This is a guest blog post by Rebeca Pop, founder of Vizlogue, a Data Visualization and Storytelling Lab that offers workshops and consulting services. You can find Rebeca on YouTube, where she posts data visualization videos. Rebeca has been providing insights and creating data visualizations for almost 10 years. She has worked as a digital analytics leader for top media and analytics companies, and is teaching Data Visualization and Storytelling at the University of Chicago and at Northwestern University. Read more about Rebeca in her bio below.
Shortly after Russia invaded Ukraine at the end of February, media publications started sharing maps of Ukraine and its neighboring countries, as well as of the millions of refugees who were fleeing the war. As the war continued to develop, the story that media publications had to tell became increasingly more complex. A regular choropleth map and a point map were not sufficient anymore as they couldn’t accurately depict the situation in Ukraine. As a result, we started seeing a lot of innovative thinking and new types of maps.
In this blog post, I’ll select and discuss a few unique maps that I’ve seen in the media since the end of February when Russia invaded Ukraine. But, before I do so, let’s first take a step back to review how maps came to be.
A Short History of Maps
Maps (or cartography) are one of the oldest types of data visualizations, which contributes to the fact that we tend to find them intuitive to read and understand. The history of maps can be traced back over 5,000 years ago. Early forms of maps were typically depicting small areas and were pictorial in nature. The Babylonian clay tablet map below depicts Babylon with the Euphrates River, mountains, and the ocean and is an excellent example of early maps.
Fast forward to the Middle Ages, maps progressed in the Islamic world faster than in Europe. One of the most known maps from the Middle Ages was created in 1154 by Al-Sharif al-Idrisi. This map depicts the world as a sphere, incorporates colors, and is overall more complex than the Babylonian maps.
With the invention of the printing press in 1440 in Europe, maps evolved at a fast pace and started being more similar to what they look like today. Equally important, maps became accessible to a large portion of the population as publishing houses produced maps that were not just for the wealthy elite. The map below was published in 1662 by Joan Blaeu. It was included in the book Atlas Maior, containing 594 maps and around 3,000 pages of text. This world map shows two hemispheres, one overseen by Ptolemy and one by Copernicus, each with a very different view of the world and the solar system.
Modern maps are more diverse and easier to create than ever before with tools such as everviz. Choropleth maps are particularly popular and versatile. They display geographical areas that are colored, typically based on ranges of a numeric value. Choropleth maps allow us to compare geographical areas and understand patterns. Below is an example of a choropleth map created in everviz that encodes data from Natural Earth.
Probably the second most common type of map nowadays is the bubble map. A bubble map uses circles to encode numeric values by geographical areas. In addition to the size of the circles, this map type can incorporate a second level of data encoding – color. The map below is an example of what an everviz bubble map can look like.
Finally, another widely used map type is the point map. Point maps are helpful when our goal is to show the position of a geographical location on a map. In the example below created in everviz, a cities in Europe are marked on the map using a dot.
While choropleth, bubble, and point maps have been used to tell the story of the war in Ukraine, many data journalists quickly concluded that these common map types were not sufficient as they couldn’t capture the entire story. Thus, data journalists and media publications had to think outside the box and evaluate the best way to communicate a multitude of new events that were taking place, such as the movement of refugees, the control of territories, and the closed airspace. In the next section, I will discuss key map types that I’ve seen used in the media to visualize the war in Ukraine.
Similar Stories, Different Maps
While I’ve probably seen dozens of maps depicting the war in Ukraine, not all these maps are unique. They have many similarities. For example, territories that are under Russian control are typically colored in red. Arrows depict the direction of the Russian troops advancing or the countries where Ukrainian refugees are going. Bubbles are used in some cases as an alternative to arrows to indicate the number of refugees in every country bordering Ukraine. Finally, symbols such as bombs or soldiers can indicate the difference in resources between Ukraine and Russia.
I often say that color is one of the most powerful tools in data visualization. Color has meaning. For example, if I use green, you might think of freshness, positiveness, or youth. Reversely, if I use red in data visualization, you will likely associate the color with negativity, or pain. Also, using color sparsely can help grab your audience’s attention and ensures that your message is coming across. Therefore, it was no surprise to notice that most maps depict territories under Russian control in red, indicating violence and danger.
In the map below from BBC, we notice in red the areas that are under Russian control. In addition, Crimea is highlighted in red with a black contour line, meaning that it was annexed in 2014. There are also a few points on the map indicating where major Ukrainian cities are located. A small map in the corner shows where Ukraine is located. This additional context is needed, given that BBC’s audience might not be familiar enough with key Ukrainian cities and potentially with the country’s location on the world map.
Another example of a map that uses red to indicate Russian military presence comes from The Financial Times. While the map below has a lot in common with the one from BBC, you might notice that there is a second color being used – yellow. Instead of only highlighting the Russian presence, this map also indicates the geographical areas where Ukraine claimed a counter-offensive. There are also two shades of red – a darker one for the regions where Russia claimed control and a lighter red for areas where the Russian troops were advancing. Similar to the BBC map, Crimea is in a red pattern, showing that Crimea was annexed in 2014.
