2025-10-24 16:30:34
Welcome to episode 3 of season 6 of Explore Explain, a long-form video and podcast series all about data visualisation design.
In this latest episode, I am delighted to welcome Liuhuaying Yang, a Data Visualisation Designer who works at the Complexity Science Hub Research Center in Vienna, Austria. We explore the story behind Liuhuaying’s unique data visualisation ‘Not My Name‘, which explores the process and components of translating Chinese names into Pinyin.
You can watch this episode using the embedded player below or over on the dedicated Explore Explain Youtube channel, where you’ll find all the other video-based episodes and curated playlists.
To listen directly, visit this link or use the embedded podcast player below. The audio podcast is published across all common platforms (such as Apple, Spotify, Amazon Music etc.), so you will find this series listed in their respective directories by searching for ‘Explore Explain’ or by manually entering – or copying/pasting – this url to your subscriptions – https://feed.pod.co/exploreexplain.
The post EXPLORE EXPLAIN S6 E3: LIUHUAYING YANG appeared first on Data Viz Excellence, Everywhere.
2025-10-14 20:16:22
My September newsletter, that was sent out to subscribers a couple of weeks ago, is now open for all to read.
You can also access this issue, as well as visit the growing catalogue of previous issues, via the Newsletter page.
If you’re not already a subscriber, its time to change that! To receive this free monthly newsletter straight into your inbox you can sign up here or visit the Newsletter page to get a bit more background information and instructions.
Once again I’m very grateful for the messages and feedback I receive about this newsletter, which always gives me the renewed energy to continue spending time gathering, curating, and publishing these monthly digests.
The post The September 2025 newsletter is now open to all appeared first on Data Viz Excellence, Everywhere.
2025-10-08 15:34:28
Fullfiling a Childhood Dream
Last time, I talked about remote sensing, basically, how we use technology to sense and collect data about our environment. Think of it as your five senses, but upgraded with tech.
My favourite version of this, without a doubt, is LiDAR, which stands for Light Detection and Ranging. Why is it my favourite? Easy: lasers. As a kid, my fascination with lasers started after watching an episode of Drake and Josh (don’t ask which one, just trust it was iconic). And honestly, adult me still thinks lasers are amazing. So let’s talk about what LiDAR can actually do.
Welcome to Data in the Wild
Welcome back to Data in the Wild the series where we highlight real-world examples of data collection and visualization in action. As always, it’s a pleasure to be speaking to a group of people whose views on AI are as polarized as opinions on Marmite. Today, we’re diving into light, lasers, and LiDAR.
A Quick Laser Detour
Before we go too far, let’s talk about the real star of this show: the laser. It turns out “laser” is also an acronym (brace yourself): Light Amplification by Stimulated Emission of Radiation.
The difference between a laser and, say, a light bulb is in how the light behaves. Normal light sources (like bulbs or the sun) emit light in different wavelengths that scatter. Laser light, on the other hand, is carefully manufactured so that all the wavelengths line up in phase and shoot in the same direction.
The result? A beam that’s:
Basically, it’s tailor-made for precision measuring. Also, it looks cool.
So What exactly is L.I.D.A.R
The “L” in LiDAR stands for light, because light is what’s used to measure distance. Here’s how it works:
A laser emits pulses of light towards a target. Those pulses bounce back to a sensor, and the system measures how long that round trip takes. Because light travels at a constant speed (2.99792458 × 10⁸ m/s — thank you GCSE physics), we can use the formula
Distance = Speed × Time
From Lasers to Point Clouds
Here’s where it gets fun. Every time a LiDAR system measures a distance, it records a point in space and not just one. We’re talking millions of these points, each with:
Together, these points form what’s called a point cloud. If a regular 2D map is like drawing on paper, a point cloud is like building a Lego model of the real world. It gives us an incredibly detailed 3D picture of whatever’s being scanned, from forests to city blocks.
Why This Matters
This is why I love LiDAR. With these 3D coordinate datasets, we can explore places in incredible detail without even being there.
And that’s just the start. L.i.D.A.R is used in archaeology, conservation, city planning, autonomous vehicles… the list keeps growing.
But isn’t it Expensive?
