References

• This paper in Data Science introduces the WORCS workflow, explains the underlying tools, and illustrates how the worcs package can be used to create a new project that follows the workflow. You can cite WORCS, both the package and paper, using the citation below.

Van Lissa, C. J., Brandmaier, A. M., Brinkman, L., Lamprecht, A., Peikert, A., , Struiksma, M. E., & Vreede, B. (in press). WORCS: A Workflow for Open Reproducible Code in Science. Data Science, 2021. Data Science, vol. 4, no. 1, pp. 29-49. DOI: 10.3233/DS-210031.

• The worcs package documentation & GitHub repo

• Presentations on WORCS:

  • Overview Lectures: https://cjvanlissa.github.io/worcshop/overview_lecture.html & https://bvreede.github.io/worcshop/slides/overview_lecture.html)
  • Presentation at MPIB 2020
  • Presentation at EUR 2020
  • Presentation at EARA 2020

• Videos on WORCS:

  • Workflow for Open Reproducible Code in Science (WORCS), presented at SRCD 2021
  • Workflow for Open Reproducible Code in Science (WORCS), presented at EARA 2020
  • Tutorial: WORCS, Workflow for Open Reproducible Code in Science

• R Markdown cheatsheet