Skip to content

Module 9: Data Management Plans

This page is currently under construction

The training curriculum is currently undergoing final revisions and quality checks. All materials will be released shortly. Until the official release, please refrain from using, distributing, or implementing any part of these resources.

Learning Objectives

  • Learning Objective 1 (LO1): Describe the concept of data management plans, identify challenges, and communicate its relevance to researchers.
  • Learning Objective 2 (LO2): Design practical data management strategies to meet research requirements according to the FAIR principles.
  • Learning Objective 3 (LO3): Identify data management requirements of research funders and institutions with regard to data management plans.
  • Learning Objective 4 (LO4): Apply solutions for creating data management plans (knowing at least one tool for data management planning).
  • Learning Objective 5 (LO5): Develop data management planning templates.

Total Module Duration

8 hours 30 minutes

Learning Objective 1

LO1: Describe the concept of data management plans, identify challenges, and communicate its relevance to researchers.

Learning Activities

  • Lecture (60 mins): Slide presentation with a data management plan (DMP) example for illustration. The learners will be provided with a reflection document, that encourages them to question their understanding of the many concepts, terms and workflows the lecture presents. A case study or examples of situations where a DMP is being used to predict certain eventualities can also be used during the lecture to illustrate better (Resource 4).

Materials to Prepare

  • Slide presentation.
  • A set of questions/prompts such as:
    • "Which repositories for research data do you know?" or
    • "Why do you have to know about metadata?".
  • Example of a DMP.

Instructor Notes

Lecture:

  • What is a DMP and what value does it bring to a research project? What are the pros? Which problems, resistance and friction may arise? The instructor can use material and the video from Resource 3 to develop the lecture.
  • The set of questions for the learners encourages them to discuss their understanding of key terms and workflows introduced during the lecture.
  • The instructor can use a real DMP to illustrate this learning activity. They can use a database to find some DMPs for re-use (Resource 5).
  • Learners should be encouraged to understand the data management planning process, and what resources are necessary for a professional data management planning process. Identify risks, for example that the plan is created at the time of highest uncertainty and the doubt that the value of the plan is worth the effort.

Resources

Resources to help create the lecture and associated questions or prompts:

  1. Open Research Data and Data Management Plans, ERC, 2022. https://erc.europa.eu/sites/default/files/document/file/ERC_info_document-Open_Research_Data_and_Data_Management_Plans.pdf.
  2. Essentials4Datasupport, Data Management Plans, RDNL. https://danstraining.moodlecloud.com/mod/page/view.php?id=266. Accessed 15 Apr. 2025.
  3. Data Management Planning. https://mantra.ed.ac.uk/datamanagementplanning/. Accessed 14 Apr. 2025.
  4. "Enabling Seamless Data Management Planning within PaNOSC with DSW." Data Stewardship Wizard. https://ds-wizard.org/enabling-seamless-dmp-within-panocs. Accessed 14 Apr. 2025.
  5. Public DMPs. https://dmponline.dcc.ac.uk/public_plans. Accessed 14 Apr. 2025.

Other helpful readings:

  1. Success Stories. https://ds-wizard.org/success-stories.
    Highlights the effectiveness of a good data management planning process.
  2. RDMkit. https://rdmkit.elixir-europe.org/data_management_plan.
    A handbook on every step of the project planning process from the perspective of a data steward.

Learning Objective 2

LO2: Design practical data management strategies to meet research requirements according to the FAIR principles.

Learning Activities

  • Case study (60 mins): Analyse an existing data management plan (DMP) for a research project and identify how well it meets the FAIR principles. Discuss improvements.
  • Group work on DMP Development (60 mins): In small groups, design a basic DMP for a hypothetical (or real) project, ensuring alignment with each of the FAIR principles. Share Resource 5 with the groups so that they can see if they missed anything.
  • Checklist activity (30 mins): Use a FAIR data checklist to evaluate DMPs and ensure they incorporate key FAIR elements (e.g., using persistent identifiers, selecting appropriate repositories) and they are in alignment with local institutional policies (or national/funder policies, dependent on the example used in the case).

Materials to Prepare

  • Case study: Prepare examples of FAIR-aligned DMPs.
  • Prepare a blank DMP template.
  • Create a checklist mapping DMP components to the FAIR principles.
  • Provide links to institutional and national FAIR strategies.

