Section 3 Skills Workshops
Short format workshops that run over one or more days can be a great way to bring people together to share skills. For workshops to be most impactful, it is important to use good quality lessons and have them taught by prepared instructors. The Carpentries supports and mentors a global community of instructors and lessons they can teach.
3.1 Software Carpentry
Overview of Software Carpentry workshops
Software Carpentry aims to help people begin to think computationally about the work they do. It does this by introducing the shell for task automation, then by introducing a programming language such as R or Python, and then by bringing in version control systems such as Git to ensure that research work done can be easily retrieved, repeated, or adapted for other uses. Using these methods, learners can lay the foundation for performing open, reproducible research.
Software Carpentry maintains lessons in the Unix Shell, Git, R, Python, SQL, Make and Mercurial. Software Carpentry lessons focus on teaching tools in a discipline-agnostic way, in order to help researchers from all disciplines develop skill with the tools. Software Carpentry lessons aren’t meant to be exhaustive and comprehensive enumerations of all possible features of a particular tool. Instead the lessons seek to strike a balance of reducing cognitive load, while empowering the researcher to have a better understanding of how the tool could be applied in their workflow.
3.2 Data Carpentry
A Data Carpentry workshop teaches the core skills for working with data effectively and reproducibly.
When working with data, it’s often difficult to figure out what skills to learn or how to get started learning them. In Data Carpentry, we identify the fundamental skills needed in a given domain and develop and teach these skills in hands-on, two-day, interactive workshops. Workshops are currently designed for people with little to no prior computational experience and are domain-specific, so that researchers are working with data most relevant to their own work. They follow a narrative structure, working with one dataset through the whole data lifecycle from data and project organization to data analysis and visualization.
Data Carpentry currently have curriculum in:
- Geospatial data
- Social sciences
3.3 Library Carpentry
Library Carpentry aims to help people in library and information roles develop software and data skills.
Library Carpentry has nine lessons in the works, some more mature than others. New lessons are being drafted around FAIR principles and digital preservation.
|Data intro for librarians||An introduction to data structures, regular expressions, and computing terms|
|Unix Shell||An introduction to command line interfaces and task automation using the Unix shell|
|OpenRefine||An introduction to cleaning up and enhancing a dataset using OpenRefine|
|Git Intro for Librarians||An introduction to version control using Git and GitHub for collaboration|
|SQL for Librarians||An introduction to relational database management using the SQLite tool|
|Webscraping||An introduction to extracting structured data from websites using a range of tools|
|Tidy data for librarians||An introduction to good data organisation, which is the foundation of much of our day-to-day work in libraries|
|Introduction to Python||An introduction to Python, a general purpose programming language|
|Data Intro for Archivists||An introduction to data structures, regular expressions, and computing terms for archivists|