Yeah, it is. If you’re starting from scratch, a full LiDAR setup usually involves:
All in, you’re looking at around $20,000+ to get going properly. So yes, there’s a barrier to entry. But for smaller experiments, community projects, or collaborations, it’s becoming more accessible than you might think. That’s a topic for another day.
LiDAR takes something invisible, light, and uses it to map the world in stunning 3D detail. It’s data collection at its most elegant and, honestly, its most fun.
So if you are a fan of these more in-depth breakdowns on data sourcing and how tech can be used to understand the world, see you next time when we uncover more data… in the wild.
Imagine mapping the world using light. That’s exactly what LiDAR does. It fires laser pulses that bounce off objects and return to a sensor, calculating distances with GCSE-level physics. Repeating this millions of times creates point clouds detailed 3D maps. From mapping cities to powering self-driving cars, LiDAR reveals the invisible.
Our five senses are amazing… but limited.
Enter remote sensing: satellites, planes, and sensors that upgrade how we see the world. From zooming in on Google Earth to mapping the ocean floor sometimes the best datasets aren’t online — they’re captured from above, below, and beyond.
Ancient Andean cultures used quipus knotted strings as a powerful form of data encoding. Long before spreadsheets, these tactile tools tracked census data, resources, and stories. Each knot carried meaning. Portable, durable, and deeply structured, quipus are a forgotten ancestor of modern data viz reminding us that information has always needed form.
The post Data in the wild #14: Light, Lasers & LIDAR appeared first on Data Viz Excellence, Everywhere.
2025-10-02 22:37:42
I’m thrilled to see a visualisation I created has been included in a new graphics book by Nigel Holmes, titled ‘Let’s Get Infografit: A Graphic Look at Exercise and Health‘.
Nigel got in touch with me late 2023 to ask “what you do to try to stay in some sort of shape: do you do anything? Running? Weight training? Treadmill? Yoga? At home? In a gym? Golf? Tennis? Swimming? Ski jumping?“.
After brushing away initial concern that he was writing to critically comment on my ‘some sort of shape’-ness, I realised he was instead enquiring to see if I had produced any prior visualisations on such a topic and, if so, would I be willing to contribute them towards the next book he was working on?
I didn’t have any existing work matching that brief, but I did have some data, with a year’s worth – and growing – of recorded details relating to aspects of my fitness and health. This data was just gathering spreadsheet dust, sat there yearning to be analysed.
I therefore agreed, with a huge sense of appreciation for the opportunity, to work on something new using this data that may be submitted for his consideration for inclusion. And, thankfully, it was included, in a chapter showcasing other graphic contributions from fellow information design friends in the field.
The graphic I created takes the form of a personal fitness scorecard, based on self-recorded data covering my daily weight, food portion size across meals, alcohol consumption, and exercise activities with granular details of outdoor runs especially.
This was initially framed over a period of 10 weeks – the 5 weeks leading up to Christmas day and the 5 weeks after – but having worked up an initial version I then re-read the brief and realised I’d misunderstood the graphic dimension requirements and so I had to kill those initial 5 weeks for space reasons. This wasn’t the worst thing to do as I caught Covid and did nothing but eat over Christmas so there was a large void in my fitness activity data!
My goal, as stated in the final graphic, was “Following the excesses of Christmas, in the face of unfavourable winter conditions and a busy work schedule, I aim to drop my weight below target within one month through a combination of healthier diet, smaller portions, and increased frequency of walks and running activities.”
I designed it with an aesthetic style inspired by 1950s baseball scorebooks, with folded-cardboard background and a limited colour palette of blue red and white, and with a typeface and icons similarly inspired by aspects of that mid-century, retro-futurism era that, at the time of producing the graphic, I was exposed to through the TV show ‘Fallout’.
I was happy enough with the outcome of the design (and also the fact that I reached my target weight objective, so nice that would be captured in the data and the graphic!). I just wished I’d fully proofed how the white annotated text would look in the eventual published graphic, which appeared fine on screen and in draft pdf but, ultimately, I feel gets lost contrast wise in the published graphic – that’s my responsibility and my error, not Nigel’s nor the publishers.
Here’s a copy of the final short/squarer version published in the book.
If you’d like to see a gif of the design process and version iterations, click on the below…
The post Visualisation work included in new book by Nigel Holmes appeared first on Data Viz Excellence, Everywhere.
