Week 3: Quarto for project management
In-class materials
Project organization and management
To complete this assignment, create a new .qmd file in your in-class notes RProject. Complete this activity by rendering the .qmd file to an html and committing/pushing the resulting files to gitlab.
Project audit
To begin this exercise, please consider a single project (either ongoing or recently completed) that you wish to have as a reproducible and open entity.
Note: Consider “reproducibility” and “openness” here broadly – for example, you might want a project to be reproducible not because you want someone sitting on the other side of the world to reproduce your work, but simply that you want your collaborator or advisor to be able to generate the same results that you are looking at. Or think of “future you” as a collaborator – it is clearly in your best interest to make that “future you”’s life easier by providing context for the decisions you are taking, the data you are collecting, and the analyses you are conducting.
Answer the following questions about the project:
In 3–4 sentences, what are the overall questions you hope to address through this project?
In 3–4 sentences, what are the general steps you have taken so far (or will take) to achieve these objectives?
Please provide a list of all the files you have generated (or anticipate generating) related to this project. Try to be as thorough as possible – e.g. do you have physical and/or digital meeting notes from brainstorming conversations? Data files collected in the lab or in the field? What kinds of scripts does the analysis require, and what files do your analyses generate (e.g. figures, intermediate files, etc.)?
What is your current or anticipated organizational scheme for these files? How often do you conduct data backups?
With whom do you currently share or anticipate sharing project-related files? Which of the files that you are generating do you feel are important to share along with the final “product” to come out of this work (e.g. resulting journal article) to ensure its reproducibility?
What are some “pain points” in your project organization scheme? Are these particular issues that you find yourself confronting on a regular basis? Is there any way to streamline your project organization/setup to help ease this pain point?
More practice with R
Almost all undergraduates in this class are brand new to using R, so I want you all to build up more familiarity with it before we dive deeper into coding next week.
Please use class time and time before class next week to work through the Software Carpentry lessons on R for Reproducible Scientific Analysis: https://swcarpentry.github.io/r-novice-gapminder/.
In this exercise, Episodes 1–3 go through the basics of R, Rstudio, and project management. You may find these good reviews of material we covered in class over the past few weeks.
Note: As explained in Episode 3, I recommend that you avoid getting help from generative AI as you work through this. The reasons for this are explained on the Software Carpentry lesson. In lieu of using generative AI, please istead ask me (Gaurav), classmates, or other human beings (either people you know or people on the internet). Making mistakes is the fastest, most efficient way to get “good” at coding in R at this stage in your career.
At your own pace, please go through Episodes 4–7. We will build off of these in class starting next week.
Please write new code in your Rstudio project, and commit and push it to git. I will not be evaluating/grading this, but will be looking through your repositories next Monday evening to get a sense of how far you have progressed through the lessons.