FAIR

Så langt er Norden nået med FAIR-arbejdet

EOSC-Nordic-projektet skal bidrage til at identificere problemer og løsninger i forhold til FAIR data (Findable, Accessible, Interoperable og Reusable).

Projektet er vigtigt fordi, de nordiske lande har stor fokus på Open Data, og mange nordiske aktører er allerede dybt involverede i EOSC-aktiviteter. Norden har desuden en stærk tradition for at samarbejde, og den nordiske vinkel er et vigtigt input til EOSC-processen.

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Case 3: TrygFonden

Project framework

This case took a different approach, because TrygFonden found the FAIR principles very interesting in their context as a funding organization. So the case mostly was about how TrygFonden could use FAIR, and how to put up conditions about FAIR, if possible.

Knowledge of FAIR prior to case engagement

Beginning knowledge

When was tools used working towards FAIR in the case

Dansk

Case 2: Sensitive Health Data

Project framework

Timeline: several years
Number of people involved: +10
Number of institutions involved: 1
Funding (EU funding or not): not

Knowledge of FAIR prior to case engagement

No knowledge

When was tools used working towards FAIR in the case

After – in the publishing phase at Danmarks Statistik

Which FAIR tools were used in the case and for what purpose

Dansk

Case 1: FAIR in Biotechnology

Project framework

The case is not based on a single project as such, but various research outputs that involves the use of the Caenorhabditis elegans worm. It’s a very narrow and specific use case, and no specific conclusions can be drawn from this example to be generalised.

Knowledge of FAIR prior to case engagement

No knowledge, but lot of experience in data handling.

When was tools used working towards FAIR in the case

Dansk

M4M: Metadata for Machines gør automatisk deling af data mellem computere mulig

DeiC og GO FAIR Foundation skal frem til midten af september afholde workshops om metadata, der kan udveksles mellem maskiner.

Målet med disse workshops, Metadata for Machines (M4M), er at udvikle metoder og løsninger til, hvordan man rutinemæssigt kan gøre brug af maskindrevne metadata inden for en bred vifte af forskningsfelter.

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