Research data management and sharing

The Research Council of Norway and the EU require a DMP for projects they fund. UiB's policy for open research requires a DMP for all projects led by UiB-affiliated researchers, including those without external funding. The plan is a living document that is updated throughout the project.

The content of this guidance is based on the framework for the management and processing of research data developed by Science Europe.

1. Description of data, data collection and reuse of existing data

- How will new data be generated/collected and/or how will existing data be reused? 
- What data (type of data, format and volume) will be generated or collected?

2. Documentation and data quality

- What metadata and documentation (for example a description of methods or organization of data) will accompany the data?
- What measures for quality control of the data will be used? 

3. Storage and backup during the research process

- How will data and metadata be stored and backed up during the research process? 
- How will data security and the protection of any sensitive data be ensured during the research process?

4. Legal and ethical requirements and guidelines 

- If personal data is processed, how will compliance with legislation on personal data and data security be ensured? 
- How will other legal questions, such as intellectual property rights and ownership, be handled? Which legislation applies?
- How will possible ethical questions be taken into account, and which ethical guidelines are followed?

5. Data sharing and long-term preservation

- How and when will the data be shared? Are there potential restrictions on data sharing or reasons to place an embargo on the data?
- How will data for preservation be selected, and where will data be preserved in the long term (for example a data archive)?
- What methods or software will be needed to access and use the data?
- How will the use of a unique and permanent identifier (such as a Digital Object Identifier (DOI)) for each dataset be ensured?

6. Responsibility for data management and resources

- Who (for example role, position and institution) will be responsible for the data management?
- What resources (for example funding and time) will be devoted to data management and to ensuring that the data will be FAIR (Findable, Accessible, Interoperable, Reusable)?

See also the resource plan.research-data.no for more detailed information on several aspects of data management.

FAIR is the international framework for good research data management that aims to ensure that data is, as far as possible, findable, understandable and reusable. The Research Council of Norway, the EU and UiB require publicly funded research to follow the principles as far as possible:

• Findable – data has a persistent identifier, descriptive metadata and is registered in a searchable catalogue
• Accessible – data can be retrieved via standardized protocols, with a clear description of any access restrictions
• Interoperable – data and metadata use common standards and open formats
• Reusable – data has a clear licence and thorough documentation that enables reuse

In line with UiB's policy for open research, the principle "as open as possible, as closed as necessary" also applies. Sensitive or rights-protected data can be shared with restricted access.

Researchers meet different requirements for data management plans from research funders. Some examples:

• The Research Council of Norway requires a data management plan, and that data is shared as openly as possible.
• The EU – Horizon Europe – requires a data management plan, and that data is made FAIR, including being shared as openly as possible.

In addition, UiB's policy for open research obliges all researchers affiliated with the university to prepare a data management plan, and to make the data FAIR.

Check the requirements in your funding agreement. The University Library can help interpret them.

The University Library recommends using Fair Wizard Norway, as it contains DMP templates and serves as an online tool. Plan.research-data.no gets you there, and provides DMP guidance and support materials. The University Library can provide general guidance on writing a DMP.

To make your research data visible and accessible, you should choose a discipline-specific archive. re3data.org is the largest and most comprehensive register of available data archives. The register is curated and all listed repositories meet defined quality criteria. fairsharing.org is another curated register of research data archives.

Institutional archives are a good alternative to discipline-specific archives. Researchers at UiB can archive research data in DataverseNO and receive guidance during the archiving process.

If you have large amounts of data, NIRD Research Data Archive (Sigma2) can be an option.

If there is no discipline-specific or institutional archive suitable for your data, general archives such as Zenodo can be a good option.

DataverseNO is UiB's institutional archive for open research data, available free of charge to students and staff affiliated with UiB. 

The archive gives datasets a persistent identifier (DOI) and a structure for standardized metadata. The datasets are published with an open licence, thereby fulfilling the FAIR principles. The University Library's curators provide advice on and preparation of submitted datasets, in accordance with DataverseNO's deposit guidelines.

Research data should be archived in open, non-proprietary formats to ensure long-term access to the files. For more information on archival formats, see DataverseNO's deposit guidelines.

Metadata is structured information that describes, explains, locates and makes it easier to retrieve and reuse data. To make your data reusable and accessible to others in the future, you must create and archive accurate metadata together with your data.

If you archive your data in a discipline-specific or institutional archive, the archive usually defines the metadata standard.

More about metadata standards:
Digital Curation Centre
fairsharing.org

Reusing data with attribution to the data creators requires a licence. For research data it is common to use Creative Commons licences. In general, you should choose as open a licence as possible for research data to ensure that the data can be reused. Be aware that an attribution requirement (CC-BY) can lead to so-called attribution stacking.

For open software licences, choosealicense.com and Open Source Initiative are useful resources.

Although research data should be made available as early as possible, an embargo on the data release can sometimes be appropriate. This may concern, for example, related rights or contracts entered into, or the planned publication of an article or book. Embargo periods and reviewer access are supported by most archives.

To ensure long-term preservation and allow citation, it is recommended to publish source code generated during a research project. Many researchers use Git, a system for distributed version control, to manage their source code. Github and Gitlab (beta) facilitate publishing code in the general research archive Zenodo, which also allows versioning.

It is important to document source code for reuse. See the CodeRefinery page for more information and a checklist.