Instructor Notes

Case Study on DMP and FAIR principles:

  • Through the use of a case study, explain to learners how each part of the DMP relates to FAIR principles (for instance, how metadata standards contribute to making data findable and interoperable – make a link to the Metadata module of this curriculum).
  • Highlight that DMPs need regular updates to maintain FAIR compliance, particularly as research evolves or new data is generated. DMPs are not static documents but evolve throughout the research life cycle to stay aligned with FAIR principles.
  • Address discipline-specific considerations for implementing FAIR principles in different fields (differences in metadata standards or repository selection). A strong DMP is essential for implementing FAIR principles in research. Each aspect of the FAIR framework must be addressed in the DMP to ensure effective data stewardship.

Group work:

  • A blank DMP can be shared with the learners for the group work (Resource 3). The groups should be asked to come up with a hypothetical (or real) research project and then prepare a DMP together. A plenary discussion can summarise the questions that each group had, challenges they faced or other comments they had during this activity.
  • The instructor can use Resource 2 if they want to prepare research projects for each group for which they can make their DMP. They can then also show the groups the real DMPs at the end of the activity.

Checklist activity:

  • This activity is to align DMPs with making data FAIR (Findable, Accessible, Interoperable, and Reusable). This will help to map research needs to FAIR-aligned data strategies (metadata standards, storage, sharing protocols).
  • The instructor can use Resource 4 to do this mapping exercise.

Resources

General information:

  1. Research Data Management. Science Europe. https://www.scienceeurope.org/our-priorities/open-science/research-data-management/. Accessed 15 Apr. 2025.
  2. Public DMPs. https://dmponline.dcc.ac.uk/public_plans. Accessed 14 Apr. 2025.
  3. Researcher Guidance for Data Management Plans. Science Europe. https://scienceeurope.org/media/411km040/se-rdm-template-3-researcher-guidance-for-data-management-plans.docx. Accessed 14 Apr. 2025.
  4. Hettne, Kristina Maria, et al. "FIP2DMP: Linking Data Management Plans with FAIR Implementation Profiles." FAIR Connect, edited by Barbara Magagna, vol. 1, no. 1, Jan. 2023, pp. 23–27. DOI.org (Crossref), https://doi.org/10.3233/FC-221515.
  5. Checklist for a Data Management Plan. https://www.dcc.ac.uk/sites/default/files/documents/resource/DMP/DMP_Checklist_2013.pdf.

Learning Objective 3

LO3: Identify data management requirements of research funders and institutions with regard to data management plans.

Learning Activities

  • Lecture (45 mins): Workshop activity of reading one or more requirements with regard to data management plans (DMPs) by funders or institutions and discuss in plenary.

Materials to Prepare

  • Slide presentation (and video): The teacher prepares a set of questions that can structure and focus the plenary discussion dependent on the learners. The teacher can choose to
    • focus on comparing the different requirements of funders,
    • encourage the learners to share experiences, or,
    • create a check-in activity, where the learners simply report on what they have understood from the requirements they read (if it is more appropriate for the learners).

Instructor Notes

Lecture:

  • The aim of this learning objective is to identify which research funders and institutions require DMPs or descriptions at the application stage. What are the requirements? The instructor can use the EU DMP template and at least one local template as examples (Resources 2, 3).
  • Regarding the resources, choose guidelines from national funders as appropriate. Possible questions the instructor can use to structure the plenary discussion are:
    • What strategies or best practices could be used to effectively meet these requirements in a DMP?
    • What are the most common requirements you have observed among the different funders?
    • Can you identify any dilemmas or causes for resistance between funder requirements and how the researchers you know work?
    • How could these dilemmas/resistance be mitigated?
  • The resources provided give a variety of examples to share with the learners.

Resources

DMPs:

  1. Open Research Data and Data Management Plans. European Research Council. https://erc.europa.eu/sites/default/files/document/file/ERC_info_document-Open_Research_Data_and_Data_Management_Plans.pdf. Accessed 15 Apr. 2025.
  2. Annotated template HORIZON 2020 DMP. https://ec.europa.eu/research/participants/data/ref/h2020/other/gm/reporting/h2020-tpl-oa-data-mgt-plan-annotated_en.pdf. Accessed 15 Apr. 2025.

European funders requirements:

  1. EC guidelines. https://ec.europa.eu/research/participants/data/ref/h2020/grants_manual/hi/oa_pilot/h2020-hi-oa-data-mgt_en.pdf.

National funders requirements:

  1. The ANR introduces a Data Management Plan for projects funded in 2019 onwards. https://anr.fr/en/latest-news/read/news/the-anr-introduces-a-data-management-plan-for-projects-funded-in-2019-onwards/.
  2. Handling of research data. DFG. https://www.dfg.de/resource/blob/174736/92691e48e89bf4ac88c8eb91b8f783b0/forschungsdaten-checkliste-en-data.pdf.
    Not explicitly named DMP, but similar content.

