Frequently asked difficult questions

General questions on DMPs

Where can a DMP be published?

Zenodo is an agnostic research archive (operated by CERN) which allows you to share all sorts of research outputs including data managment plans. Zenodo also allows versioning and will create a unique DOI for your DMP versions.

Who will evaluate my DMP?

Practices for DMP evaluation (first draft/as part of the final reporting) are still under establishment and routines may vary between different research funders and institutions. DMP evaluation may be carried out as part of administrative routines, as part of the scientific proposal evaluation, or by designated data management experts.

Science Europe, an organisation of European funders (incl. RCN) has created a rubic for reviewers on minimal DMP requirements.

In the Horizon Europe funding scheme, a brief outline of data management (1-page DMP) is required at proposal stage and included the scientific proposal evaluation.

Where can I find an example of how a DMP should look like?

Reading through different DMPs can be an useful exercise. Keep in mind that not all public DMPs are quality-controlled.

Questions on level of the DMP

How much of the DMP should I fill out at this stage?

Ideally, a DMP should be as filled out as much as possible before the active phase of the project starts and some aspects should alreday be in place at the proposal stage. Mapping out aspects of the research life cycle as early as possible will make it easier for you to have an idea of which data should be gathered while conducting the research project. For example; deciding early on which data repository you will submit the data to for long storage will give you an idea of which metadata will be necessary to gather in order to submit to the relevant archive.

The DMP should be updated as the project develops and decisions taken, it should be considered ‘a living document’. Scheduling regular updates is recommended, either at given intervals or in connections with milestones in the project.

I need a 1-page DMP for a Horizon Europe application

European Commission. (2021, updated 2023). Horizon Europe Programme Guide: Evaluation of open science practices p.42ff

Proposers will have to provide concrete information on how they plan to comply with the mandatory open science practices. Failure to sufficiently address this, will result in a lower evaluation score. A clear explanation of how they will adopt recommended practices, as appropriate for their projects, will result in a higher evaluation score. [page 42]

Under the ‘Excellence’ part of their proposals, in the section on methodology, proposers should describe how open science practices (mandatory and recommended, as appropriate) are implemented as an integral part of the methodology and show how their implementation is adapted to the nature of their work, therefore increasing the chances of the project delivering on its objectives. Information relevant to the specific area of the proposal should be provided in no more than one page. If open science practices are not applicable to the proposal, justifications should be provided so that, if evaluators agree, open science will not be taken into consideration in the evaluation. Additionally, proposers generating or reusing data should outline in a maximum of one (additional) page their plans for data management. [page 42]

Research data management (RDM): RDM is mandatory in Horizon Europe for projects generating or reusing data. If you expect to generate or reuse data and/or other research outputs (except for publications), you are required to outline in a maximum of one page how these will be managed. Further details on this are provided in the proposal template in the relevant section on open science. A full data management plan (DMP) is not required at submission stage.(…) [page 43]

Researchers and research advisors can be referred to the section Considerations pre-start/pre-award.

A research centre/research consortium needs a DMP

There is currently no accepted standard for how a DMP for a research centre or consortium (e.g. Centre of Excellence (Norwegian: Senter for fremfragende forskning), large EU project) can deviate from DMPs for individual research projects. An appropriate approach could be the definition of common data management principles, shared practices or guidelines and responsibilities for a centre or consortium in an ‘umbrella DMP’ or ‘master DMP’, including guidelines on how DMPs for individual projects or work packages should be developed. Cross-referencing between such an ‘umbrella DMP’ and related DMPs is recommended.

Relevant literature:

David, R., Richard, A. S., Connellan, C., Lauer, K. B., Chiusano, M. L., Goble, C., Houde, M., Kemmer, I., Keppler, A., Lieutaud, P., Ohmann, C., Panagiotopoulou, M., Khan, S. R., Rybina, A., Soiland-Reyes, S., Wit, C., Wittner, R., Buono, R. A., Marsh, S. A., … Ewbank, J. (2023). Umbrella Data Management Plans to Integrate FAIR Data: Lessons From the ISIDORe and BY-COVID Consortia for Pandemic Preparedness. Data Science Journal, 22(1). doi: 10.5334/dsj-2023-035
Mittal, D., Mease, R., Kuner, T., Flor, H., Kuner, R., & Andoh, J. (2023). Data management strategy for a collaborative research center. GigaScience, 12, giad049. [doi: 10.1093/gigas

General questions on RDM

I don’t have data in my project

How about other sources utilized in the project and how are they managed? Do they have identifiers? Are resources required to ensure access? (e.g. literature access, case law, database access)
Which methodology is applied to extract information and their documentation (e.g. coding)?
The project will likely have working documents such as manuscripts. How are they organized, named, stored, backed-up and exchanged between collaboration partners?
Is there ethical aspects or Intellectual Property Rights (IPR) to be considered and documented?
Text is data, images are data… Check out the Discipline-rooted approaches to research data management for inspiration.

I feel it is too much work to prepare my data for archiving in a domain-specific archive

Subject-specific (discipline-specific, domain-specific) repositories are the first choice to ensure data will be reusable in your research community, as metadata follow domain standards. Comparison between datasets or reuse at large scale (e.g. meta-analysis) is easiest if subject-specific repositories are used. Re3data and FAIRsharing are curated registries and can help identifying suitable subject-specific repositories.

Research data repositories commonly have guides/help-pages which makes it easier for you to prepare your data before submitting them to the repository. See if the repository you are submitting to has such a guide. Familiarizing yourself with such a guide early on, such as when drafting up a DMP, makes it easier for you to plan which metadata needs to be gathered in order for you to be able to submit to your repository of choice.

What format should I store my research data in?

You should consider a format which is common to the research discipline you are working in, which also adheres to Open Science standards.

What metadata should I consider collecting in my reseach project?

If you choose to share your data in a long term archive, it is highly likely this archive has a set of guidelines, wherein the necessary metadata are described. Making yourself familiar with relevant metadata schemes early in the project is recommened.

If you are unsure about which metadata to collect, a minimal set is provided in The Dublin Core Metadata standard, which originally comprosed of a collection of 15 “essential” terms.

Is my data still personal if it has been pseudonymized and the key has been deleted/is stored in a safe system
My project is in collaboration with a Greek/British/US/Indian/Chinese/Iranian partner. Are there restrictions on data sharing?
I am moving to a new position. Who owns the research data?
How should the CARE principles be implemented in practice? Is there Norwegian resources?

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