Data Paragraph (Grant Proposal)

When applying for funding, it has become increasingly common to include a data paragraph, also known as data management paragraph or data management section. A data paragraph is a section within a grant application or research proposal that outlines how the research data will be handled throughout the course of the project. It is a concise yet comprehensive description of the data management practices that the researchers plan to implement to ensure the proper collection, organization, storage, preservation, and sharing of the research data. A more detailed description of data management is included at a later stage (post-award stage) in a Data Management Plan.

Some funding agencies, such as NWO, provide a specific template for the data paragraph in your proposal. If you do not have a template to refer to or are unsure how to begin, refer to our guide in the next section. It includes a checklist and sentence examples to help you get started. For more detailed support or feedback when drafting your data paragraph, please get in touch with RDM Support or the data steward of your faculty. Please contact a data steward at least a week before your proposal deadline.

Checklist and examples

While a dedicated section on research data management may not be required by all funding agencies, we strongly encourage researchers to consider the following questions when preparing a project proposal. Use these questions as a checklist for your data paragraph, select example sentences, and adapt as needed to fit the specifics of your research.

tip

As data paragraphs often have size limitations, focus on the topics more relevant to your research and/or funder (usually data reuse or how FAIR principles are incorporated to the research).

Data collection and reuse

Are you reusing or generating datasets and/or other research outputs (for example, analysis scripts or other code/software, protocols, samples, etcetera)? Is or will the data be available for reuse?

• If reusing data, what is its source? Are you allowed to reuse the dataset (what is the license, have you received permission from the author, or is there a data agreement in place)?

  Example sentence I: license

  The methodology described in this research proposal will be applied to the numerical data previously collected and published by Meijer et al. [9]. The dataset is available through the 4TU.ResearchData repository under the CC-BY 4.0 license.

  Example sentence II: agreement

  Secondary data processing is used in order to answer our research questions. The data (high-speed videos) is owned by our industrial partner and has been shared with us under a Non-Disclosure Agreement. Although the data is confidential, the analysis script and other research outputs will be made publicly available for the purpose of reuse.

• If not reusing data, explain the reason.

  Example sentence: data collection

  For this unprecedented study, we will be interviewing two hundred participants as currently there is no sufficient data suitable for reuse available. The dataset (textual transcripts) will be presented in an open file format (.txt) and it is expected to not exceed the size of 10GB. After anonymization, the dataset will be made available for reuse via a trusted data repository.

Data storage and sharing

How will you store data during the project? Will you share data only internally or also externally?

• If storing data on TU/e supported storage, you can include one of the following sentences:

  Example sentence I: general statement

  During the project data and corresponding metadata will be stored on TU-recommended scalable storage solution (for example, SURF Research Drive, TU/e network drive or MS OneDrive). The university guidelines regarding data storage will be adhered to (and discussed with data stewards as necessary). During the active phase of the project, only the researchers involved in the project will have access to the storage folder. Clear folder structure with consistent file naming will be used. Data stored on TU/e recommended solutions is backed-up daily to multiple secure and geographically diverse locations to avoid data loss. External data sharing will be done securely via SURFfilesender.

  Example sentence II: SURF Research Drive (sharing with external parties required)

  For data storage and sharing during the active research phase, project members will use the SURF Research Drive platform. SURF Research Drive is a national cloud service in the Netherlands designed for storing, synchronizing, and sharing files related to research projects, with a particular emphasis on research data sharing with external collaborators. This platform is hosted and technically managed by SURF in the Netherlands, is ISO 27001 certified, and complies with the SURF Baseline Information Security. Data in Research Drive is encrypted both at rest and during transfer. Collaborators and other consortium members can be granted access to the TU/e instance of Research Drive using their organizational email address with multifactor authentication. For handling highly confidential data, TU/e members will use the encryption tool Cryptomator Hub, which ensures secure data sharing¹.

  Example sentence III: TU/e Network Drive (sharing with external parties not required)

  During the active research phase, TU/e members will use the TU/e Network Drive for data storage. Technical IT measures ensure only authorized TU/e staff and privileged accounts can access and process data. The system includes ransomware protection, critical vulnerability scanning, a next-generation firewall, data back-up, disaster recovery, and server-side encryption. The primary storage location is a data center with ISO 27001 certification, built to Tier 4 standards for maximum reliability. Furthermore, TU/e has implemented a strategic information security policy based on the NIST framework. The TU/e security organization undergoes the SURFaudit and includes a Chief Information Security Officer, an operational security team, a Computer Emergency Response Team (available during office hours), and a 24/7 Security Operations Center with SIEM capabilities. Additionally, there is an active system software update policy and regular backups of university information systems¹.

