• How will new data be collected or produced and/or how will existing data be re-used?
• What data (for example the kinds, formats, and volumes) will be collected or produced?

• What metadata and documentation (for example the methodology of data collection and way of organising data) will accompany data?
• What data quality control measures will be used?

• How will data and metadata be stored and backed up during the research process?
• How will data security and protection of sensitive data be taken care of during the research?

• If personal data are processed, how will compliance with legislation on personal data and on data security be ensured?
• How will other legal issues, such as intellectual property rights and ownership, be managed? What legislation is applicable?
• How will possible ethical issues be taken into account, and codes of conduct followed?

• How and when will data be shared? Are there possible restrictions to data sharing or embargo reasons?
• How will data for preservation be selected, and where will data be preserved long-term (for example a data repository or archive)?
• What methods or software tools will be needed to access and use the data?
• How will the application of a unique and persistent identifier (such as a Digital Object Identifier (DOI)) to each data set be ensured?

• Who (for example role, position, and institution) will be responsible for data management (i.e. the data steward)?
• What resources (for example financial and time) will be dedicated to data management and ensuring that data will be FAIR (Findable, Accessible, Interoperable, Re-usable)?

Grantees should provide a sufficiently detailed description, including the scientific focus and technical approach, to allow the association of their datasets and derived data products with specific research themes.

Grantees should describe the protocols used to structure their data and indicate the metadata standards applied. This will allow other scientists to make an assessment, to attempt to reproduce the conclusions derived from the dataset (and possibly even the dataset itself), and potentially reuse the data for further research. If available, grantees should provide a reference to the community data standards with which their data conform and that make them interoperable with other datasets of similar type.

Grantees should plan to use repositories that will provide a unique and persistent identification (an identifier) of their datasets and derived data products and a stable, resolvable link to where they (or, as a minimum, their metadata) can be directly accessed.

Grantees should provide information on the standards that will be used to ensure the integrity of their datasets and the period during which they will be maintained. Grantees should also explain whether and how their datasets will be preserved and kept accessible in the longer term. If applicable, they should detail the criteria for prioritisation, appraisal and selection of the datasets to be retained. If raw data cannot be stored (e.g. because they are too large or modified in (quasi-)real-time), grantees should describe what data products will be derived and how these will be preserved and kept accessible. If available, grantees should provide a reference to the public data repository in which their datasets or data products will reside.

Grantees should provide information on how their datasets and/or data products can be accessed, including the terms of use or the licence under which they can be accessed and re-used, and information on any restrictions that may apply. It is also important to specify and justify the timing of data sharing. This could be, for example, as soon as possible after the data collection, or at the end of the project. For data that underlie publications, it could be, for example, at the time of publication or pre-publication.