Topic
Making research software findable, accessible, interoperable, and reusable: citation, metadata, and discoverability.
Related standard: FAIR4RS Principles (RDA)
This short course is teaching tools and practices for producing and sharing quality, sustainable and FAIR (Findable, Accessible, Interoperable and Reusable) research software to support open and reproducible research. The course can be delivered over 2 full or 4 half days.
This lesson covers the implementation of CI/CD pipelines in research software projects, focusing on automating tests, builds, and deployments using GitLab CI.
A comprehensive reference guide covering collaboration practices in open research — community setup, GitHub workflows, code review, meetings and events, leadership, and research infrastructure roles. Part of The Turing Way open handbook.
A set of practical computing habits every researcher can adopt — covering data management, code organization, collaboration, version control, and project structure.
This course aims to teach a core set of established, intermediate-level software development skills and best practices for working as part of a team in a research environment using Python as an example programming language (see detailed learning objectives below).
Prerequisites
Modular Programming with PythonThis lesson covers modular programming in Python, explaining how to write reusable code in modules, organize codebases, and test them to improve collaboration and maintainability.
This session aims to introduce the use of Docker containers with the goal of using them to effect reproducible computational environments. Such environments are useful for ensuring reproducible research outputs, for example.
A comprehensive reference guide covering all aspects of reproducible research — version control, testing, data management, CI/CD, open research, licensing, and more. Part of The Turing Way open handbook.
Practical, low-barrier approaches to making research software citable, discoverable, and reusable — including CITATION.cff, licensing, metadata, and FAIR principles.
This course provides an overview of key skills for Research Software Engineers, including software design, version control with Git, testing with pytest, and project management.
Prerequisites
Modular Programming with Python