Course Description
The Workflow for Open Reproducible Code in Science (WORCS) is a step-by-step procedure to make a research project open and reproducible, compliant with the FAIR principles (Findable, Accessible, Interoperable, and Reproducible), and the TOP-guidelines (Transparency and Openness Promotion). WORCS is an easy workflow that can be used either in parallel to, or in absence of, existing institutional requirements - and yet can be extended to meet advanced users’ needs. WORCS is based on universal reproducibility principles - which are relevant regardless of your preferred analysis software - but for R-users, the workflow is implemented in a package that automates most steps. The morning session of this workshop focuses on the fundamental principles of reproducible science, including a live demonstration of creating a reproducible project using the WORCS R-package. Special attention is devoted to data sharing and alternative solutions when data cannot be shared. The afternoon consists of two specialized sessions: one on automatically reproducing your analyses in the cloud to prevent user error and provide even more transparency, and one on using the R-package targets together with WORCS to only reproduce code if it, or its inputs, have changed. This eliminates redundant computation, which saves time and is more environmentally friendly. This workshop presupposes a passing familiarity with R, and requires installing free software prior to the meeting. Throughout the workshop, students practice implementing the workflow with their own existing analyses - or with mock analyses for those who do not yet have their own project. Students are thus encouraged to bring data and code for an existing research project that they want to make reproducible.
Prerequisites
A basic understanding of R is expected for this workshop.
To set up you computer for WORCS you can follow the following instructions: https://cjvanlissa.github.io/worcs/articles/setup.html
Reading Materials
Required
Van Lissa, C. J., Brandmaier, A. M., Brinkman, L., Lamprecht, A. L., Peikert, A., Struiksma, M. E., & Vreede, B. M. (2021). WORCS: A workflow for open reproducible code in science. Data Science, 4(1), 29-49. https://doi.org/10.3233/DS-210031
Optional
Pages 10-20 of Peikert, 2023 (“What makes transparency necessary?” to “Transparency about statistical models: Computational reproducibility”) https://aaronpeikert.github.io/thesis/manuscript.pdf
Capacity
This course has a maximum capacity of 25 participants.
Time and Location
This workshop will be held on-site only at Eindhoven University of Technologyon October 23, 2024. Details will be provided to all attendees over email after registration for the workshop.
Workshops start from 9:30 to 16:30 with a lunch break from 12:30 to 13:30. Lunch will not be provided but can be purchased at the university canteen or the on-campus supermarket.
Registration
To register for this workshop, please complete the following form by Oct 10th. Note that your registration will be considered finalized only after receiving a confirmation email.
Registration Form
Instructors
dr. Casper van Lissa
Caspar van Lissa is associate professor of social data science at the department of Methodology & Statistics, chair of the Open Science Community Tilburg, and board member of the Tilburg Young Academy. His research addresses the epistemological implications of machine learning for theory formation in the social sciences, evidence synthesis (summarizing existing research quantitatively and qualitatively), and open reproducible science. He is an advocate for open source research software and has (co-)authored ten R-packages.