Context: The Secret of Impactful Data
Three ways you can make data visualizations more impactful by adding in context while retaining simplicity and minimalism.
By: Holger Kuehnle
April 18, 2017 wasn’t just any other Tax Day. Around this time one year ago, Artefact was knee-deep in numbers working on a unique feat of data visualization: USAFacts — the first comprehensive database of US government statistics illustrating where tax dollars go and why. In the year since USAFacts launched, close to one million people have visited the site, demonstrating a clear desire to better understand government data. Seeing the impact of the platform got me thinking about why USAFacts resonates with so many, when government data already existed in the public domain. The key? Making the data approachable, and placing it into context that ensures accuracy while encouraging exploration and understanding.
When creating data visualizations, it’s our responsibility as designers not just to make beautiful graphics, but to give users the tools to grasp the wider context of the information before them. Yet context can be a challenge, adding in complexity when we seek simplicity in our visualizations. After a year of working on USAFacts, I’ve learned three design approaches to help place data in context and create beautiful, accurate visuals that empower users to understand the complete picture.
- Show data as parts of a whole
Statistics lack meaning in isolation. If you show select numbers divorced from their larger context, at best people walk away with numbers without substance. At worst, you’ve introduced bias or implied causation where there is none. The solution: when showing parts of data, always ensure there is a view of the whole.
One of my favorite visualizations for USAFacts illustrates the impact of the federal budget. It can be difficult to grasp the practical implications of a budget that tosses around numbers in the trillions. To introduce context for the user, we added benchmarks for comparison by juxtaposing the plan against actual historic budget data and independent projections from the Congressional Budget Office. Then, we introduced controls for inflation and per-capita adjustment that allow users to understand the significance of the numbers in comparable terms.
Historic context is vital to painting a holistic data picture. Consider annual US foreign aid spending. On the one hand, $46.7 billion is a lot of money, but on the other hand, the figure is less than 1 percent of total federal expenditure. Moreover, annual foreign aid in aggregate increased for about a decade since 2000 but has been in decline again since 2012. Trends and cycles show the historic significance of a particular data set. Whether or not the numbers necessitate policy reform is for the user to interpret, but it is our role as designers to demonstrate how discrete data is part of a larger whole.
2. Layer in factors of understanding
Designers often pare down data visualizations in the name of beauty, but oversimplifying information can strip away the very context that gives data meaning. One way to retain that valuable context in a digestible manner is to add information in layers. This allows users to navigate through related data that can help them gain a more holistic perspective.
USAFacts’ State of the Union visualization maps out how often a president mentioned certain topics in each State of the Union address, overlaid by related metrics for that year. For example, you can see how often a president used the words “budget” and “spending” in relation to total federal revenue and expenditure in the corresponding year. The issues are broken out into several categories such as education, jobs and healthcare, allowing users to toggle back and forth between topics. The visualization provides an intuitive understanding of which issues were paid lip service and which were prioritized.
3. Create pathways to comprehension
Visualizations that thrill data enthusiasts can overwhelm others. One way to improve clarity is by creating pathways of discovery that let users choose their own adventure. This provides context while making the data digestible to a wide audience.
We designed USAFacts to encourage exploration, with a “simple first, detail upon interaction” process that progressively discloses information. In illustrating the impact of the Tax Cuts and Jobs Act of 2017, for example, we created an automated timeline that runs through projected changes in revenue and spending based on current policy compared to the new reforms. Casual users can start from a bird’s-eye view and let the visualization walk them through the data. Those seeking specific information have the ability to jump into the visualization and explore on their own.
We took a similar approach with the visualization for immigration statistics, starting with the broader question of, “Why do people come to the US?” Purposes for immigrating — such as tourism, work or safety — are color-blocked in one simple treemap chart. Users can then dive into their category of interest. For example, selecting “work” zooms into the types of work visas issued, with further detail on which countries of origin are most represented. In this way, users can quickly understand what broad forces drive immigration, while also having the capability to drill down to such granular figures as the percentage growth of agricultural workers immigrating from South Africa since 2011.
Cumbersome government reports discourage engagement. USAFacts makes the data approachable, dynamic and — dare I say it — even fun.
Lies, damn lies, and statistics
“There are three kinds of lies,” Mark Twain famously observed, “Lies, damned lies, and statistics.” Today more than ever, the sheer volume of data propelling our world makes extracting meaning from statistics difficult at best. Those of us entrusted with framing data have the opportunity to encourage data literacy. Designing context into data visualizations give numbers significance and help differentiate the “damned lies” of data from the valuable insights we all seek.
