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FAIR Training in ELIXIR Europe

Mateusz Kuzak; Leyla García Castro; Bérénice Batut; Ricardo Arcila; Niall Beard; Melissa Burke; Denise Carvalho-Silva; +10 Authors

FAIR Training in ELIXIR Europe

Abstract

ELIXIR is an intergovernmental organization that brings together life science resources across Europe. These resources include databases, software tools, training events and materials, cloud storage, and supercomputers. ELIXIR's activities are divided into the following five areas Data, Tools, Interoperability, Compute and Training known as “platforms”. The ELIXIR Training Platform coordinates training activities, trains life-science researchers, and helps scientists and developers to find the training they need. One of the goals of ELIXIR is to coordinate these resources so that they form a single interconnected infrastructure. This infrastructure makes it easier for scientists to find and share data, exchange expertise, and agree on best practices, such as best practices for developing and sharing training materials. The FAIR Training Working Group was first informally formed after the “How to make training FAIR” workshop held at the ELIXIR All Hands Meeting in Berlin in 2018. During the workshop, it became clear that there are two different but interdependent topics (1) availability and findability of training materials about FAIR Data Stewardship, (2) making training resources FAIR. Within the Working Group, two Task Forces have been established, and their activities will be highlighted in this talk.

Keywords

FAIR, training, data stewardship, metadata, ontology, bioinformatics

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This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
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This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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