Day 3

Day 3:

  1. Portable file paths with here
  2. Managing R dependencies with renv
  3. Sharing your data

Does the package renv sound familiar to you?

😯 I’ve heard of it

👍 I’ve used it

👏 I use it all the time

❤️I don’t have a clue

Excercise

Restore an environment

  1. Download this reproducible project.

  2. Open the project and run renv::status() in the R console. What’s the status of the packages?

  3. Run renv::restore() in the R console and proceed.

  4. Run renv::status() again to check that the project is in a consistent state.

  5. Render analysis/report.Rmd to make sure that it worked.

If you work with data, what’s the typical size?

😯 A few megabytes (less than 100 Mb per file).

👍 A lot of small files (more than 50 Gb in total).

👏 Chunky files (more than 100 Mb).

Choose an emoji from Reactions

Permissions

  • Are you even allowed to share your data?

  • Proprietary information / licences

  • Privacy (personally identifiable information)

  • If sharing derived data only. What is the licence of the original data?

Small data

  • A few megabytes.

  • You can keep it inside the git repository.

  • If on GitHub:

    • No more than 100Mb per file
    • No more than 5Gb in total

  • Warning: size of the repo >> size of the data

Larger data

  • GitHub release (see piggyback package)

  • External data repositories:

    • Provide DOI
    • Data versioning

  • figshare

  • Open Science Framework

  • Zenodo

Preparations for day 4:

  1. Reproducible computational environment with Docker
    • Follow the instructions here
    • Make sure your docker installation works!