Share, archive, and reuse research data

In this half-day course in research data management, participants will gain insight into the potential in archiving and reusing research data in line with the FAIR (Findable, Accessible Interoperable, Reusable) principles.  

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Target Audience

  • PhD students,
  • Postdocs, and
  • Researchers and research support staff at the University of Oslo and Oslo University Hospital.
  • External participants are welcome to attend as long as there are free spots left.

Learning Objectives

In this 3-hour course we will give an introduction to the FAIR principles and data sharing requirements. Participants will also become familiar with the use of persistent identifiers, licenses, metadata standards, research data archives, and research data search services. 

The course is a combination of practical exercises and lectures, allowing for discussions on participants' own data as well as any challenges or opportunities related to data sharing. Please note that we assume no or very little previous knowledge on the topic as this is a beginner’s course.

 
Knowledge
After the course, the participant will have: 

  • knowledge of political and practical aspects of open data and FAIR data
  • basic knowledge of licenses and rights when sharing and reusing research data
  • basic knowledge of widely used metadata standards and interoperability principles for research data
  • good knowledge of different types of archives or repositories for research data and archiving and searching in these.

Skills 
After the course, the participant will be able to:  

  • archive research data in line with applicable requirements and recommendations
  • document and describe research data for their retrieval and reuse
  • find and evaluate research data for reuse
  • choose suitable licenses for your own research data and understand which restrains different licenses give for reuse and further sharing of research data.

Prior knowledge and implementation

  • Prior knowledge: None is required
  • Format: Physical course
  • Language: English
  • Preparations: No preparations necessary
  • Bring: PC
  • Course certificate: No
  • Lunch: No

Price

The course is free of charge

Contact

Ivana Malovic, Live Kvale

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Other relevant courses

This workshop is part of the Data Management Week 2026 Autumn Edition

Tags: Research data management, Data sharing, DataverseNO, Documentation, Metadata, Research data curation
Published Aug. 31, 2026 4:28 PM - Last modified Oct. 7, 2026 3:02 PM