UiT Research Data Portal

Management of research data at UiT has been a project in development since 2015. The project is conducted in close collaboration with the Department for Research and Development, the IT Department and the University Library.

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

Some important points

• 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.

Background

Good management and sharing of research data is a key principle for UiT The Arctic University of Norway. The principle is rooted in the value of increased transparency and quality of research, and in our social mission as a broad-based research university in the North. UiT endorses the principles for research data management of the Research Council of Norway and the EU – «Open as standard» and «As open as possible, as closed as necessary».

The National strategy for research data (Ministry of Education, 12/2017) identifies three basic principles for publicly funded research data in Norway: 1) Research data should be as open as possible and closed as necessary. If no legitimate considerations stand in the way, research data shall be facilitated for open access. 2) Research data should be handled and organized in a way that optimises the value for future re-use. 3) Decisions on archiving and facilitating research data must be taken in the research communities.

The purpose of the Principles and guidelines for research data management at UiT is to clarify responsibility and provide guidance about how the institution and its employees shall manage, share, and archive research data in line with the institution’s administrative, financial, and ethical guidelines.

The University Library offers a series of courses on research data management. Read more about them at site.uit.no/rdm-training. 

All courses are offered in English and Norwegian.

A list of future courses can be found un in the right-hand menu at the UiT Research Data Portal.

UiT and research funders such as The Research Council of Norway and the European Research Council require a research project to provide a good management plan for gathering, handling, archiving and sharing of data.

If your research project comprises of several sub-projects/work packages and have different funding sources, we recommend that you create a combined data management plan where you describe data handling for each of the various sub-projects/work packages.

There are a range of templates for data management plans, depending on the type of project:

• If your project is subject to notification to NSD and or approval by REK, we recommend you to use the NSD template.
• If your project is funded by Horizon 2020 we recommend you to use the template in DMPonline.
• For all other projects we recommend you to use the UiT template.

Some examples of DMPs are available here.

At UiT, the following guidelines apply for follow-up of data management plans: Retningslinjer for oppfølging av datahåndteringsplaner ved UiTs enheter (in Norwegian). The PhD / research administration at your faculty can provide more information about this.

For guidance and feedback on your DMP you can contact the University Library at researchdata@hjelp.uit.no. This will also help us plan and improve our support services.

Research data is an essential part of most research projects, and should be managed based on best practice throughout the project period.

Agreements and templates ...

External infopages about Data Management Plans:

• NFR
• Horizon 2020

Processing and storage of research data can be challenging, especially for large datasets and data that are sensitive or require secure storage.

Here are some general tips for good data management:

• Use consistent and comprehensible file names.
• Document data right from the start of the project.

More information can be found here.

More about management and storage of research data:

Research data management (UB)

Information Security Management System at UiT (only in Norwegian)

Section for Digital Platform and Operation

Personal storage and file sharing (Box, provided by UNINETT)

Transferring large files (Filesender, provided by UNINETT)

Secure data storage and encryption (only in Norwegian)

Research funders usually require that data, resulting from the funded research project, are archived in a proper manner. In addition, journals can have requirements or recommendations for making background data for publications available. There exists a wide range of research data repositories that can satisfy such requirements. Here are some recommendations on how to choose a repository that suits your data:

1. In some cases, the funder or journal has a requirement to use a specific repository.
2. Use a repository already established for your research domain to preserve the data following the standards in your discipline. In order to find a subject-specific repository, you can use the repository registry re3data (https://www.re3data.org/). There are several criteria to keep in mind when searching for a repository. For more information, have a look at this OpenAIRE-guide.
3. If you are researcher at UiT, you can archive your data in UiT’s institutional repository for open research data, UiT Open Research Data (https://opendata.uit.no/). UiT Open Research Data is CoreTrustSeal-certified as a trustworthy and sustainable repository, ensuring the long-term preservation of archived data. Here, each dataset is assigned a DOI and an automatically generated reference for use in publications. Data archived in the repository will become searchable in discovery services like Google Dataset Search. The repository also has version control, whereby all changes made in the dataset after initial publication are registered and made visible. More information and user guides can be found on this info page: https://info.dataverse.no/.
4. For data containing person-identifying information, we advise you to use NSD’s repository (https://www.nsd.no/en/archiving-research-data/).

