Data Management Plans
Contents
The research data policy of Freie Universität recommends the “creation of a data management plan at the earliest possible stage of the project.” This guide lists specific recommendations for action, and provides a selection of templates and tools for creating data management plans.
A data management plan (DMP) is a systematic description of how the research data that is created or collected in projects is handled. It documents the storage, indexing, maintenance, processing, retention, and publication of the data. A DMP makes it easier for third parties to interpret and reuse data; appropriate responsibilities for handling data must be clarified before the start of the project.
In their role as collectors, explorers, or generators of data, researchers and research groups can benefit greatly from using a DMP. For example, creating a systematic description forces them to reflect upon how they handle and manage research data. DMPs also allow researchers to record aspects such as the data flow processes, legal parameters, and software applications implemented throughout the project, something which can be of benefit to not only project staff but also third parties who might wish to use the data in a follow-up project. Carrying out research data management within a project, for example, when documenting or publishing research data, can also make the potential of the data clearer, for example, by answering a DMP questionnaire.
In addition, funding institutions increasingly expect a DMP or a related section on how to handle the research data generated in the project to be contained within the project proposal. Depending on the funding line, the DMP may be required while applying for the project, six months after the start of the project or, in some cases, only for data-intensive projects.
Data management plans allow for the costs or effort involved in creating, documenting, and publishing the data produced in the project to be clarified and reflected accordingly in the projected costs/budget of the project proposal.
In order to achieve the greatest possible benefit, the DMP as formulated in the research data policy should ideally be created before the project begins. In any case, it should be created as early as possible in the course of the project, and updated regularly. However, even if it is created later, a DMP can still be helpful.
Researchers have several tools at their disposal with which to create their own data management plans.
Templates
A wide range of templates, checklists, sample DMPs, and published real-world examples are available for anyone wishing to create their own DMP.
Templates provide researchers with a predefined framework with which to create their own DMP. Researchers are rarely required to use a specific template – this is usually a choice that is left to the researcher.
A number of universities and research institutions offer their own templates, a selection of which can be found below:
- Freie Universität Berlin
- Humboldt-Universität zu Berlin (DMP templates and samples for Horizon 2020; DFG, BMBF, and Volkswagen Foundation project proposals)
- Leibniz Universität Hannover (Guide to Creating a Data Management Plan in German, PDF)
In 2021, the German Research Foundation (DFG) created a checklist for handling research data. The catalog of questions included in this checklist is well suited for creating a DMP.
The European Commission has created DMP templates for the Horizon Europe (2021–2027, DOCX) and Horizon 2020 (2014–2020, PDF) funding programs, the use of which is recommended but not mandatory. The European templates are strongly oriented toward the FAIR principles (e.g., with sections such as “Making data findable, including provisions for metadata” or “Making data interoperable”).
Science Europe published a practical guide in 2021. The chapter “Core Requirements for Data Management Plans” contains a detailed list of questions to support researchers in preparing DMPs.
In addition, subject-specific templates focus on the unique aspects of a given subject area (e.g., special features related to data protection in the social sciences).
Publicly available DMPs can serve as an additional source of inspiration when developing an individual DMP.
Below is a selection of published DMPs:
- DMP Use Case Project and blog entry “Establishing a collection of 841 publicly available Horizon 2020 Data Management Plans” (Description of the DMP Use Case Project)
- Published DMPs in Argos
- Zenodo search results for “DMP” and “Data Management Plan”
Tools
Most DMP tools are web-based services, where the DMP is usually created by answering a questionnaire. Here, the researcher is asked several questions that allow for the individual sections of an underlying DMP template (e.g., for a DFG application) to be filled in step by step. After completing the questionnaire, the researcher can then usually export the final DMP in their chosen file format (e.g., DOCX, ODT, PDF), and edit it locally.
Selection of DMP tools:
- Research Data Management Organiser (RDMO). Tool developed in Germany as part of a DFG project. Questionnaires available for different contexts (e.g., DFG, EU applications).
- DMPonline. Tool jointly developed by the Digital Curation Center (UK) and the University of California Curation Center.
- Argos. European tool developed in the context of OpenAIRE.
These tools often offer a demo version that can be accessed for free.
Contents of a Data Management Plan
Some questions that are commonly asked in questionnaire-based DMP templates or tools include:
- What kind of data is used or created?
- How is the data generated (methods/tools/software)?
- What general conditions apply (i.e., what standards and policies does the discipline, the research institution, or the funding institution have in place)?
- What data formats will be available and how large will the dataset be?
- How will data be organized and named?
- Where will the data be stored and what backup provisions will be in place?
- How will sensitive data be protected?
- How and where will the data and the context of their creation be described and documented?
- How and where will the data be archived after the end of the project?
- Should the data be published? If not, why not? If yes, where and with which license?
The answers to these questions may vary in detail depending on the research project and the discipline. For example, medical or social science projects will more often have extensive explanations when it comes to data protection (sensitive data). A central point in many DMPs covers the topics of storage, security, and backup in order to avoid data loss. Another main point is the publication of data after the end of the project in order to enable their reuse.
The University Library’s RDM team is available to answer questions about research data, research data management, and creating a DMP. The RDM team provides support in choosing a suitable template or DMP tool, and is happy to supply information on the requirements of the various funding bodies. In addition, DMP drafts can be submitted to the team for review. For specific questions, please contact the funding institution directly.
Version July 25, 2023