Data Visualization in Europe: A Short Introduction

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Data Visualization (DV) has been around a really, really long time — I’d argue ever since the very first hominids communicated with one another. These crude shapes have greatly evolved over the years to arrive where it is today.

This article starts with a speed boat tour of ~2000 years of visual communication in Europe to establish a backbone for future explorations. It concludes with a problem I see stopping us from fully realizing the potential of the current phase, and what I consider an emerging solution to it.

The Qualitative Age

Early visualizations feature common graphic elements that can best be described as conveying qualitative data. Some of the very earliest carved objects and cave paintings in Lascaux focused on communicating qualitative, rather than quantitative, data. Generally speaking, these works focused on basic information transmission: what (human, animal, etc.), how many (1, 2, several), and some descriptors (big, small). In addition to conveying information, some of these works reach surprisingly high levels of detail and quality (symmetry, reproducibility) and are similar to what can be found in pre-agricultural societies around the globe.

Cave painting of a Dune Horse in Lascaux. Source: wikipedia

The Age of Symbols

With the rise of agriculture and the spread of mathematical knowledge (e.g., trigonometry), visual literacy begins to increase. Maps of land and sea make their first appearance. The beautiful example below shows an outline of the southern part of Italy and sea and land to the east and west. What is interesting is that North is not at the top of the map, which is a feature quite common in early maps. As the use of maps increases, it becomes common for individuals to start or settle land disputes using them and the transmission of navigational charts makes trade cheaper and easier.

Section of Tabula Peutingeriana — top to bottom: Dalmatian coast, Adriatic Sea, southern Italy. link

Artifacts, such as the Phaistos Disc show that the encoding of abstract concepts is not limited to maps. Basic shapes become increasingly representational and Mycenaean and Minoan Frescoes have clear elements of visual storytelling in them. The communication of simple events and more advanced ideas becomes possible. Another good example of this is the Boar Hunt fresco from Tiryns that shows hunters, hounds, the boar, and chariots. The entire hunt from the beginning to the end is portrayed.

The Phaistos Disc

During the Middle/Dark Ages refinement of artistry and standardization of symbolic encoding continues to evolve. In illustrations of the Christian religion, it is pretty clear who the focus is (hint look for halos) and who is there to fill the canvas. Bigger narratives in visual form become possible because the audience is able to identify and decode story elements the author/artist wants to communicate. You can find examples in many Catholic churches where the life or suffering of Jesus is depicted on the church walls or windows. It’s easier spotting recurrent actors if the way they are depicted is consistent across panels, and an appreciation of local variation increases because they stand out even more.

The printing press had a huge impact on the dissemination of visual communication that cannot be ignored. Groups of people didn’t have to be trained to copy illustrations or maps by hand anymore. (They were probably still needed to help transfer them onto stencils, but let’s leave that for another article.) The first mechanical copying, of course, didn’t live up to the results a trained copier could provide, but the seed eventually grew into high-quality mass reproduction.

The Quantitative Age

The beginning of the quantitative age originated during the Renaissance. Early examples include Tycho Brahe’s star constellation maps and Galileo’s Jupiter moon tracking charts. These were remarkably accurate and aesthetically pleasing.

The 1572 supernova in the constellation Cassiopeia, from Tycho Brahe’s De Nova Stella.

Most of these surviving visualizations are fragments of disseminated research that was highly controversial at the time, typically because they questioned the narrative which was at the foundation of civil society. It’s an irony of history that some of the best-preserved copies were kept by the fiercest critiques, thus ensuring that they wouldn’t disappear in the sands of time.

As time progresses, both the scientific approach to describe and discover the world and its representation of data becomes more established as it evolves. Patterns began to develop and they started to look familiar.

John Snow’s work on the Cholera outbreak is using a map of London which is highly detailed, and he drew bar plots on it! No need to introduce Florence Nightingale’s timeless illustrations of the causes of death in the British Army. Now consider that both of these works were done in the 1850s.

LEFT — John Snow showing clusters of cholera cases in the London epidemic of 1854. RIGHT — Example of polar area diagram by Florence Nightingale

By 1869, Minard published his Map of Napoleon’s invasion of Russia.

By 1885 Marey published his time-series plot showing transit between Lyon and Paris over 24 hours. This plot is significant because it is one of the early examples of a time series plot, which in some areas of academia became the bread and butter for sharing insights.

While most of these visualizations were clearly made for highly trained audiences, some practitioners took up the challenge of finding visualizations that would speak to people regardless of their educational background. Otto Neurath (Picture Statistics) and Rudolf Modley (Isotypes) were leading figures in this.

The Connected Age

Compared to a couple of years ago, there are now online Data Visualisation galleries with more masterpieces than anyone could have wished for. Tutorials and forums are full of accessible information on how to start and improve your technical and design skills. It is also easier than ever to follow European Data Visualisation trailblazers, just follow them on social media and they will feed your stream with delight and the reality of how the work gets done.

But we shouldn’t pat ourselves on the back quite yet or wait for the next phase to kick off.

While it has become easier to share examples of our work, and in many cases the process used to build it, we haven’t fully leveraged the new tools at our disposal. Certain larger cities may have a local community where workshops are hosted quite frequently (yes Greater London, and Amsterdam I’m talking about you). But for most locations in Europe, local meet-ups are still not common or frequent. If you wanted to change this you would find that you have a hard time finding people in your local community that are engaged in DataViz because most of the information about DataViz focus on the method and approach, but not on the community or it’s history.

I think this is about to change. When the Data Visualization Society was launched, it took off quickly. I don’t think many people knew what it had to offer; I certainly didn’t when I signed up. But it sounded like something that I had a hard time locating, coming into the field via a non-traditional route. What I found blew me away. Dozens of Slack channels with people engaging with each other, asking for help, discussing the latest trends, or just hanging out. While the number of people in the channel focused on Europe is relatively small (around 200 at the time I am writing this), I am convinced that great things will emerge from it (some of them I’m contributing to in my own small ways). I am pleased to be part of this group and I’m ready to support the growth of the European data visualization community by any means that I can. I am prepared to support the community and make this region the best place to enter or excel in data visualization. Are you ready to join me or accept my help?

PS. DVS New York it’s on!

This post is what it is thanks to the contributions and support of Georges Hattab, Alyssa Bell, and Jason Forrest. Thanks!