Research Data

General

Research data is the foundation of knowledge. Data generated or collected during the research process are of high value to the research team and other researchers. Good research data management (RDM), in addition to promoting further research, collaboration and innovation, is essential for upholding research integrity and quality of research outputs.

To uphold trust in research findings and further enhance academic and social benefits of research work, Nord University supports the FAIR principles for the management of research data and adheres to the principles of the Ministry of Education, Research Council of Norway and the EU for sharing research data—‘As open as possible, as closed as necessary’ and ‘Open as standard’.

FAIR principles apply to all types of research data.

Services

RDM support at Nord University (from the University Library) caters to the needs of researchers across career stages. The services are aimed to facilitate FAIR-compliant research data management at all stages of research projects.

You can find help in:

Writing data management plans (DMPs)

Archiving research data in trustworthy repositories

Grant application writing (regarding Open Data practices, etc.)

Check out and register for courses and webinars to become apprised of the current developments and requirements. Research data café can be used to ask questions and discuss issues while working on specific RDM activities.

Important links

Guidelines relevant for notification to Sikt and DMP

Guidelines research data management at Nord University.pdf

Guidelines for storage and sharing of data at Nord University (in Norwegian)

Send notification to Sikt

Notification Form for personal data

Sikt's templates for information letters to

participants in research projects

Data Management Plan tools

Sikt's DMP template

Horizon Europe DMP template

DMPonline

Data Stewardship Wizard - Elixir Norway

EasyDMP

Argos

Data archives

DataverseNO

Sikt

Send e-mail to:

research-data@nord.no

  • Webinar series on research data management, Spring 2025  — A deep dive into research data management

    Click here to sign up

    Full schedule

    7 April 2025 (Monday) 

    9:15-9:50 A.M. FAIR data—What does making data available mean?  — Sagnik Sengupta (Senior Research Librarian, Nord University) 

    Break (10 minutes) 

    10:00-11:00 A.M. FAIR-ing and sharing qualitative data — Agata Bochynska (Senior Academic Librarian, University of Oslo)  

    9 April 2025 (Wednesday) 

    10:00-10:45 A.M.  Data Management Plan (DMP)—Boon or bane?  — Sagnik Sengupta (Senior Research Librarian, Nord University) 

    10 April 2025 (Thursday) 

    09:30-10:30 A.M. Data privacy in research — Toril Irene Kringen (Data Protection Officer, Nord University)

    11 April 2025 (Friday) 

    09:00-10:00 A.M. DataverseNO—A national platform for research data archiving – Sagnik Sengupta (Nord University) 

    29 April 2025 (Tuesday) 

    10:00-11:00 A.M. FAIR qualitative data in health and nursing sciences —  Huw Haugland-Grange (Senior Academic Librarian, University of Tromsø) 

    CANCELLED - 13:00-14:00: Consortia, contracts and sharing of data — Tor Gustav Sigeman (Senior Advisor, Nord University) 

  • Discuss, ask and implement your data management strategy

    Click here to participate

    Upcoming dates for Research Data Café:

    13 Nay 2025

    28 May 2025

    11 June 2025

    25 June 2025

Contact person

Frequently discussed topics

    • As a general rule, Nord University has ownership of all research data generated by its employees.
    • Research data shall be accompanied by a Data Management Plan (DMP​​).​​ 
    • Research data shall be archived either in Nord University's collection in DataverseNO or in other suitable and reliable repositories, ensuring Nord University’s continuous access to the data.
    • As a general rule, research data shall be made openly accessible for further use for all relevant users, except when there are legal, ethical, security-related or commercial reasons for not doing so.​

    See Nord University's complete guidelines for res​earch data management.

    See also the Norwegian Government's National strategy on access to and sharing of research data.

  • Research data constitute the basis of scientific knowledge. Any registries, records and reports that are generated and/or handled/analyzed during the research process, considered scientifically interesting and/or have scientific potential are an integral part of research data. Research data can be in the form of, but not restricted to, numbers, text, images and audio.

    • How to write a data management plan?
    • How to handle personal data in research projects?
    • Collaboration projects, collaboration agreements and sharing of data
    • Ethical assessments when using research data
    • How to classify and store active research data?
    • How to structure, document and archive research data?

    Powerpoint presentations and more information at iNORD. If you have any questions, contact us at research-data@nord.no.

  • The FAIR principles are overarching principles for data management. FAIR stands for Findable, Accessible, Interoperable and Re-usable. The main purpose with FAIR data is to enable others to find, understand and re-use research data.

    The FAIR principles in a nutshell

    The FAIR principles (Wilkinson et al., 2016) entail the following:

    • Findable: Data is easy to find. Data and supplementary materials have sufficiently rich metadata and a unique and persistent identifier.
    • Accessible: Data is accessible. Metadata and data are understandable to humans and machines. Data is deposited in a trusted repository.
    • Interoperable: Data can be combined and re-used across e.g. systems and institutions and over time. Metadata use a formal, accessible, shared, and broadly applicable language for knowledge representation.
    • Reusable: Data can be re-used. Clear usage licenses and accurate information on provenance.

    Source: libereurope.eu

    An important aspect of FAIR data management is the choice of data repository. Follow this link for more information.

  • Does your project collect and process personal information?

    All projects collecting and processing personal information must notify Sikt. A notification can be prepared here. Deliver your notification at the earliest. Researchers must receive the approval before data collection can begin.

