New Year’s only feels like yesterday but we are already well on our way to the midpoint of 2017. With this in mind, it’s time to take stock and think about some of the key changes in the look, feel and style of data visualization since January.
What are the defining aesthetic trends of this year? What are the latest conventions in the industry? What can we expect from 2017: Part 2? Let’s take a look.
There is an elephant in the data-room. That elephant is the vast array of information sources and stores that visualizers now have to play with. This is a subject of some controversy. Of course, no one wants to admit to being out of their depth and everyone wants to show that they are able to stay on top of things. More data is, of course, a positive development, but it has been coming so thick and fast in recent years that the anxiety among data visualizers is palpable.
2017 looks to be the year that DV experts finally get to grips with all that data and start whittling it down into valuable, concise digital offerings. From an aesthetic point of view, this has led to challenges; for example, how can such a raging torrent of information be presented in a neat and tidy manner?
One way in which visualizers are combating this is via multi-lateral visualization, in which layers of data are peeled back like an onion. These are often classed as ‘interactive’ data visualizations. Although, this is a little disingenuous as there is little to no additional input from the user, beyond deciding what they want to look at. However you want to describe it, multi-layered visuals are an important step in the aesthetic presentation of data, and will become increasingly vital as data volumes continue to expand.
Clarity Is Key
Visual artists in 2017 are waking up to the fact that the user must always come first. The whole idea of successful data visualization is to take a complicated arrangement of information and to communicate its central thread, meaning, or message with the utmost precision.
This means a departure from some of the more flashy, ostentatious visuals we have seen in recent years. Data sources are multiplying, seemingly overnight, and audiences are craving insight and understanding into ever more complex systems and configurations of data. This is leading to stripped down, straightforward visuals in which a clear message comes first and superfluous decoration is kept to a bare minimum.
Keeping It Neat with Color
Infographic designers have sometimes shown themselves to be a little free and easy when it comes to color, splashing multiple different hues here there and everywhere in an effort to stand out from the crowd. However, in 2017, it seems that the prevailing trend is towards calmer, more muted color schemes.
At the beginning of this year, Siege Media compiled a list of their 100 greatest infographics. These visualizations covered a wide range of subjects and styles, with topics as diverse as types of cheese and transport history, and average corporate visualization spends getting the DV treatment. There was some experimentation with outlandish color schemes but, generally speaking, the visualizations which had the most impact featured relatively simple color schemes featuring only two or three different hues.
A strong and defined theme like this helps the visualizer tie their work together, making it feel complete and well-rounded. In contrast, a visualization which resembles an explosion in a school arts cupboard is likely to succeed in catching the eye, but then immediately distracting attention away from the intended message.
It appears that this infographic trend has been carried forwards into 2017. Clearstate’s Healthcare Almanac infographic is an example of one of the many great visualizations which have been produced this year, combining sleek and crystal clear design with compelling factual content. This is backed-up with a sharp color scheme; a mixture of oceanic greens and greys with the occasional red dot to provide contrast.
European software firm Scoro weighed in back in April with their impressive series of productivity graphics. Tasteful sepia tones and simple imagery give these info visuals a warm retro feel, which does not detract from the messaging but instead enables it to shine on through. Textbook stuff.
Supporting Access from a Variety of Different Sources
The way in which you engage with a visualization, at least in the aesthetic sense, depends greatly on which device you use to view it. While it is true that smartphone screens are getting larger and more powerful, and that tablet devices are becoming increasingly popular, visualizers still need to get to grips with the challenges posed by different devices.
The answer to this? Testing. A visualizer, working away at a particularly complex problem, finds that her work looks great on a desktop PC. However, when the DV launches, she checks out her work on her smartphone and is disappointed. Much of the impact has been stripped from the imagery. This can be avoided simply by testing her creation across a range of different devices and making the necessary tweaks to optimize the content on each platform.
An interesting example of aesthetic concerns colliding directly with technical ones, we can expect device optimization to be a major influencer on data visualization over the next 12 months and beyond. The last thing a visualizer wants to do is alienate a significant proportion of his audience. Getting the impact and messaging right across all platforms is critical.
Virtual Reality Takes the Lead
One of the defining data visualization talking points of 2016 revolved around virtual reality vs augmented reality, or, more specifically, which one of the two innovations represented the future of DV.
Warning shots were fired, battle plans were drawn up and, as 2016 drew to a close, augmented reality looked to have taken the upper hand. Fans of AR praised its connection to the ‘real’ world around us, which enables visualizations to be transposed directly into the user’s environment. VR, on the other hand, involves a wholly fabricated environment, and is therefore too disconnected from real life to be any use to a data visualizer.
As we approach the halfway point in 2017, the balance seems to have tipped the other way. Virtual reality is garnering serious support thanks to the totally immersive, distraction-free experience it offers to users. Whether VR truly does represent the future of data vis remains to be seen. What is for sure is that it creates a major aesthetic shift. Visualizers suddenly have a world of news axes, dimensions, variables and experiences to add to their work. At the very least, things are going to get interesting.