Getting Credit For Your Hard Work

Objective

Learn the wrap-up steps to publish/archive a research compendium with a DOI. Understand reproducible computational environment. Learn renv and discuss Docker (concept).

Lesson Outline

  • Why share code?

    • Facilitate discussion
    • Show figure from Maitner et al. (2023)
    • Higher citations
    • To “pay it forward” to other researchers
    • To demonstrate your skills
    • To facilitate error correction

  • Getting credit for code

    • Code is not cited often, but partly because it’s not made easy to cite

  • CITATION.cff

    • Show CITATION.cff files for this repo and maybe one for a research compendium
    • Show “cite this” button on GitHub
    • Show CITATION.cff creation tool CFFINIT
    • Maybe mention cffr::cff_validate()

  • Archiving

    • Most participants probably won’t be ready to follow along with their own repos, but we will be there to help when they are ready
    • Demo archiving a repo with Zenodo using this repo
    • Add DOI badge to readme
    • Update CITATION.cff with DOI

  • renv

    • Discuss why
    • Ask students to activate renv for a project and inspect files it creates (have co-instructor share screen)
    • Explain how renv works, especially renv::status() , and renv::snapshot()
    • Clone co-instructor’s repo with renv files
      • Show that no packages are available initially (project is isolated)
      • run renv::restore()

  • Docker (if time)

    • Conceptual overview of what it is

    • Discuss how tools like renv and Docker both help and hinder reproducibility

Homework

  • Prep for showcase session

References

Maitner, Brian, Paul Santos-Andrade, Luna Lei, George Barbosa, Brad Boyle, Matiss Castorena, Brian Enquist, et al. 2023. “Code Sharing Increases Citations, but Remains Uncommon.” https://doi.org/10.21203/rs.3.rs-3222221/v1.

Citation

BibTeX citation:
@online{scott2023,
  author = {Scott, Eric and Diaz, Renata and Guo, Jessica and Riemer,
    Kristina},
  title = {Getting {Credit} {For} {Your} {Hard} {Work}},
  date = {2023},
  url = {https://cct-datascience.github.io/repro-data-sci//lessons/10-get-credit/notes.html},
  doi = {10.5281/zenodo.8411612},
  langid = {en}
}
For attribution, please cite this work as:
Scott, Eric, Renata Diaz, Jessica Guo, and Kristina Riemer. 2023. “Getting Credit For Your Hard Work.” Reproducibility & Data Science in R. 2023. https://doi.org/10.5281/zenodo.8411612.