• If not storing on TU/e supported storage, explain what is used instead including what measures are in place for securing the data.

Data archiving and publishing

How will you store data after the project? Which datasets are going to be made publicly available? Which are not and why (what are the constraints)?

Example sentence: open data

Data not subject to access restrictions (e.g. for reasons of ethics, confidentiality, or IP protection) will be disseminated via a trustworthy and compliant data repository (such as 4TU.ResearchData or Zenodo) under a Creative Commons license. Data published in this way follows the FAIR principles and is available open access.

tip

Data relevant to substantiate the research results as well as the data and project documentation (including, for example, the data management plan, informed consent signed by participants, and agreements) should be preserved for at least 10 years.

Example sentence: archiving

In accordance with the Netherlands Code of Conduct for Research Integrity all research data and documents relevant for the execution of the project and related to the data handling will be stored for reasons of scientific validation and integrity for 10 years after completion of the project with restricted access. This preservation will take place on a TU/e archive system¹².

Other research outputs

Are there any other research outputs worth mentioning?

• If working with code and/or scripts, do you need to collaborate on the code? Are you documenting it and keeping track of changes? Do you plan to make the code open source? If so, under which license?

  Example sentence: TU/e GitLab

  During the research, we use TU/e GitLab for collaboration and version control of our codes/scripts. They will be easily searchable through creating several GitLab projects each with a clear folder structure and file names. README files and additional documentation will be added to explain the project, code, data, and methods used. Local working copies of files and code used by the researchers in this project will be pushed daily to the corresponding GitLab projects. The code is released under an open-source MIT license, making it freely available for reuse and modification.

• If creating logbooks, (electronic) lab notebooks, and/or protocols, briefly describe how they will be managed.

  Example sentence: additional documentation

  Additional information on the methodology will be documented in logbooks. At the end of the project, these will be digitized and/or exported to an open file format and also stored alongside the research data.

FAIR principles in practice

What and how FAIR principles are incorporated to your research data management practices?

tip

The research data management practices described in this document (implicitly) incorporate the FAIR principles. Should you want to emphasize them (because this is particularly important for the funder or other reason), the following sentence could be added to the data paragraph.

Example sentence: FAIR principles in practice

Eindhoven University of Technology aims to comply with the FAIR principles and share with the scientific community any data obtained in research projects, if ethical and legal regulations permit doing so. Where possible, data will be published via a trustworthy repository, such as 4TU.ResearchData. Via the repository, data will be:

1. Findable by indexing data by search engines on the internet, including rich metadata according to, e.g., the 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 (to be determined, but most likely OSI-approved (for code) or Creative Commons),

3. Interoperable by using standards for metadata (e.g., DataCite), by adding documentation (e.g., README files, codebooks), 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.

Costs and resources available

Do you expect that costs/expenses will be incurred from the data processing activities during and after your project? What are the services (or tooling) required for conducting the research data management?

• If no additional costs are expected, consider describing the main data management activities involved and who is responsible for their execution.

  Example sentence: RDM costs

  Data management and making the data FAIR (assigning DOI, describing the data, assigning metadata to the data, etc.) is part of the ongoing research activities of involved researchers. Although we do not foresee any extra expenses, a budget of 5000 euros is reserved for RDM purposes.

• If additional costs are expected, make sure to include them in the budget section of your proposal. Consider, for example, activities/services such as anonymization, documentation, data cleaning, and file conversion/digitization.

tip

If relevant, mention the research support and/or resources available at no additional cost.

Example sentence I: support available

To ensure that data collection in the project adheres to the highest ethical and privacy standards, all studies will undergo prior screening and approval by relevant parties, including the Ethics Review Board, Data Stewards Team, and Privacy Team, as appropriate. Additionally, the university provides dedicated staff to offer support in areas such as Research IT infrastructure, Open Access, intellectual property, and legal matters.

Example sentence II: 4TU.ResearchData repository

4TU.ResearchData is able to archive 100GB of data per researcher per year free of charge for all TU/e researchers. We do not expect to exceed this and therefore there are no additional costs for long-term preservation.

Useful links

• Funder requirements

• Data Management Advice for NWO grants

• Writing a data management plan | Radboud University

Footnotes

1. For updates, please check: Data paragraphs etc. ↩ ↩² ↩³

2. See also: Step-by-step guide on archival package ↩