Research data at VID
Research data are defined as "documents in a digital form, other than scientific publications, which are collected or produced in the course of scientific research activities and are used as evidence in the research process, or are commonly accepted in the research community as necessary to validate research findings and results" (EU, 2019, Article 2(9)).
Examples of research data include statistics, observations from fieldwork, interview recordings, software code, and metadata.
Research data management (RDM)
If you collect data for your research project, it's important that you manage it properly, and VID provides guidelines for how you can do so.
Research Data Management (RDM) consists of several steps:
- Creating a Data Management Plan explaining how you will manage data during and after your project.
- Collecting data in an organized and well-documented way.
- Managing data securely throughout the project.
- Sharing, archiving, and, if necessary, deleting data at the end of the project.
Illustration of steps in research data management (RDM)
Data management plan
Contents of a Data Management Plan (DMP), based on Science Europe guidelines
A Data Management Plan (DMP) describes what data will be collected during your research project and how this data will be managed both during and after your project. VID expects that all researchers write a DMP before beginning a research project, and a DMP is a requirement for most external funding.
Need help writing a DMP? Start with one of these templates:
Contact the Research Data Management Team with questions or for additional assistance.
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Research ethics and personal data protection
All data must be categorized into one of the four data classifications
As a researcher you have an obligation to conduct research ethically. The broad principles of research ethics are respect, good consequnces, fairness, and integrity. See VID's Research Ethics page for more information.
In addition, everyone who conducts research at VID must familiarise themselves with VID's Guidelines for the processing of personal data in research and student theses and follow it. It is especially important that you:
- classify your research data based on their sensitivity;
- create an information letter for research participants;
- register your project with Sikt if you are handling personal data; and
- apply to REK if your health research project must be approved by them.
See the sections below for more information.
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Processing and storage
Once you know what category of data you will be working with (see Research ethics and personal data protection section), you can begin to plan how you will process and store data during the course of your project. How data can be collected and stored depends on their category.
VID has a data collection and storage guide that outlines which services/locations can be used for each data category. The tables below provide a quick reference of the recommended data collection methods and storage locations for research data, depending on the data's categorization.
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Data sharing and reuse
Illustration from Wikimedia Commons by SangyaPundir. Used under a CC BY-SA 4.0 license.
According to VID Guidelines, research data should be archived and shared, unless there are legal, ethical or security reasons for not doing so (section 2.2). VID supports the FAIR principles, that data should be Findable, Accessible, Interoperable and Reusable. Properly sharing research data can help increase the value, validity, and visibility of your research.
Of course, some data (data with private or confidential information, for example) cannot be shared. The goal is that research data be "as open as possible, as closed as necessary".
Where can I share my data?
- DataverseNO: If your data can be shared publicly, you can publish your data in VID's archive on DataverseNO, a national archive for open data operated by UiT. Practical information about publishing research data can be found here. Contact the Research Data Management Team for more information.
- Sikt has an accredited archive system for archiving research data within the social sciences and humanities, and for selected fields within medical and health research. See Sikt's Archiving research data page for addition guidance and requirements.
- You can also use international data repositories like the Open Science Foundation (OSF), figshare, or Zenodo.
- You can also use re3data to search for potential repositories in your own field.
Where can I find data to reuse?
You can use international services like Google Dataset Search, BASE, and DataCite to search for relevant datasets. There are also several Norwegian sources of data that you can use, some of which are outlined below. Remember: If you use someone else's data, remember to properly cite it!
Data citation example
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Research Data Management Team
The Research Data Management Team answers questions and provides advice on the management of research data and processing personal data in research projects at VID. We also offer courses and training. Follow VID's arrangments calender for upcoming coures or contact us to arrange courses or training for your research group, supervisors etc. For questions related to research data management, contact us at forskningsdatahandtering@vid.no.
Adapted from UiT The Arctic University Research Data Portal
Last updated: 26.09.2024 by Jennifer Thøgersen