West Midlands Cyclotron

A fun, retro-styled, interactive display providing near real time insights into how many cyclists are using roads and cycle routes across this central region of the UK.

The visualisation was featured in How many people actually use the £10 million 'waste of money' cycle lane 'no one uses' by Birmingham Live.

West Midlands Cyclotron Visualisation

Red Means Stop, Better Streets for Birmingham

Working with Better Streets for Birmingham, I helped bring to life the shocking results of their survey by 32 volunteers who recorded 576 drivers jumping red lights, on average every 5 minutes or every 3.3 light changes.

The analysis became the lead story on BBC Midlands Today and was covered by Birmingham Live.

Red Means Stop Visualisation

Wood Burning Campaign, Mums for Lungs

Launched on Clean Air Day 2023, I worked with Mums for Lungs on their Wood Burning Campaign to create a simple but instantly recognisable visualisation of just how polluting burning wood is.

For more information on the campaign, head over to the full post on the Mums for Lungs Website.

Comparison of Wood Burning Methods

Tour de France - 34 Stage Wins

A work in progress and celebration of the current 34 stage win world record. Held jointly by Eddie Merckx and Mark Cavendish, the viz shows not only their achievements, but those of all the heroes in between.

Built in R and then finished in Figma, with data from Wikipedia. Watch this space.

 

#BrumBreathes

Launched on Clean Air Day 2020, with Sustrans West Midlands, an interactive map that enabled residents and others to see, explore and understand the air quality where they live, work and travel.

For more information on the map and wider project, head over to the full post on Sustrans’ Website.

For my technical followers, I analysed the data using R and then created the visualisation with a Leaflet.js map as a base with markers and the circular bar chart built in D3.js. Data supplied by Birmingham City Council’s Environmental Health Department.

Two Decades of Rail Usage

I created this interactive visualisation to show how rail usage in the UK has evolved over nearly two decades for the Campaign for Better Transport using the amazing mapping platform Carto.

The map, covering 18 years of journeys across the UK. A huge hit, featured by the BBC and on the front page of the Scotsman and viewed over 100,000 times. The fact that the map shows 45,000 data points in a way that can be quickly understood is astonishing.

The map allows the viewer to assimilate large amounts of data to instantly grasp the picture nationally, and zoom in on the area in which they live and work.

As a result of this piece of work, Carto asked me to be an ambassador.

Cycle Eye | Five Years of Rides

This was a personal project visualising 284 rides, over 9,000 miles and climbing the equivalent of Everest 13 times!

Created in R (#rstats) with the ggplot using data from Strava via the rStrava package (with thanks to authors Marcus Beck and Daniel Padfield who kindly helped me resolve some technical issues) and then finished off in Adobe Illustrator.

How the UK Votes at the UN

For #TidyTuesday | UN Voting, I created this chart, showing how the UK votes differently to the 10 ‘most powerful’ countries listed by US News’ Power Rankings.

Each circular chart compares the UK’s voting to others, based on the number of votes for a given topic.

The chart was created with R using ggplot. Voting data is taken from Harvard’s Dataverse via the UNVotes R package. Colours taken from the Wes Anderson Darjeeling palette.

Visualusation of how the UK votes at the UN

Modern Slavery in the UK

I was asked to create this visual to highlight the shocking figures about Modern Slavery in the UK by Hope For Justice.

Created in R (#rstats) with the ggplot using data from the UK National Crime Agency and then finished off in Adobe Illustrator.

Visualisation of Modern Slavery in the UK, where to the victims come from?

How Spotify Genres Compare

As a challege for our Information Design Collective....

Created in R (#rstats) with the ggplot using data from SpotifyR

Visualisation of how Spotify genres compare

My British Birds

As an exercise to create a complete data visualisation using ggplot, i.e. without the need to add any finishing touches with a package such as Illustrator. To include specific fonts, cropped images and a repeating pattern where each item has similar constituent parts.

To make it a bit more interesting, I wanted to use R to extract colours from the included images.

Patterns

My foray into Art in R.