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course_title author_name
Open Science Tools
Claudio Zandonella

Open Science Tools (Prof Edition):
Making our Scientific Research Accessible and Reproducible

“Researchers are disorganized and chaotic by nature. While this may be the secret of their creativity, it can also lead to costly errors, especially when it comes to coding. In this course, we will learn some software development secrets and introduce coding good practices that may save us lots of headaches. Only by following a structured approach to coding can we ensure the reproducibility of our results and make Science an open-source knowledge development!”

Introduction

The Open Science movement is reshaping modern scientific research. Among its main elements, transparency and reproducibility of the results are fundamental components for improving scientific research. Many researchers, however, lack specific knowledge about recommended practices and tools to guarantee the accessibility and reproducibility of their results. These aspects are particularly relevant when sharing analysis code and data, indispensable elements of scientific research, which unfortunately rarely receives the required attention.

Topics

In this course, recommended practices and main tools for Open Science will be presented focusing on the solutions to guarantee transparency and reproducibility of our results. Among others we will learn about:

  • Open Science Framework (OSF). A free and open-source project management tool for collaborating, sharing, and preregistering our research.
  • Projects Organisation. Lear recommended practices on how to organise our repository structure and document our material efficiently.
  • Functional Programming. Learn how to write code and develop the project efficiently.
  • Git and GitHub. Implement version control and the git workflow in our project, the gold standard in software development.
  • Docker. Enhance reproducibility of our results by building a container for our project.

During the course, examples will be provided using the R programming language. However, the course contents can be applied using other programming languages and software as well.

Course Schedule

First Day

  1. Projects Organization (4 hours)

    • Open Science Framework
    • Project organization
    • Functional Programming

  2. Git anf Github (4 hours)

    • Introduction to the terminal
    • Local versioning
    • Collaboration and git workflows

Second Day

  1. Project Management (4 hours)

    • Workflow analysis (targets)
    • Dynamic documents (Quarto)
    • Requirements (renv)

  2. Environments (4 hours)

    • Introduction to containers
    • Docker
    • Rocker

Where and When

Giorno Orario Aula (CLA)
Thursday 15 June 9:00 - 13:00 and 14:00 - 18:00 CLA 5
Friday 16 June 9:00 - 13:00 and 14:00 - 18:00 CLA 5

Getting Started

Please install the following software in advance.

Materials

Slides

Exercises

Code

Books

  • “The Open Science Manual: Make Your Scientific Research Accessible and Reproducible” by Claudio Zandonella and Davide Massidda (Link web version and PDF version)

  • “Building reproducible analytical pipelines with R” by Bruno Rodrigues link

Course Survey

  • Course Survey link