Data Management Plan - content

This section contains information about the research project where the data will be handled.

Enter here information such as project name, short project description, project manager, contributing researchers, research principal, funder, diary number or equivalent, as well as the date and version of the data management plan. It should show who is involved in the project, both individuals and organizations.

Describe how research data will be collected, created or reused. What type of data the project will handle (e.g. tabular data, survey replies, measurements, videos), expected volume and the formats that will be used.

Specify how the data will be collected and processed. What standards and methods will be used? Are the data created reproducible (e.g. created through experiments) or not (eg. participatory observations, interviews)?

If existing data sets are reused, how can they be integrated with other data and how are issues relating to copyright, licenses and intellectual property dealt with?

What formats will be used? – for example text files (.txt), come-separated values (.csv), geo-referenced data (.tif,.tfw), discipline-specific formats (ex. CIF inom kemi). If data is created using an instrument, specify the instrument name and version/format.

Are the selected formats compatible with open standards and how does the format choice affect the conditions for long-term preservation and the ability to reuse data?

Specify expected volume/size (e.g. Gigabyte/Terabyte or number of objects/files) for the data handled in the project. If the project handles large volumes of data, has that been taken into account in the budget, when choosing the storage solution and how it affects the conditions for sharing/transfer of data.

See also: Choosing file format (Swedish National Data Service)

This part focuses on documentation and quality assurance of the project data.

Specify how the material will be documented and described in terms of methods of data collection and analysis as well as structure, format, standards, variables and other data description. How is it ensured that others can understand, review and reuse data? To what extent will discipline-specific metadata standards be used.

How will data be organized during the project, e.g. filename procedures, folder structure and version control?

How will data quality be ensured and what documentation procedures are used to obtain data that is complete, accurate and consistent (e.g. repeated measurements, validation of data input, use of descriptive metadata)?

See also: Working with Data (Swedish national data service)

This section focuses on storage solutions, data security and procedures for backup of data during the course of the research project.

Briefly describe the selected storage solutions for the project's data. How are data security, data integrity and controlled access ensured?

Have the data been classified in regards to level of sensitivity and what considerations have been taken if the data contains sensitive information such as personal data?

If data includes personal data, how will the identity of individuals be protected, for example through pseudonymisation or anonymisation?

See also:

• Store data and collaborate
• Information security

The focus here is on how data is handled in accordance with ethical guidelines and legal regulations, including personal data protection, confidentiality and intellectual property rights.

How is it ensured that data is handled properly on the basis of legal and research ethical aspects? Is an approved ethical test required to begin data collection?

How are responsibilities and rights to data managed? This may apply to copyright and/or intellectual property rights, both for existing and new data that will be collected/generated. What are the prerequisites for publishing data and continuing use of data after the end of the project?

Have rights and obligations been managed through contracts if several parties are involved in the project?

If the project will handle sensitive information, how will the conditions for storing, sharing and publishing this data be affected? Is there a need to protect certain data for future commercialization of results or patent application?

See also:

• Research Agreements
• Innovation Support
• Research Ethics

This section focuses on how research data can be made openly available and preserved in the long term.

How will data and other digital objects such as code and software from the project be made available? Are there legal, ethical or other reasons that limit the possibility of publishing data and associated components?

Is special software, equipment or source code needed to access, understand and reuse data from the project?

When publishing data, what repositories or other platforms will be used? Under what type of license will the data and other components be published? How is it ensured that published data is given a permanent identifier, e.g. DOI number?

Research data are public records at the University and must according to law also be kept at the authority. How is long-term preservation and documentation of data ensured so that the basis for published research results can be reviewed?

If multiple parties are involved, how is the responsibility for data retention distributed after the end of the project?

See also:

• Prepare and share data (Swedish National Data Service)
• Publish Data
• Archiving and Thinning of Public Records

This section describes who is responsible for the different parts of data management and what resources are required.

Describe the roles and responsibilities for different parts of data management. In the case of multi-party projects, it should be clear how responsibility is distributed.

What resources will be required to implement the planned data management and to ensure that the data comply with the FAIR principles? This can apply to budget for storage solutions, hardware and software, but also skills. Do you need to hire external staff or services, and if so, have the project budgeted for this?