    Remember to attach supporting documents, e.g., information letters to study participants, interview guides etc. to allow Sikt to assess and guide you effectively. In its feedback, Sikt will ensure that the best practices are adhered to in all research projects.

    For help in filling out the notification form, contact research-data@nord.no. Complex issues will be resolved in consultation with Nord's Data Protection Officer or IT, if needed.

  • All research projects must have a DMP

    • A DMP shall be prepared within the first 6 months of the project
    • A DMP is obligatory for admission to a PhD programme
    • Use version control
    • The DMP will be updated throughout the project period
    • The updated DMP should be archived along with other files of the research project

    Information on the following will be needed to write a DMP

    Data characterization and classification

    To write a DMP, it is recommended that you have the project plan ready with the following details in a comprehensive table:

    • Research activities to be conducted in each work package.
    • Data to be collected in each work package
    • Which work packages will contain personal information or other types of sensitive data
    • Who will have access to sensitive data
    • Will the sensitive data be shared with project partners within or outside EU/EEA?
    • Has a Joint Data Controller Agreement been prepared? (This is relevant only for collaborative projects with multiple project partners)

    Data characteristics

    Here are some questions that will help you characterize your data and fill out the DMP with ease:

    • What kind of data will you collect?
    • Will there be documents, photos, audio, video, codes from a programming language?
    • What will be the approximate volume of the data?
    • For your processed data, willl you use files that can be used without purchasing licenses for a specific program (i.e., will you use non-proprietary file formats)?

    Data classification

    Data are classified according to the nature and volume of sensitive information. One of the key questions considered is, "How much damage will be caused to individuals and/or institutions if the data is not suitably protected?"

    Details about classification of research data can be found here (for employees only). This guide (for employees) can help you understand how to/how not to share information.

    In brief, there are four categories of data:

    Green: Contains no sensitive information. Can be shared openly. Anonymized data "may be" considered green data.

    Yellow: Unauthorized sharing of this type of data can lead to some level of harm to institutions or individuals. A large fraction of research data come under this category. Several types of personal data come under this category.

    Red: Data containing large volumes of special categories of personal information, documents that MUST be protected under legal obligations and other types of information which, if shared, can lead to serious losses to institutions or individuals.

    Black: Unauthorized sharing of such data can lead to substantial harm to individuals and institutions. Examples include, but are not restricted to,

    Data classification is the key to developing suitable short-and long-term storage and sharing solutions.

    Daa protection

    See

    See Data protection in research | Nord.no

    Research ethics

    See Research Ethics | Nord.no

    Collection, storage and data sharing solutions

    See guidelines (access for employees only)

    Data archiving solutions

    Green data: Can be archived openly at DataverseNO (Norr University's open data archive), Sikt or any other trustworthy discipline-specific archive.

    Green, yellow & red data: Can be archived at Sikt.

    Black data: Access to black data are managed via TSD.

    Unless a suitable legal basis exists, all data containing personal information are deleted at the end of a project.

  • To increase visibility, reusability, transparency, and thereby research impact and trust in research findings, archiving of data (i.e., long-term storage with persistent identifiers and connections to internet search engines) is essential. Trustworthy data repositories are indexed and can be traced in re3data. FAIR-compliant data archives help you archive research data in accordance with the FAIR principles, as required by major funding agencies such as the Research Council of Norway and Horizon Europe.

    DataverseNO

    • Nord University has its open data archive at DataverseNO
    • Only green data (containing no sensitive information can be archived here)
    • Anonymized data can be published at DataverseNO after additional checks during curation.
    • DataverseNO is a generic archive where all data from disciplines can be deposited
    • Curator from Nord University will follow up and help you during the whole process

    Sikt

    • Archives up to green, yellow and red data
    • Sikt has its own team of curators who will follow up the datasets sent in for curation
    • At Nord University, you can find an overview of Sikt and its services by writing to research-data@nord.no

    Other archives

    There are a many discipline-specific archives where you can choose to publish your data. Some archives are listed below

    Biobank Norway

    CESSDA - Consortium of European Social Science Data Archives

    CLARINO

    Elixir Norway

    GBIF Norway

    Norwegian Advanced Light Microscopy Imaging Network (NALMIN) – NALMIN

    NAPI

    Frontpage - www.norcrin.no

    Openscreen

    Sigma2

  • If your project handles data that need extra protection, Nord University has agreement with UiO’s service Tjenester for Sensitive Data (TSD) for storage. TSD can be used for storing highly sensitive (black) data and sensitive (red) data. In addition to being a storage solution, TSD provides a platform for analysis, processing and sharing of your data with your project partners.

    The project leader can create a project in TSD and the cost of using TSD must be covered by the project funds. The cost of a project in TSD will vary depending on the volume of data and other needs specific to the data handled in the project.

    The basic package of TSD costs NOK 20,500 per year (excluding VAT). This includes:

    • 1 TB storage and backup
    • 1 Windows server VM (2 CPUs, 4 GB RAM). TSD sets up Windows and Linux VM with 2 CPUs, and 4GB RAM. This can be changed depending on the needs of the project 4 CPUs and 16GB RAM without extra costs.
    • 1 Linux VM (2 CPUs, 4 GB RAM)
    • Standard programs and services
    • Possibility of collecting data via Nettskjema.no (Applies only to questionnaires that store data in TSD)

    For services in addition to the basic package, see Price list for TSD (UiO). Check the column for university and high school sector (UH).

    Further information on how to register a project here: how to create a project in TSD. If you have questions or require assistance, contact user assistance for TSD (UiO)

Phase-wise guidance for all research projects