Hello - I'm Jack!
👨🏼💻 Who am I?
I am an air quality data analyst for a consultancy company in the United Kingdom, developing and maintaining R scripts, packages and apps to support work in the practice. I recently submitted my thesis for my PhD in atmospheric chemistry at the Wolfson Atmospheric Chemistry Laboratories at the University of York, investigating how emissions from road transport impact the air we breathe. As part of my work I delve into very large data sets, which I accomplish primarily using R in the RStudio IDE, with a focus on the {tidyverse} suite of R packages and the dedicated air quality analysis package {openair}. When exploring data, I commonly employ RMarkdown and, more recently, Quarto for reproducible data analysis.
As well as developing my own R code to solve the data challenges I face, I have supported and taught colleagues R and developed my own self-teaching R materials to assist new users through reading, manipulating and visualising data inside of an R environment. I have used these materials to teach introduction sessions to both PhD students and air quality professionals. More recently, I have become an Rstudio Certified Tidyverse Instructor.
📢 My Publications
The publications I have been involved in so far can be viewed on my ORCID iD page. All focus on the use of the Vehicle Emissions Remote Sensing technique to measure emissions from road transport, and the unique insights they can provide that in-lab or on-board techniques cannot. They were written in LaTeX, a plain-text document preparation system, using the online editor Overleaf.
The data analysis for my publications is almost entirely conducted and visualised within R, though I commonly use the open-source vector graphics editor Inkscape to refine figures and produce graphical abstracts. I have no formal graphic design training and self-taught myself the software with help from the Logos by Nick YouTube channel.
📊 Data Visualisation
In my spare time, I enjoy developing my R and data visualisation skills through the #TidyTuesday Project, a weekly data science challenge to both wrangle and visualise an unseen, "real-world" data set. You can view all of my visualisations and the code used to create them in their dedicated repository. Let me know what you think over Twitter - I'm @JDavison_!
