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Metadata for Machines

Metadata for Machines is about helping researchers structure metadata so that computers can automatically find relevant research data.
Data flow
Foto: Colourbox.

The FAIR principles focus on making rich metadata available which can be interpreted by both humans and - especially - machines, ie. computers. Making metadata machine-readable and scientifically relevant requires an effort by the individual disciplines to define its standards.

DeiC is working, in close collaboration with GO FAIR, to develop the format of the workshop. The goal of 2 half-day modules is to help a research group to be able to work concretely with tools and methods to make metadata more FAIR.

DeiC aims to be able to offer this workshop format as an open resource for free use by the universities during 2021. In this context, it may be possible to establish a Train the Trainers program for workshop leaders.

Previous workshops

In 2020 a series of workshops (5 x 2 days) have been held in collaboration with the GoFAIR foundation and Stanford University. Participating in the workshop were two research groups, AnaEE and DTU Wind Energy. The aim of the workshop series was for the two research groups to produce a roadmap (DTU Wind Energy roadmap) for their advanced FAIRification process.

You can find slides from the webinar held in January 2021 here.

In 2021, 2 workshops have been held. The first was held online in January with an international research group (PaRI - Nordic Pandemic Research Infrastructure / Bioinformatics) and the second in September as a physical workshop with a Danish research group from Aarhus University (Department of Environmental Science).

The feedback from researchers leaves us motivated to increase our effort and work on a Train the Trainers concept over the coming months.

M4M citation
Grafik: DeiC.

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25 Oct 2021