Other funder requirements:

  1. Funder Requirements. DMP Online. https://dmponline.dcc.ac.uk/public_templates?page=2&search=&sort_direction=asc&sort_field=templates.title. Accessed 15 Apr. 2025.

Learning Objective 4

LO4: Apply solutions for creating data management plans (knowing at least one tool for data management planning).

Learning Activities

  • Lecture (45 mins): Slide presentation on going from a project description to a data management plan (DMP).
  • Practical exercise (90 mins): The learner will prepare a DMP based on the project description in the DMP tool of their institution.

Materials to Prepare

  • Prepare a description of a synthetic research project with RQ and data requirements.

Instructor Notes

Lecture/Exercise:

  • The aim of this learning objective is to guide learners to discuss, what solutions there are at their local institution for creating and maintaining DMPs. Introduce at least one tool available.
  • The instructor can indicate that solutions include using simple text documents or specific tools for creating DMPs (for instance FAIRWizard, Research Data Management Organizer, DMPonline).

Resources

Lecture/Exercise:

  1. Data Management Plans | DCC. https://www.dcc.ac.uk/dmps. Accessed 15 Apr. 2025.
  2. DCC. (2013). Checklist for a Data Management Plan. v.4.0. https://www.dcc.ac.uk/sites/default/files/documents/resource/DMP/DMP_Checklist_2013.pdf.

Learning Objective 5

LO5: Develop data management planning templates.

Learning Activities

  • Lecture (60 mins): Lecture or slide presentation on domain specific data management plans (DMPs) and cross-disciplinary interoperability. Illustration of the creation of data management planning templates using a tool available at your institution. Resources 3 and 4 provide ideas on content for such a lecture (which can be supplemented with the instructor's domain-specific expertise).
  • Think-Pair-Share Activity (60 mins): Interview scenarios between groups of learners, in which they practice asking about the needs of a project. Resource 5 has more detail on how to structure such an activity, and the Instructor Notes have more guidance on the kinds of questions that could be included in the interview.

Materials to Prepare

  • Slide presentation on domain-specific DMPs.
  • Data management planning template for illustration.

Instructor Notes

Overall:

  • We expect instructors to tailor the session according to the disciplinary requirements. We include this learning objective here nonetheless to highlight that data stewards may sometimes be required to adapt or customise DMP templates in accordance with discipline (or institution) specific requirements.

Lecture:

  • The instructor is urged to emphasise institutional requirements to DMPs and provide examples from the institutions of the learners, including possible disciplinary differences in how the DMPs are completed.
  • In this unit, the instructor should discuss with the learners how to identify the specificity and needs of various cases or disciplines, in order to encourage the learners to design and adapt templates that meet a variety of requirements from the project/research team.

Think-Pair-Share:

  • Learners are divided into groups of two. They switch being the project owner and the data steward during the scenario.
  • The "researcher" is given a short project description to base their answers on, the "data steward" is given some questions to get them started asking into the needs of the project and research team.
  • Questions could include:
    • What data will your project produce?
    • Where does your data need to live?
    • Where does the data need to go?
    • Who will be generating the data?
    • What is the data about?
    • Is all the data you produce equally important?
    • What format is the data in?
    • Which requirements from funders regarding data do you have?
    • Which requirements from your institution regarding data do you have?

Resources

Lecture/Activity:

  1. DMPonline. https://www.dcc.ac.uk/dmps.
    A tool and practical guide to create DMPs that meet funder requirements, review and share DMPs.
  2. DMP checklist. https://www.dcc.ac.uk/sites/default/files/documents/resource/DMP/DMP_Checklist_2013.pdf.
    To check that all the important elements have been covered in the DMP.
  3. Netscher, Sebastian, et al. "Data Management Planning across Disciplines and Infrastructures. Introduction to the Special Collection." Data Science Journal, vol. 23, Apr. 2024, p. 16. DOI.org (Crossref), https://doi.org/10.5334/dsj-2024-016.
  4. Netscher, Sebastian, et al. Domain-Specific Data Management Plans and Cross-Disciplinary Interoperability. Aug. 2021. DOI.org (Datacite), https://doi.org/10.5281/ZENODO.5137325.
    Slide show about domain specific DMPs and cross disciplinary interoperability.
  5. Think, Pair, Share | Kent State University. https://www.kent.edu/ctl/think-pair-share. Accessed 15 Apr. 2025.