Amanda Cox, the editor of the Upshot at the The New York Timesonce said that, “The annotation layer is the most important thing we do…otherwise it’s a case of here it is, you go figure it out.”

In my experience, annotating a graph is one of those things that lots of people fail to consider, but it can be a vitally important step to help your reader better understand the context and your argument. It can also be important to simply help your reader understand how to read the graph.

In my view, there are three types of annotation we can include in our data visualizations, moving from simple to more complex: adding labels, creating active titles, and adding detail.

1. Adding Labels

Let’s start with the easiest type of annotation: adding labels. The default in many software tools is to create a data legend and place it below the chart or somewhere to the side, disconnected from the data. This forces your reader to do more work to figure out what each line or bar represents. Instead, a better approach is to directly label your data series. This makes it easier for your reader to connect the data values with its description.

Take a look at this line chart from a paper I wrote on the Disability Insurance program. I included all 50 states plus Washington, DC on the graph and highlighted the seven states of interest. Instead of adding a legend to the top of the graph, I labeled the lines off to the right and color-coded them to match the lines.

This doesn’t have to be complicated or difficult; it just needs to take the reader’s perspective into account. Remember, your audience may not be familiar with the content or the data or simply the presentation of the data, so we want to make it as easy as possible for them to absorb the content. Reducing the amount of time your reader needs to spend understanding what each line or bar represents can help them move to the more important job of understanding the content.

2. Create titles that work as headlines

The next way to annotate your visualizations is to create titles that work as headlines, something I often call “active titles.” Too often, we attach a title to the chart describing the data that are being plotted instead of leading the reader to the point or argument we want to make. Our titles say things like “Figure 1. Support for Targeted and Universal Preschool, 2013.” That could have been the title of the graph from a recent blog post by my Urban colleague Erica Greenberg, but notice how the title of this graph immediately conveys her argument.

A common argument against using more active titles is that the author doesn’t want to seem biased or partisan. I’m not arguing that you use an active title to distort or misrepresent the results, only to put your message in the title. More often than not, when someone argues that they can’t have an active title, I can look in the text next to the graph and see something like, “In Figure 1, you can see that…” Their argument is right next to the graphic, but, like the legend I described above, it’s disconnected from the graph — from the content. Once again, try to integrate your graphs as part of your argument, not as pictures to litter the page.

In Erica’s case, she doesn’t leave it to the reader to figure out what the takeaway point is, nor is she biasing the results by adding commentary in the title; instead, she tells you what you’re supposed to learn from the visual.

3. Adding Detail

Finally, we can provide detail in our graphs to help further convey the argument, highlight specific points, or even explain how to read the graph. In cases where you are visualizing data to help your audience better understand your argument, detailed annotation can help them grasp the context and other key aspects of the graph.

Take this “Marimekko” graph about immigration challenges in different countries from former Urban colleague Audrey Singer. The graph shows the relationship between the number of migrants in different countries along the y-axis and migrants as a share of the world’s population along the x-axis. Labeling the bars for the US and Germany, adding an active title and subtitle, and placing a sentence directly in the graph all help the reader understand both how to read the graph and what content they are supposed to absorb from it.

You have certainly seen good examples of annotated graphs when looking at any major newspaper. Sufficient annotation is crucial to helping readers — especially readers who may have less experience with data, statistics, or data visualizations — grasp and understand the content as quickly as possible.

John Burn-Murdoch, an interactive data journalist at the Financial Times once told me that “the annotation layer is where the journalism really comes into visual journalism. Making a graphic is the equivalent to interviewing your source; but it’s then your job to actually pick out…the bits the reader should know about.”

We’re not all journalists, but we all need to find ways to help our readers know what’s important and what we want them to learn.

 

This post was originally published on the Data@Urban blog on March 17, 2018. Take a look at all the other great stuff we are publishing on Data@Urban and sign-up for the newsletter here.