

You can find the policies and conditions of several important research funders and links to DPM templates here.

A typical Data Management Plan includes the following key elements:

  • Data Description
    A clear description of the types of data and formats that will be generated or collected during the research project. This may include raw data, processed data, code, multimedia files, and metadata. Some funders may specify preferred data formats or recommend adherence to certain data standards to enhance interoperability and reusability of research data.

  • Data Documentation and Metadata
    Information on how the data will be organized and structured for easy understanding and use by both the research team and potential collaborators or other researchers.

  • Data Storage and Backup
    Plans for secure data storage, backup strategies to prevent data loss, and measures to ensure the integrity of the data over time. Generally, simply mentioning that the data will be stored securely and backed up in institutional storage solutions is often sufficient. Additional details become more relevant if you opt for external storage solutions not provided or managed by the TU/e. In such cases, providing further elaboration is necessary.

  • Data Preservation and Archiving
    Here you address a strategy for preserving the research data beyond the project's lifespan, including plans for long-term storage/archiving and potential data dissemination. For long-term data storage, you may consider a data repository if you plan to publicly share your data.

  • Data Sharing and Accessibility
    When applicable, a simple statement declaring that all data is suitable for re-use is adequate. However, if certain data is unsuitable for re-use due to reasons such as privacy or intellectual property concerns, a clear explanation must be provided. It is essential to specify whether these restrictions apply to the entire dataset or only specific portions, such as raw data, interview data, or confidential data, which may not be suitable for re-use. If you indicated that some or all of the data is suitable for re-use, it is crucial to specify the intended data sharing location. Typically, funders expect you to mention a specific trustworthy repository (e.g., 4TU.ResearchData, Zenodo, DANS, etc.) and clarify whether the repository provides a persistent identifier, such as a DOI (Digital Object Identifier). This ensures the data's accessibility and long-term traceability.

  • Data Security and Ethical Considerations
    Here, you describe the measures you will take to protect the privacy and confidentiality of sensitive data, as well as compliance with ethical guidelines, data protection regulations, and any necessary consent procedures.

  • Intellectual Property Rights
    This section requires clarification on ownership and rights related to the research data, especially in cases where data may have commercial potential or involve collaboration with third parties.

  • Data Management Resources
    In this section, you address repository costs or any other data management-related expenses that may not be readily available within your institution or may require additional funding.

If you need help with writing your DMP, please contact us.

Tools and Further Reading​

FAQ​

Does TU/e have a policy for research data management?​

No, TU/e is still working on this.

Is there a template for filling out a data management plan?​

All research funders provide templates to help you create your DMP. At TU/e, you can access a dedicated DMP template through the DMP tool on the Research Cockpit.

NWO wants me to consult a TU/e data steward. Can someone support me with making a data management plan?
Yes, you will receive guidance from your departmental data stewards while completing your DMP when creating a DMP on the Research Cockpit. You can also contact a Data Steward.