Reproducibility and open scientific practices are increasingly in demand and needed by scientists and researchers in modern research environments. Our work often require or involve a high level of hands-on collaboration on scientific projects throughout all stages of the research lifecycle. We are faced with obstacles that we have no training for nor knowledge on how to address. Obstacles, that can be as simple as not having a shared way of writing code or managing files, can impede effective collaboration. Or they can be complex, like documenting software dependencies or steps in an analysis pipeline in a way that makes it easy to resolve issues and get the most recent set of results after collaborators have worked on a project. Aside from the impact on collaboration, these barriers can even affect projects with just one primary researcher. Ultimately, this can have consequences on the reliability and reproducibility of scientific results, especially considering that the measures taken to address these barriers are often not explicitly shared in classical science output (like a publication).
With this course, we aim to begin addressing this gap. By using a highly practical, hands-on approach that revolves around code-along sessions (instructor and learner coding together), reading activities, and hands-on exercises, our overarching learning outcome is that at the end of the course, participants will be able to: Describe what an open, collaborator-friendly, and nearly-automated reproducible data analysis pipeline and workflow looks like, and then create a project that follows these concepts by using R.
Our specific learning outcomes are to:
And we will not learn:
Because learning and coding is ultimately not just a solo activity, during this course we also aim to provide opportunities to chat with fellow participants, learn about their work and how they do analyses, and to build networks of support and collaboration.
The specific software and technologies we will cover in this course are R, RStudio, Git, GitHub, and Quarto, while the specific R packages are {renv}, {precommit}, {styler}, {targets}, and several of the {tidymodels} packages.
This course is designed in a specific way and is ideal for you if:
Considering that this is a natural extension of the introductory and intermediate r-cubed courses, this course builds on the knowledge and skills learned during those courses, including Git, RStudio R Projects, functions, functional programming, and Quarto / R Markdown. If you do not have familiarity with these tools, you will need to go over the material from the introductory and intermediate courses beforehand (more details about pre-course tasks will be sent out a couple of weeks before the course).
While having these assumptions help to focus the content of the course, if you have an interest in learning R but don’t fit any of the above assumptions, you are still welcome to attend the course! Priority is given to participants employed at Danish institutions and in the Danish life science industry. If the event is overbooked, the DDEA reserves its right to select participants based on the defined requirements and country of employment.
Participants will have to reserve time in their calendar to do pre-course tasks.
Considering that this is a natural extension of the introductory and intermediate r-cubed courses, this course builds on the knowledge and skills learned during those courses, including Git, RStudio R Projects, functions, functional programming, and R Markdown. If you do not have familiarity with these tools, you will need to go over the material from the introductory and intermediate courses beforehand (more details about pre-course tasks will be sent out a couple of weeks before the course).
Deadline to complete pre-course tasks: 1 November 2023
Make sure to bring your own laptop, since the course includes hands-on learning.
The DDEA offers accommodation in Copenhagen to all participants living outside Copenhagen area for the nights of 8 & 9 November. Please state if you need accommodation when you register.
The DDEA organises a Networking Dinner both 8 & 9 November. Please state if you would like to join these when you register. And if you have any special diet requirements.
A course certificate will be given to all attending participants at the end of the course. Full participation is required to attain 2.5 ECTS points.
Please note that it is free of charge to participate in the course however the DDEA will charge a no-show fee of 1000 DKK if you do not show up and have not unregistered from the course prior to its start.
EAN: 5798 0022 30642
Reference: 1025 0006
CVR: 29 19 09 09