2025-09-16 05:48:52
The State of Our Senses
Humans have five senses: taste, touch, sight, hearing, and smell. They’re our built-in data collectors. They help us make sense of the world: you can see danger before it arrives, hear a warning shout, feel that something’s too hot to touch, or taste a muffin and know instantly it’s worth eating (within reason).
But here’s the catch: our senses only go so far. We might see a sandstorm rolling toward us, but by the time our eyes register it, it’s already too late to do much. Same with hearing thunder you know the storm is close, but you can’t measure how far or how fast. That’s where remote sensing steps in.
Welcome to Data in the Wild
Welcome back to Data in the Wild, the series where we explore everyday examples of data viz in action. It’s always a pleasure to speak to people who would never forgive a pie chart crime but will still make a 3D bar chart “just to see how it looks.” Today, we’re zooming in (and out) on remote sensing.
So what is it? According to NOAA:
Remote sensing is the science of obtaining information about objects or areas from a distance, typically from aircraft or satellites.
Basically, it’s our five senses… but stretched out with tech. Think of it as super-vision, super-hearing, super-smelling, without the radioactive spider bite.
Here are a few flavours of it:
Uncommom Datasets
Now, why does remote sensing matter in a series about data viz? Because it’s not just about how we present data, it’s also about how we find it. If you only ever look at datasets you can download from the web, you’ll limit your perspective. Remote sensing reminds us that data is everywhere in the skies, under the sea, and bouncing off forests and cities. With the right tools, we can capture it and tell stories our senses alone could never reveal.
So yes, scrape the web, chase down Wikipedia tables, and wrestle with APIs. But don’t forget: with a sensor, a camera, or a laser, you can see the world in entirely new ways.
See you next time when we uncover more data… in the wild.
Imagine mapping the world using light. That’s exactly what LiDAR does. It fires laser pulses that bounce off objects and return to a sensor, calculating distances with GCSE-level physics. Repeating this millions of times creates point clouds detailed 3D maps. From mapping cities to powering self-driving cars, LiDAR reveals the invisible.
Our five senses are amazing… but limited.
Enter remote sensing: satellites, planes, and sensors that upgrade how we see the world. From zooming in on Google Earth to mapping the ocean floor sometimes the best datasets aren’t online — they’re captured from above, below, and beyond.
Ancient Andean cultures used quipus knotted strings as a powerful form of data encoding. Long before spreadsheets, these tactile tools tracked census data, resources, and stories. Each knot carried meaning. Portable, durable, and deeply structured, quipus are a forgotten ancestor of modern data viz reminding us that information has always needed form.
The post Data in the Wild #13: Remote sensing appeared first on Data Viz Excellence, Everywhere.
2025-09-11 20:53:16
Welcome to episode 2 of season 6 of Explore Explain, a long-form video and podcast series all about data visualisation design.
In this latest episode, I am delighted to welcome Dr Anna Lombardi, Climate Data Visualiser for Copernicus ECMWF, who is based in the UK. We explore the story behind Anna’s extensive data visualisation and design contributions to ‘The European State of the Climate 2024‘, which offers a detailed overview of climate conditions in Europe and the Arctic region in 2024, based on the close collaboration of 100 scientists and experts across the world.
Here are links to some of the key references or resources mentioned during this episode:
Post-recording, Anna was keen to mention the following:
“I realised I didn’t take the opportunity to thank the rest of the editorial team and communication team here at ECMWF, as well as the external agencies we work with that closely worked with us to put the PDF layout and website in place, and who worked on the social media campaigns, media briefing etc. None of this would have been possible without them.”
She also felt it important to clarify the role of ECMWF:
“Copernicus is the Earth Observation component of the European Union’s space programme. It is organised in six thematic services, managed by entrusted entities on behalf of the European Commission. ECMWF (the European Centre for Medium-Range Weather Forecasts) is managing the climate change service (which coordinates the ESOTC report) and the atmosphere monitoring service.”
You can watch this episode using the embedded player below or over on the dedicated Explore Explain Youtube channel, where you’ll find all the other video-based episodes and curated playlists.
The post EXPLORE EXPLAIN S6 E2: DR ANNA LOMBARDI appeared first on Data Viz Excellence, Everywhere.
