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LIBER Webinar: Library Carpentry – Teaching Data Science Skills & Upcoming Instructor Training

Authors: Erdmann, Chris; Schneider, Juliane; Kane, David;

LIBER Webinar: Library Carpentry – Teaching Data Science Skills & Upcoming Instructor Training

Abstract

Nearly all academics use research software and 69% say their research wouldn’t be practical without it. As the use of technology in research increases, libraries have a new and essential role to play. With appropriate training, libraries can effectively support the data science needs of their researchers. This is critical for the development of Open Science (as highlighted in the report of the European Commission’s Open Science Skills Working Group). This webinar, hosted by Birgit Schmidt of LIBER’s Research Data Management Working Group, will featured speaker Christopher Erdmann. He will introduce The Carpentries: a non-profit organisation that trains people in software development and data science skills. One branch of this organisation, Library Carpentry, is focused on the needs of libraries. Chris spoke about the concept of Library Carpentry: what is taught, why and how, the impact it’s having, and what’s next. We also heard from Juliane Schneider, a Carpentries trainer, and David Kane, a systems library at the Waterford Institute of Technology. They spoke about the process for, and benefits of, becoming a Library Carpentry instructor.

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Keywords

library carpentry, data science, RDM

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
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