Imagine, for a moment, that you’re attending a hotly anticipated presentation. You arrive extra early to claim a seat in the first row, tear the plastic wrap off a brand new notebook, and do your habitual hand calisthenics to prevent your fingers from cramping.
Then the speaker opens up their presentation on the big screen and, much to your dismay, you see that they’ve crammed all of their notes onto a single slide. Oh, the horror!
As the presentation gets underway, you find yourself speed-reading through the bullet points instead of actually listening to the talk. But by the time the presentation is over, you realize that you didn’t actually retain anything the speaker said. Plus, now you have a headache from squinting at the tiny text.
For some of you, this scenario may seem absurd; for others, it may feel uncomfortably familiar. Either way, this kind of upfront information overload isn’t endemic to public speaking; it’s a common pitfall in many disciplines that seek to translate information into understanding.
Avoiding information overload
The field of data visualization is no exception. As the sheer volume of data available to us continues to skyrocket, it’s tempting to create rich interactive visualizations that encourage deep, open-ended exploration. And there’s nothing wrong with that—these kinds of visualizations can be tremendously engaging and illuminating, especially to viewers familiar with the topic or data in question.
But not everyone is a subject matter expert, and not everyone has the skills or patience to decode complex visualizations. And while there’s a time and a place for open-ended interactives, these formats can also alienate non-experts, leaving them frustrated and confused.
If you’re trying to communicate a particular insight to your audience, or to tell a particular story, then it’s incumbent on you, the author, to ensure that your readers are able to follow along. Oftentimes, this requires a bit of handholding. And one of the most effective, and elegant, ways to do this is to break your content down into a sequence of related steps or events, and then guide your readers through them one by one.
Map choreography with sidecar and slideshow
ArcGIS StoryMaps is optimized for linear storytelling. In fact, the sidecar block and the slideshow block, which can be added to any story made with the new builder, serve this very function. Both of these blocks combine large, fixed-position media panels with smaller narrative panels. As the reader scrolls or clicks through the narrative panels, the content or configuration of the accompanying media panels updates.
These blocks are especially effective when used in conjunction with maps, as they allow authors to create logical sequences of related map views; for instance, gradually revealing thematic layers, or panning and zooming to different areas of interest. On the ArcGIS StoryMaps team, we refer to this technique as “map choreography.”
Break it down
There are a number of different ways you can employ map choreography, but they can be reduced to two basic patterns: changing the map’s content by adjusting layer visibility, and changing the map’s geographic focus by adjusting its extent. Let’s begin with layer-based map choreography.
The simplest, and perhaps most flexible, form of map cartography is displaying different layers in each map view. As the reader scrolls or clicks through the sidecar or slideshow block, the layers smoothly animate from one view to the next, enabling easy comparisons.
In the example above, this technique is used to highlight change over time (specifically the development of downtown Indianapolis, Indiana). Each map view contains a different layer; together, they tell a striking story of urban transformation.
Here’s another example, using the slideshow block this time:
Once again, each map view contains a single thematic layer. As reader advances through the slides at their own pace, the maps and corresponding narration update automatically. Readers are free to jump between slides as they see fit, and can interact with the maps directly to dig deeper into the data. But since the primary purpose of this story is to compare overall crop and livestock cultivation patterns—as opposed to, say, highlighting local case studies—the slideshow simply guides readers through the different layers with simple previous/next interactions.
Build it up
You can take this technique a step further with the “progressive reveal”: Instead of bombarding your readers with a tapestry of thematic layers all at once, you first introduce one layer, and then add another, and then add another, gradually building your map up until it’s “complete.” Along the way, you can use the narrative panels to provide written context, or to draw attention to compelling patterns and relationships within and between the layers. Check it out:
In the example above, the first map highlights a general area of interest (the ten watersheds of the Hindu Kush-Himalaya), the second map adds a simple population density layer, and the third map highlights population distribution as proportional symbols. The author could’ve easily presented all of these layers in a single map, but the resulting visualization might overwhelm readers.
Also note that this example uses static maps. As long as the extent of your maps isn’t changing, you can apply this technique to static or interactive maps. The fade transition ensures visual continuity from one map view to the next.
A fresh perspective
You can also use map choreography to present different views of the same data. By providing additional perspectives, you might expose or reinforce insights that would be otherwise overlooked. In the previous example, as well as the one below, the maps visualize population distribution in two different ways: The first map uses a raster surface to visualize density, and the second uses proportional symbols to highlight outliers.
Together, the two maps more effectively communicate the local variation in settlement patterns than either one would do on its own.
A change of scenery
Map choreography isn’t solely useful for transitioning between layers; you can also use it to guide readers through a series of places by changing the map extent in each slide. Because the maps automatically transition as the reader progresses through the block, the spatial relationship between locations is preserved.
The most common application of this technique is transitioning from a small-scale overview map to a large-scale regional map (or vice versa). Again, because the maps smoothly animate from one view to the next, they maintain narrative continuity.
These are just a few uses and examples of map choreography in action. It bears mentioning that none of these techniques are mutually exclusive—they can also be combined to great effect. In fact, some of the examples in this post include both layer- and extent-based map choreography. (See if you can spot ‘em!)
Clarify, don’t simplify
Occasionally, someone will tell me that these techniques “dumb down” the content and, in doing so, insult the intellect of the readers; that this kind of narrative handholding is gratuitous and inefficient. And they’re not entirely wrong—it’s true that three maps with one layer apiece will take up more space on the webpage than than one map showing three layers.
But to paraphrase information design expert Alberto Cairo, the fundamental purpose of data visualization is to clarify, rather than simplify. If your target audience is dissuaded from, or altogether incapable of, engaging with your content directly, then you have failed them, and any concerns about efficiency are irrelevant. And this, I think, is why step-by-step visual storytelling is here to stay.