Data visualisation: a form of art?
The most useful handmade visualisations date back to the 1600s when people were confronted with a passel of possibilities to make information more meaningful. One can think back to the cartographer, William Smith, who drew the first sketch of Britain in 1815, Francis Galton’s weather map and even Florence Nightingale’s circular area charts that explain the health conditions of British soldiers in 1875.
I know what you are thinking. Another one of those boring posts where you have to sink your teeth into statistics, right? Luckily for you, not. In this post the focus is on data visualisation as a form of art.
It becomes difficult to define what constitutes art. However, some people may refer to it as something that is both functional and aesthetically pleasing (or damn right ugly). Art is not static and becomes subjective when we try to make sense of it.
When we think of art, a few characteristics might spring to mind. These will probably include aestheticism, visual appeal, tone, texture, colour, line, form, content and emotion. You get the picture.
Although data visualisation is driven by numbers, lists, statistics and logic, it creates a certain emotion and is usually beautiful. Due to its pragmatic nature, these visualisations convey information that is both communicative and, at the same time, easily consumable. After closer examination of the aforementioned, it becomes clear that data visualisation cloaks itself as a particular form of art.
According to Lev Manovich, professor of Computer Science at City University of New York, “the desire to take what normally falls outside of the scale of human senses and to make visible and manageable aligns data visualization art with modern science. Its subject matter, i.e. data, puts it within the paradigm of modern art”. Thus, data visualisation is not a new form of art, but it is only in this contemporary era that it is recognised as such.
How art comes about
The artist has to think of a concept that drives the artwork. One that makes sense and draws inspiration from different areas. In the case of data visualisation, inspiration stems from available statistics. This stage further involves the identification of variables that might be connected to one another and visible data points that will make the particular story more comprehensible.
Not only does art have a concept, but also an artist who hides behind it. Is this not the same with data visualisation? You (the artist) create a visualisation (the artwork) based on a particular data set (the concept). Congratulations, you now qualify as an artist who is able to create successful works of art. Seems simple enough, right? That is because it really is.
Secondly, the process of creation occurs. At this stage, it becomes necessary to employ the inspiration and start to create a visualisation that can be consumed by others. Since the visual elements are the backbone of visualisations, a suitable visualisation that will convey the message best, must be identified during the creation process. The same characteristics that belong to art make the visualisation stronger and visually appealing.
Lastly, consumption takes place both in a private and public space. When art is consumed privately, e.g. on one’s personal computer, emotions experienced by the viewer cannot normally be captured by others. There exists more room for the viewer to examine the artwork and take all its nuts and bolts into account before publication occurs on an online platform. When art is consumed publicly, a particular reasoning is found behind it. It must convey a message to a wider audience quickly and efficiently.
Data visualisation artists make their appearance almost every day as data is made more visible and accessible to the public.
Although we have established that data visualisation is a form of art, artists use data to create, what seems to be, modern artworks. Martin Wattenberg focuses on science, data, art and media in his artworks. His artwork entitled, Wind Map (2012), shows the illustration of wind currents over the United States.
Wattenberg mentions that “it conveys the movement of the air in the most basic way: with visual motion. As an artwork that reflects the real-world, its emotional meaning changes from day to day. On calm days it can be a soothing meditation on the environment; during hurricanes it can become ominous and frightening”. People further use the map for travelling purposes and even for the examination of migration patterns.
Similarly, computer artisan Mario Klingemann, employs the characteristics of art to create a visually appealing data visualisation that represents the hidden patterns of the illustration of data. It is notable that Klingemann carefully assembles the data to communicate the structures and connections associated with it. If the visualisation, after closer examination, does not have the word “art” written all over it, it is time to put on your thinking cap and analyse it once more.
The image illustrates the hidden patterns employed by data. Image supplied by Mario Klingemann on Flickr.
Art does not merely need to be a pretty picture when one takes data visualisation into account. All the elements that belong to the visualisation are important when the processes of conception, creation and consumption take place.
Do not miss out on the opportunity to take a ride on the visual vehicle as we examine the power of data visualisation in the next post.