General Overview
We have all experienced seeing others presenting their research as either a slideshow presentation, blog post, book or journal article. Looking at the figures and tables without being able to run computational experiments to probe the results presented, effectively limits the scope for understanding the magnitude of the available knowledge within scientific studies. Allowing others to replicate, test, reuse, extend and build on published research results can accelerate the rate at which scientific development drives cultural and technical innovation. Adopting and applying open and transparent approaches to research is integral to genuinely rigorous analysis and adds to the material value of one’s research. In view of this, the presentation of the available code, data and algorithms should be available to scrutiny and possible connectivity to wider research projects.
In this workshop we will introduce you to open source software R and GitHub that could serve as a tool for reproducible research. R has become essential in the research itself and in communicating its results to the community at large. It is free public domain software that is available to anyone with a desire to discover, learn, explore, experience, expand and share the algorithms of their research science journey. We will show you how to use RStudio IDE for R from its installation to RStudio customisation and files navigation. RStudio supports working with Git, an open source distributed version control system, which is easy to use when combined with GitHub, a web-based Git repository hosting service. We will introduce you to GitHub and show you how to become acquainted with good practice when incorporating the use of Git into an R project workflow.
Once we demonstrate how to set up the RStudio working environment you will be shown how to turn your research analyses into high quality documents and presentations with R Markdown. We will be designing reproducible reports by automating the reporting process, showing you how to take a modern approach to telling your data story. With the knowledge from this workshop you will be able to start to create reports straight from your R code, allowing you to document your analysis and its results as an HTML, pdf, slideshow or Microsoft Word document.
By presenting some simple, but informative examples we will illustrate how reproducible research can become common practice for researchers when using a simple and freely available tool.
Objectives:
- Understand the motivation for documenting, sharing, automating, organising and disseminating the files in making search reproducible
- Introduce the open source tools R/RStudio/RMarkdown/GitHub that can address these problems
How the workshop works
The material is structured within 2 modules. Each module is delivered in a hands-on interactive student/teacher session lasting one hour and forty minutes, with two ten minutes breaks and the last twenty minutes reserved for questions and discussions.
Each module will be taught by Dr Tatjana Kecojevic and will cover various related topics through appropriate case studies, presentations and readings. The conceptual models come to life when practice becomes reality during the hands-on taught sessions, through the application of R. Students are then expected to use their own time to practice and hone acquired expertise during the taught sessions.
Students are expected to participate fully in all of these delivery modes.
Who can enrol
This workshop will benefit anyone who wants to discover effective and attractive ways to communicate their research outcomes.
Prior experience is not required.
You might wish to have your laptop with the latest version of R and RStudio installed. If you do not know how to install them see this set of instructions that will help you to install R and RStudio on your system.
We hope you will join us!
Material is released under a Creative Commons Attribution-ShareAlike 4.0 International License.
