Research data portal

Good research data management and open sharing are also essential for promoting transparency and quality in research and for UiT to fulfill its social mission as a broad-based research university. 

Research data is all registrations, records, and reports generated or obtained during research that are considered to be scientifically interesting/have scientific potential. The registrations can take the form of numbers, texts, source codes, images, film, and sound, among other things. -  Principles and guidelines for the management of research data at UiT 

The research data life cycle illustrates the various stages that research data undergoes, from planning to reuse. The cycle can help in getting an overview of the various tasks and areas of responsibility associated with each stage, as well as linking the various data handling activities to the overall plan of the research project. Datasets that are well-documented and well-organized can be efficiently shared and reused long after the project is completed.

If you want to learn more about the research data lifecycle you can watch the following video: The research data management life cycle (DocEnhance Data Stewardship course - YouTube)

On March 9, 2017, the University Board at UiT adopted Principles and guidelines for research data management at UiT. The regulations apply from the 1st of September 2017.

The guidelines' goal is to:

"To clarify responsibilities and give guidance on how the institution and personnel should manage, share, and preserve research data in accordance with the administrative, financial, and research ethical requirements of the institution." Principles and guidelines for research data management.

The principles should not be an administative workload, but rather an integral element of good research practice.

Important information

• As a general rule, UiT owns all research data produced by employees at UiT.
• All projects that involve research data must have a data management plan.
• Research data shall be stored and archived at UiT-approved facilities/repositories.
• Research data shall be made openly available for further use provided that there are no legal, ethical, security or commercial reasons for not doing so.
• The rights to use and/or publish research data must not be transferred to commercial entities unless UiT retains the ability to make the data openly available for reuse.
• UiT shall provide support services that span the complete life cycle of research data management, i.e. support services for:
• Research data management training
• Creating data management plans
• Data processing and storage
• Data archiving
• Agreements and license determination

If you'd want to learn more about archiving research data, a webinar on the subject is held each semester. There will also be a webinar on how to archive in DataverseNO. On the course page, there are PowerPoint presentations with more information.

Open sharing of research data is a key principle to increase transparency and quality of research, and for UiT to fullfill its mission in society as a broad university. Research funders and scientific journals also more and more often require research data to be managed in a responsible way and to be made open available. By doing so, research data becomes verifiable and can be used to the fullest potential. 

UiT agrees with the Research Council of Norway, the EU, and the Ministry of Education and Research's explicit objectives and guidelines for the management of research data - "Open as standard" and "As open as possible, as closed as necessary".

The researcher must make study data openly available for use by all relevant users, unless there are legal, ethical, security, or commercial reasons not to do so. Data must be archived, either at your own institution or in other relevant and reliable archives, to ensure that UiT has continuing access to the data. - Principles and guidelines for the management of research data

Research data must be made available as early as possible. This means that data used in a scientific publication must be submitted no later than the time of publication. Other data that may be valuable for future research will be acquired at the end of the project.

The scientific community must make decisions about archiving and organizing research data. 

UiT operates a national, generic repository for open research data, DataverseNO. If you are an UiT researcher, you can archive your data in the UiT collection in DataverseNO. The repository is CoreTrustSeal-certified and managed in alignment with the FAIR Guiding Principles for scientific data management and stewardship. More details regarding the archive can be found on the DataverseNO page.

Practical information about publishing research data can be found in the section on Archiving and Publishing.

A webinar on licenses and rights to research data is held every semester for those interested in learning more. A PowerPoint presentation with more material is also available on the course page.

The FAIR principles are best practices guidelines for research data management. The goal is to maximize the societal benefit by facilitating the best possible utilization and reuse of the obtained information values. To put it another way, the FAIR principles ensure that research data is of high quality and can be reused.

The Government's strategy, the Research Council's policy, and the requirements of the EU all encourage the use of research data in accordance with the FAIR principles. The FAIR principles are central to UiT's Principles and Guidelines for Research Data Management. In this approach, UiT contributes to the growth of a global research community in which research data is widely shared. The FAIR principles provide specific recommendations on how to do this by making data FAIR.

It is important to note that FAIR data is not always synonymous with open data. Open data is data that can be freely used and shared. The FAIR principles, on the other hand, are standards that encourage data exchange while adhering to ethical, legal, and commercial limits. As a result, data can be open but not FAIR, or FAIR but closed.

How to make data FAIR

Findable
That is, it is easy to find. This can be accomplished, for example, by:

• Including a lot of descriptive metadata. Metadata is information about your data. Metadata will allow the data to be found in research data search platforms. A metadata standard ensures that metadata is readable by both humans and machines.
• To store the data in a repository that provides persistent identifiers, such as a DOI or Handle.
• To choose an archive (URL) that assures the material is indexed and hence retrievable using relevant search services (eg DataCite and Google Dataset Search).

Accessible
This implies that data is easily accessible. This is primarily about technical factors, yet it is an important consideration when selecting an archiving solution. The term "accessible" refers to:

• That an archive has criteria for securing access to a data set and, where necessary, can provide limited access.
• Even if the data itself has limited access or is no longer available, the metadata must be made publicly available.
• That a defined procedure can be used to gather metadata from an archive.

Interoperable
Data must be open, understood, combined, reused, and processed without restriction across technological systems, institutions, national borders, and time. This means that both data and metadata must be mechanically handleable and capable of "talking together" with data and metadata from other data sets. This will make data exchange between researchers, institutions, or systems easier. This can be accomplished, for example, by:

• Using similar metadata, terminology, and vocabulary standards.
• To add context to data by referencing other relevant metadata and datasets.

Reusable 
This means that the data can be copied and reused. This can be accomplished, for example, by:

• To adequately document (link) and describe data. Documentation, such as a ReadMe file, should assist others in understanding and recreating the data. It will also be beneficial in determining how relevant and usable the data is for reuse.
• To specify specific use licenses. A license specifies how data can be utilized. Preferably, licenses should be machine-readable.

If you want to learn more about how to make your data more FAIR you can watch the following video: The FAIR Data Principles (YouTube - DocEnhance Data Stewardship course)

A good and more extensive reference on why and how to make your data more FAIR can be found on the webpage "How to FAIR". To varying degrees, research data can be FAIR. It will not always be possible to obtain FAIR data as a whole.

In research data management, researchers must also be aware of the general rules that apply in handling personal and sensitive information, see the Research ethics at UiT portal.

All projects involving the handling of personal information must be submitted to Sikt. Notification must be made at least 30 days before the project's start date. 

For projects under the Health Research Act, an application must be submitted to REK (Regional Committees for Medical and Health Research Ethics). An application must be submitted to REK for studies funded by the Health Research Act (Regional Committees for Medical and Health Research Ethics). More information regarding ethics and privacy in UiT health research initiatives can be found at the "Forskningsrutiner for helseforskning" (Norwegian only).

Person-sensitive data must be securely stored both during and after the project's completion. More information can be found at: «Secure storage, collection and processing».