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Teaching Data Curation for Reproducibility (Data CuRe)

Home / Project Briefing Pages / CNI Fall 2019 Project Briefings / Teaching Data Curation for Reproducibility (Data CuRe)

January 3, 2020

Limor Peer
Associate Director for Research, Institution for Social and Policy Studies
Yale University

The evidence-based Data Curation for Reproducibility (Data CuRe) Training Program, funded by the Institute of Museum and Library Services (IMLS), will be implemented by the Institution for Social and Policy Studies (ISPS) at Yale University, the Odum Institute at the University of North Carolina, and the Cornell Institute for Social and Economic Research (CISER) at Cornell University. Against a backdrop of growing attention to computational reproducibility in the scientific community, the team has identified a skills gap. This program, a continuing education program targeting academic librarians and data archivists, will offer opportunities for practitioners to augment current expertise with the skills and knowledge necessary to perform intensive data curation tasks, including code review, and provide support to members of the research community burdened with growing expectations for reproducible research practices. The curriculum will be delivered via Library Carpentry, and include lessons that meet quality standards as defined by the FAIR Data Principles the Data Quality Framework.

Additional authors: Thu-Mai Christian, Odum Institute, UNC and Florio Arguillas, Cornell University

https://www.imls.gov/grants/awarded/re-36-19-0081-19
http://cure.web.unc.edu/
https://osf.io/3wkex/

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Filed Under: CNI Fall 2019 Project Briefings, Digital Curation, Project Briefing Pages, Teaching & Learning
Tagged With: cni2019fall, Project Briefings & Plenary Sessions

Last updated:  Friday, January 3rd, 2020

 

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