Arrows are an intuitive and common symbol to indicate movement. In visualizing the war in Ukraine, arrows have been used to depict advancing Russian troops, or fleeing civilians. Arrows can encode a few different data dimensions: distance, direction, and size.
Many media outlets used arrows on maps, but one particular example that stood out came from Bloomberg. In the map below, black arrows indicate the direction of Ukrainian refugees (from Ukraine to other neighboring countries). The width of the arrows represents the number of refugees, with Poland having the largest number (1 million). The length of the arrows is based on the distance between Ukraine and each country. To help us decode the information easier, the number of refugees is also specified next to each arrow. Note that the arrow labeled “other EU countries” doesn’t capture the location of these countries, but its width still indicates the number of refugees.
Another example of an arrow map was published by Al Jazeera. While this map is similar to the one from Bloomberg, there are two key differences. First, the arrows encode the direction of the refugees but not the number of refugees, as the width is consistent across all arrows. Instead, the number of refugees is indicated as a number, next to each country’s name and flag. The second relevant difference is that there is no additional arrow representing the number of refugees fleeing to the European countries that don’t border Ukraine.
While arrows are intuitive and can encode a few different data layers (length, width, direction), an issue has been raised repetitively in the data visualization community – arrows imply a deliberate movement and don’t humanize the data. They take away the essence of the issue, which is that civilians were forced to leave their country behind. In an attempt to solve this problem, Kenneth Field, a cartographer, and geographer, chose to replace the arrows with a potentially more empathic option – dots to indicate the spread and dispersal of the Ukrainian refugees through permeable borders. While the attempt was popular on Twitter, reviews were mixed. Some felt that Field’s map was humanizing the data in a way arrows couldn’t, while others thought that the map was giving the impression that Ukraine was “dissolving although the physical area is not shrinking but dissolving in another sense.”
Another attempt to humanize the refugee data and avoid using arrows came from El País. Instead of arrows, dots were used to indicate the number of civilians fleeing Ukraine. The dots also followed the direction from Ukraine to each neighboring country. Unlike arrows, these dots succeed in humanizing the data a bit more.
Bubbles are another alternative to using arrows. While bubbles can’t indicate direction, they can encode size. In the map below from NBC News, bubbles were placed on every bordering country to indicate the location, as well as the number of refugees who fled Ukraine. Ukraine is positioned in the center of the map, in black. The surrounding countries are in grey. Also, the name of each country and the specific number of refugees is mentioned under each bubble.
Another example of a bubble map comes from Bloomberg, in this case depicting the location of military forces. Except for Estonia, Latvia, and Lithuania, each bubble is positioned in the country that it represents. As expected, Ukraine and Russia have the largest number of military personnel. NATO troops are in blue, and most of them are located in Germany, a country that has had many US military bases.
Symbols haven’t been used as often as arrows or bubbles to depict the war in Ukraine. However, one example of a map that incorporates symbols was published by Al Jazeera and came originally from Flightradar24, a global flight tracking service that provides you with real-time information about thousands of aircraft around the world. When Ukraine closed its airspace to civilian flights and canceled flights on February 24th, it was impactful to see a simple map of Europe with the territory above Ukraine, as well as parts of Russia and Belarus having absolutely no air traffic.
After seeing the map above with data from February 26th, I was curious to check how the air traffic patterns have changed. So, I went to Flightradar24 and took a look at a live map. The answer: not much. There is still no air traffic above Ukraine and Belarus. The Russian territory surrounding Ukraine and Belarus is also missing any air traffic.
As you might have noticed, we’ve come a long way from the early versions of maps from the Babylonian Empire or the Middle Ages. Nevertheless, these early maps were foundational and had a profound impact on the evolution of cartography to what we know today. Most maps depicting the war in Ukraine that I discussed above also go well beyond a typical choropleth, bubble, or point map. As the war in Ukraine unfortunately continues, data journalists struggle to communicate the complexities of the conflict and to find the right level of compromise between what we can convey using maps and attempts to humanize the data.
Maps, as well as data visualization overall, are a compromise. I encourage you to always think outside the box and explore various choices. Always think critically about the data and the visualization that you are choosing and, if there is a need, even invent a new map type that better tells the story that you are trying to tell.
About the author
Years ago, Rebeca fell in love with data visualization and storytelling. And there was no way back.
That was the point when she realized how underrepresented these skills are, despite being core to most business professionals.
Rebeca, Vizlogue’s founder, has been providing insights and creating data visualizations for almost 10 years. She has worked as a digital analytics leader for top media and analytics companies, across a diverse set of industries, such as Fast Food Restaurants, Consumer Packaged Goods (CPG) and Automotive.
For nearly 3 years, she has been teaching Data Visualization and Storytelling at the University of Chicago and at DePaul University in Chicago.
Rebeca holds a MA from the University of Oklahoma and a BA from the University of Bucharest, Romania. When she’s not reading, practicing or talking about data visualization and storytelling, Rebeca enjoys hiking and cycling.