You can also contact us at researchdata@hjelp.uit.no for assistance in finding a repository that is suitable for your data.

Regardless of the repository, you should prepare your data according to best practice before you archive them. More information about this can be found here. We also recommend you always to use your ORCID.

More background information about choice of data repository can be found here:

• OpenAIRE Guides for Researchers: How to select a data repository? https://www.openaire.eu/opendatapilot-repository-guide
• Science Europe - Practical Guide to the International Alignment of Research Data Management - Extended Edition. https://www.scienceeurope.org/our-resources/practical-guide-to-the-international-alignment-of-research-data-management/

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

NSD is the Data Protection Official for research and student projects, and provides advice and guidelines. Here you can take a test to find out if your project is subject to NSD notification.

REC is the regulatory committee for medical and health research projects under the Health Research Act. NSD can be used for guidance before applying to REC for approval of the project, see ethics and privacy in health research at UiT (only in Norwegian).

Personal and sensitive data will be stored securely throughout the project period and after the end of the project, see secure data storage and encryption at UiT (only in Norwegian).

The Tromsø Study (Tromsøundersøkelsen) is Norway's most comprehensive and most-visited population survey that spans more than 40 years. All researcher-affiliated institutions with research expertise can apply for access to analyze data from the Tromsø Study. Research on material from the Tromsø Study has contributed to increased knowledge of health and disease and has contributed to better treatments for patients, both nationally and internationally.

Information on how to apply for access to data from the Tromsø Study can be found here.

Information on how to apply for access of data from the Tromsø Study can be found here.

Other types of research data obtained at UiT can be found in UiT Open Research Data.

What is research data?

Principles and guidelines for research data management at UiT defines research data being: "all registrations, notes, and reporting which are produced or arise in the course of research, and which are regarded as being of scientific interest and/or scientific potential. The format of these may include, but is not limited to, numbers, text, source code, photographs, films, and sound."

Does UiT have a research data management policy?

Yes, Principles and guidelines for research data management at UiT are available here. Its purpose is to clarify responsibility and provide guidance about how the institution and its employees shall manage, share, and archive research data in line with the institution’s administrative, financial, and ethical guidelines.

What is a data management plan (DMP)?

A data management plan (DMP) is a brief document that describes what kind of data you will be collecting or generating, and how, during the course of your research, and how you will store, preserve, describe and manage the data during the project. Furthermore, the DMP includes information on who the responsible parties will be, how you plan to archive and share the data, and where you will preserve the data for the long-term. The researcher shall write a data management plan in an early phase of the project and preferably within six months of the start of the project. The DMP is updated throughout the research process, as needed, to reflect the reality of project activities.

Who is responsible for implementing, reviewing and revising the data management plan (DMP)?

For research at UiT not organized as a project, the employee carrying out the research is responsible for the research data management. For research projects, the project manager is responsible for the research data management unless otherwise stipulated and agreed by contract (see section 4.1 of Principles and guidelines for research data management at UiT for more details).

Where can I find a data management plan (DMP) template?

There are different templates, all depending on the type of project:

• If your project is subject to notification to NSD and or approval by REK, we recommend you to use the NSD template.
• If your project is funded by Horizon 2020 we recommend you to use the template in DMPonline.
• For all other projects we recommend you to use the UiT template.

What is metadata?

Metadata is structured information that describes, explains, locates, and makes it easier to retrieve and use an information resource. In order to help make your data reusable and accessible to you and others in the future, you need to create and archive accurate metadata along with your data.

What file formats enable sharing and long-term storage?

Some file formats are more likely to allow long-term readability than others. We call such formats persistent. Persistent formats are usually:

• non-proprietary
• open, with documented international standards
• in common usage by the research community
• using standard character encodings, preferably Unicode (e.g. UTF-8)
• uncompressed (space-permitting)

To get an overview of persistent vs. non-persistent file formats, please see here. When archiving your data to an archive, please make sure you add your files in a persistent format in addition to the original file format. Make also sure that all of your files contain a valid file extension, e.g. .txt, .pdf.

How do I save or convert my data files to persistent file formats?

For information on how to convert your data into persistent format, please see here.

How do I describe/document my data in order to make them reusable?

For information on how to describe your data, please see here.