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My name is Thomas Zwagerman. I'm a Research Software Engineer at the British Antarctic Survey.

I previously worked as an Environmental Data Scientist and as a Spatial Data Analyst at the UK Centre for Ecology and Hydrology, where I developed tools and processes for the automated processing and quality assurance of air quality and climate change datasets, as well as developed interactive dissemination tools and reports for customers and stakeholders. I have also worked as a Data Intelligence Officer at the Suffolk County Council, where I maintained the SCC Planning organisation on Github.

Away from work I'm (slowly) working on my Shiny application fplboard.

I use R for almost everything, with sometimes a bit of Python and more and more of JS/CSS/HTML.

I have the following experience:

• Shiny Development, using the golem framework to develop applications as a package, writing modules for scalable applications and writing unit tests with testthat and shinytest2.

• Writing plumber APIs and leveraging web APIs with httr.

• Automating workflows using RStudio Connect and pins or Github Actions.

• Writing scientific and technical report and publishing websites in rmarkdown, distill and quarto, including creating company brand templates with HTML & CSS (see my scctemplate package).

• Spatial Data manipulation and visualisation with sf, terra, leaflet and other relevant packages.

I am on Twitter and LinkedIn. I also have my own website, which is still under development and you can find the repository on my page.

My first stepts in R were at the Coding Club.

A list of reference books I use frequently in no particular order:

• Mastering Shiny by Hadley Wickham.
• Efficient R programming by Colin Gillespie and Robin Lovelace.
• R Packages by Hadley Wickham and Jenny Bryan
• Engineering Production-Grade Shiny Apps by Colin Fay, Sébastien Rochette, Vincent Guyader and Cervan Girard.
• Geocomputation with R by Robin Lovelace, Jakub Nowosad and Jannes Muenchow.
• R for Data Science by Hadley Wickham and Garrett Grolemund.
• Python for Data Analysis by Wes McKinney.
• Earth and Environmental Data Science (Python) by Ryan Abernathey, Kerry Key, Tim Crone, and Julius Busecke.