We deal with data all year round. Much of our work stems from data. From insights to education, PR to promotion. In healthcare, for all the cut-through, cleverness and creative, without robust data to support it, our work can be rendered irrelevant. This holiday season, we’ve turned our data skills to a bit of festive fun. We asked Langlanders to rate their preferences across holiday movies, music and food and produced our Happy HoliData visualisations. Should festive films be dripping in tinsel? Do we love a seasonal sing-along or is it a fa la la la la la la la nah? Find out on our social channels soon.

Of course, visualising data isn’t just for the holidays; but why is it so important? Well, we know that around 70% of all the sensory receptors in the body are in the eyes, and the brain can identify images in just 13 milliseconds.¹ Compare this with the fact that even expert readers will only read at one word every 151 milliseconds, and we see that humans are very visual creatures.²

What is data visualisation?

Data visualisation translates raw data into visual, easy-to-read formats, allowing us to interpret the information faster than by analysing text or numerical data alone. Over the last decade infographics have become an increasingly popular way of sharing data. They can be a spectacular way of displaying a huge amount of information in a very accessible way. In healthcare however, our industry can be guilty of simply adding a few icons to a lot of text and calling it an infographic. David McCandless’s Information is Beautiful and the “slow journalism” publication Delayed Gratification are particularly wonderful resources to show the true potential of infographic design.

But data visualisation isn’t just infographics. The need to visualise various forms of data is more ubiquitous than you may think. From fitness trackers to finance, weather forecasts to sports broadcasts – all use their own way of visually communicating information.

From papyrus to pixels

Historically, navigation has been a driver for the development of data visualisation. Take this simple journey in Fig 1; which of these geographical data would you prefer to follow?

The first recorded piece of visualised data is an ancient Egyptian gold mining map, the Turin Papyrus Map from roughly 1160 B.C.³ But it was another 2800 years until the first visualisation of statistical data. In 1644, Michael Florent van Langren created a simple chart assessing the longitude between Toledo and Rome. Other (in some cases beautiful) graphs and charts, have been scattered throughout history – with honourable mentions of course to Leonardo Da Vinci and Galileo Galilei – but none used actual, statistical data.⁴

Connecting the dots

The design of data visualisations is more than making data aesthetically pleasing. It’s about making it useable, efficiently. According to renowned designer Richard Seymour “design means ‘making things better for people.’” True, whether it’s making a product easier to use, making an intuitive user interface, or making data accessible. A great visualisation will group data into shapes and patterns, not only to grab attention, but also reduce the amount of brainpower needed to understand the data and increase memorability.

Because our brains are set up to recognise patterns. When someone walks into a room you recognise them as the person they are from the overall pattern of their features. Not by assessing features separately like a subconscious Mr Potatohead. When looking at text, our brain will recognise the pattern of whether a sentence is fully formed before it understands the meaning of any of the words.⁵

The Gestalt principles are a leading set of cognitive theories proposed in 1912 to explain how the mind instinctively organises visual information into patterns, and how it interprets patterns it views.⁶ There are seven to twelve main principles, and discussing them could fill a number of articles. Suffice to say, these principles are particularly helpful for guiding complex design such as data visualisation. For example:

‘Proximity’ – our minds understand that objects grouped close to one another are more likely to be similar than those far apart;

or ‘Continuity’ – we assume that a line is a continuum rather than a single object.⁷

Gestaltism suggests that, the whole, beyond being ‘greater than the sum of its parts’, is in fact ‘different to the sum of its parts’. Which is why data visualisations can be more than just an overview of data, but instead a visual narrative that can truly connect and make an impact on the reader.

And as the world of communications evolves, people expect more from their digital experiences. The Gestalt principles still stand, but there are considerations beyond what could be assessed in 1912. Motion, interactivity, and responsiveness are a start, and as newer interfaces are developed – AR, VR, MR, immersive worlds – ever more will need to be taken into account. And of course there’s more, increasingly complicated, data to visualise.

Data to diagnosis

Around four hundred billion gigabytes of data is produced worldwide every day.⁸ Around 30% of that is healthcare.⁹ And to make sense of that data it’s often visualised. From ECGs to radiographical imaging, new ways of visualising data are fuelling advances in diagnostics and patient care. A recent Red Dot design award winner used AI to take data from CT scans and display it as a stereoscopic hologram, allowing oncologists to assess surgical strategies for patients with pancreatic cancer.¹⁰

As healthcare communicators, the need to convey data in a compelling way is well engrained as a high priority. And rightly so. “We are charged with communicating complicated information that can really be life-changing,” says Steffi Evans, Principal Medical Copywriter at Langland, “making information more accessible can improve health equity by better informing and empowering patients to have important conversations.”

Few other professions have the need to recall so much data in often high-pressured situations than HCPs. Yet they are also very time-poor. “Being able to succinctly and memorably communicate key data and insights is vital,” adds Diane Ross, Langland’s Executive Scientific Strategy Director, “so HCPs can quickly gain and digest new evidence that impacts the patients they see every day.”

Data visualisation is far more than an aesthetic tool – it's a vital component of communication, especially in healthcare. By making complex information more accessible, it empowers individuals to make informed, data-driven decisions. In healthcare, where clarity and simplicity can be a matter of life and death, effective data visualisation is not only important but essential.

If you’d like to discuss perspectives on data in health communication, get in touch.

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References

1. Potter M.C. et al. Atten Percept Psychophys. 2014; 76(2): 270–279.

2. Rubin G.S. & Turano K. Vision Res. 1992; 32(5): 895–902.

3. National Geographic. World's First Geologic Map Was Far Ahead of Its Time. July 2016. Available at: https://www.nationalgeographic.com/history/article/gold-mining-egypt-turin-papyrus-map-archaeology. Accessed December 2024.

4. Friendly M. et al. Amer Statist. 2010; 64(2): 174–184.

5. Fallon J. & Pylkkänen L. Sci Adv. 2024; 10(43): eadr9951.

6. Wagemans J. et al. Psychol Bull. 2012; 138(6): 1172–1217.

7. Interaction Design Foundation. What are the Gestalt Principles? August 2016. Available at: https://www.interaction-design.org/literature/topics/gestalt-principles. Accessed December 2024.

8. Statistica. Volume of data/information created, captured, copied, and consumed worldwide from 2010 to 2023, with forecasts from 2024 to 2028. November 2024. Available at: https://www.statista.com/statistics/871513/worldwide-data-created/. Accessed December 2024.

9. Thomason J. Global Health Journal. 2024; 8(1): 1–3.

10. Red Dot. Advancing cancer care with human-centered Artificial Intelligence. Available at: https://www.red-dot.org/project/advancing-cancer-care-with-human-centered-artificial-intelligence-60211. Accessed December 2024.