Library Carpentry is a growing community of instructors and lesson developers whose mission is to teach librarians the tools, techniques and best practices around working with data and using software to automate repetitive tasks. Using the pedagogical practices of live coding, pair programming, discussion and exercises, Library Carpentry creates a safe and collaborative space for important concepts in computing and data, including data manipulation and organization, using the computer to repeat things and the importance of text pattern matching. We teach these concepts using the Unix shell to repeat commands over text and data, regular expressions to match and operate on text strings, and OpenRefine to clean and standardize datasets. Not only do these skills help librarians create reproducible workflows and repeated operations for data-centric tasks, they give librarians a common language with researchers that can lead to a better mutual understanding of data issues and it paves the way to greater collaboration between the library and research departments. In the last two years, Library Carpentry has held two sprints to improve the lesson materials that included over 100 people at 13 sites worldwide. The California Digital Library (CDL) has been awarded a grant from the Institute of Museum and Library Services that funds a two year, full-time North American Coordinator for Library Carpentry and discussions are starting about integrating with Software Carpentry and Data Carpentry. Currently, Library Carpentry instructors are trained and certified through Software Carpentry, and lessons for all of the Carpentries are created and maintained in Github, using the same templates. In the next year, Library Carpentry will map out an infrastructure of the growing community, formalize lesson development processes, expand its pool of instructors, and create more instructor trainers to meet the demand for Library Carpentry workshops around the globe.
http://librarycarpentry.github.io/https://github.com/LibraryCarpentry
Presentation for this event: https://doi.org/10.5281/zenodo.1112373
