Data management paragraph
When applying for funding, it becomes more and more common practice to write a data management paragraph. On this page, we address the topics that are regularly asked for in data management paragraphs and provide you with example texts. The examples below are general and can be used in a pick-and-mix fashion. We also provide a template specifically for the Horizon Europe Standard Application Form here (pdf, 188 kB).
1. FAIR principles
Most funders endorse the FAIR principles, which state that your research data should be Findable, Accessible, Interoperable, and Reusable. It is useful to keep this in mind when writing your data management paragraph. These principles generally apply to storage of your data in the long term.
In your data management paragraph, you can apply the FAIR principles by mentioning the repository you have chosen for storage of your data and stating the following aspects:
Findable: How can others easily find your data?
- Will your data receive a Persistent Identifier (e.g. a DOI)?
- Does the repository have specific metadata standards (e.g. Dublin Core or DataCite)? If not, can you add metadata like a summary, keywords, authors, etc. yourself?
- Is the repository indexed by search engines, for example Google Scholar?
Accessible: How is the access to your data regulated?
Note that accessible data does not automatically imply open or free access. Data published with a closed and/or restricted access can also be FAIR. Although at Radboud University open access is stimulated, there can be ethical or legal reasons for not making (parts of your) data open access This means that if you have good reasons to publish your data under restricted access or to not publish your data at all, you can mention those reasons and the protocols that are in place. Regardless of how open you plan to publish your data, the following points relate to accessibility:
- Are there any limitations to who can access the data? For example, will you make use of data use agreements or licences under which you will share your data?
- If the data itself is not accessible (for example due to ethical or legal reasons), is the metadata accessible?
- Mention how long the data will be stored. The Radboud University has a policy that all research data should be stored for at least 10 years for reasons of scientific integrity.
Interoperable: Is it possible for people and computers to interpret the data and combine it
with other datasets?
- If existing in your discipline, will you make use of standard vocabularies, ontologies and/or thesauri in your metadata?
- Mention if you will try to use interoperable file formats where possible. In general, most preferred interoperable file formats are those that are widely used and free to access. For example, .odt (Open Document Text) or .pdf are to be preferred over .docx files, seeing that Microsoft Word is not free to use and possibly not available to everybody (now or in the future).
Reusable: How will you make your data ready for (re-)use by others?
- Will you include proper documentation, like a readme, codebook or methods? For more information see here.
- You can mention any data use agreements or licences under which you will share your data. For example, the CC BY 4.0 licence is a commonly used license. Some repositories issue standard licences that will accompany your dataset.
- When you work with specific software, for example for your analyses, explain how and where the software is available and if it is not commonly available, how you will deal with that. For example, by publishing your own software alongside your data when possible. If you don't use special software, mention that all the data can be opened with generally available software tools.
“It is the policy of Radboud University in general and our research institute [name research institute] in particular to comply with the FAIR principles and share with the scientific community any data obtained in research projects, as long as ethical and legal regulations permit it. In accordance with the university’s research data management (RDM) policy all research data will be archived for reasons of scientific integrity for 10 years after completion of the project. Where possible, data will be archived via the Radboud Data Repository. Via these archiving facilities, data will be (1) Findable by indexing data by search engines on the internet, including rich metadata according to the Dublin Core and DataCite schemas, and receiving a persistent identifier (DOI), (2) Accessible by using an open internet protocol, including clear authorisation procedures, and, where possible, the data will be shared when related articles are published under an open access license, (3) Interoperable by using standards for metadata (Dublin Core/DataCite), by adding documentation (codebook and readme), using preferred formats, and using a standard vocabulary if available, and (4) Reusable by including rich metadata, making sure that all data can be opened and used by generally available software (analysis) tools, by adding documentation with instructions for reuse, and by publishing it under an open access license.”
If applicable, you can also include this addition to the above sample text:
“All data not suitable for reuse, due to legal or ethical reasons, will be stored for 10 years, but not made publicly available to others after research. [Please elaborate on the reasons. Legally, it might not be possible to share data because of ownership or intellectual property rights. Ethical reasons concern for example the privacy of participants or confidentiality.] Possible access to these forms of data and its storage and processing will be in line with the privacy requirements of the EU GDPR directive.”
2. Storage during research
Besides mentioning the FAIR storage of data in the long term, it is a good idea to add information about the protocols Radboud University and your institute have for storing data securely while research is ongoing. You could mention information regarding storing personal and/or sensitive data, backing up, and data processing in unsafe environments. Below you will find several sample texts. Be aware that these examples mention very specific tools. We highly recommend consulting your institute's RDM policy to see what storage options are recommended at your faculty or research institute.
Sample text 1
“Radboud University recommends that while research is ongoing, data is stored on the campus network. Safe and secure storage is guaranteed by the IT security and safety protocols of the campus network. In addition, it is proposed that Surfdrive (for non-personal data) or the campus network (for (sensitive) personal data) can be used to exchange between researchers during the project. If it is not possible to store the data directly on the campus network, data is stored encrypted on a local device (laptop) and transferred to the campus network as soon as possible.”
Sample text 2
“In line with the policy of Radboud University, while research is ongoing, data will be stored on the campus network. For this purpose, [department name] has its own server space which is supported by the IT department. This server space allows for managed access to and the sharing of data between and among partners and guests during the project. Safe and secure storage of data is guaranteed by the IT security and safety protocols of the campus network.”
3. Facilities and/or services necessary during and after research
Some funders ask if certain extra facilities and/or services are necessary, for example ICT, archive, refrigerators or legal expertise. If this is not the case and all the facilities you need are already provided for at your institute, you can refer to the sample text under “storage during research”.
“As outlined above, all facilities necessary to store and share research data are available at Radboud University. No further facilities are necessary.”
4. Data management plan
State that you are going to write a data management plan before (most funders) or in the first months after (EU funding) the start of your project. You can write and collaborate on your DMP using the Radboud University’s DMP tool, which includes most funder formats.
“Before the start of the project, all issues of data management will be addressed in a fully-fledged data management plan. For this, Radboud University has a DMP tool, that includes feedback from RDM Support. Training and support in writing a data management plan are offered to the researchers involved by the section RDM Support (University Library, Radboud University) and the data steward of the institute.”
Radboud University has a support service for issues concerning the management of research data (www.ru.nl/rdm), as well as dedicated data stewards in each research institute. All questions that arise during the research project can be addressed to RDM Support of Radboud University or the data steward.
“RDM Support (https://www.ru.nl/rdm) together with the data stewards help researchers to store, share and reuse research data by offering training in writing a data management plan as well as providing support with any legal and ethical questions that may arise.”