This Is How Data Inspires Creativity

Melting Memories by Media artist Refik Anadol

In my last article, This Is How Data Kills Creativity, I examined a case where a marketing influencer named Josh Fechter cooked up a bogus formula for predicting content virality on the LinkedIn newsfeed (interestingly, both his original post and LinkedIn profile have since disappeared). The math used in Fechter’s viral content prediction model was hugely flawed, but I think what irked me the most about his article was his intended ‘use’ of data. His goal was to offer marketers on LinkedIn an early warning signal for detecting whether their content was going viral, which could, in turn, be used to optimize content for clicks using clickbaity tactics.

Don’t get me wrong, I’m all for using data to learn how to improve your creative execution. But Fechter’s message was all about quantity over quality. He is, after all, credited with popularizing the use of broetry, a low rate form of clickbait that, for a short while, was rewarding some users on LinkedIn with millions of impressions for what was essentially garbage content. That was until LinkedIn caught on and (thankfully) tweaked their newsfeed algorithm, essentially killing broetry for good.

But that’s not really what I want to talk about today.

It’s been just over 2 years since that post and I feel like it’s only right that my first article in 802 days (yikes!) be a follow-up to the data creativity piece. But this time, rather than look at how data can be used to kill creativity, I want to shed some light on how data can inspire it.

Data is, after all, just data. Without some form of intervention, be it human or machine, it’s worthless. For data to have value it needs both a purpose (i.e. how do I want to use it) as well as an interpretation (i.e. what did the data tell me).

A sound interpretation of the right data at the right time can be incredibly powerful. It can inspire a killer campaign idea, inform a winning business strategy, or even be used to create a work of art.

So today I wanted to switch things up and share a few examples of how data, when applied with purpose, can inspire creative thinking.

Here we go!

Data Inspired Art

Data is often an inspiration for many things, but I find we tend to limit our thinking to business applications, such as using data to find a competitive advantage or to optimize a campaign. And although these are all swell use cases for data-driven thinking, there’s so much more to be learned from examples of data being used to create art.

Here are a few of my favourite examples.

The first is an installation called Melting Memories from media artist Refik Anadol. This piece was previously on display at the Pilevneli Gallery in Istanbul and featured a 16 x 20 foot LED panel that projected visual representations of brain wave activity collected through an EEG. Anadol engineered Melting Memories to visualize how the human mind recalls memory.

Media artist Refik Anadol’s work Melting Memories

On the inspiration behind the project, Anadol’s artist statement says:

“Science states meanings; art expresses them,” writes American philosopher John Dewey and draws a curious distinction between what he sees as the principal modes of communication in both disciplines. In Melting Memories, Refik Anadol’s expressive statements provide the viewer with revealing and contemplative artworks that will generate responses to Dewey’s thesis.

Overall, Melting Memories combines cutting edge thinking in data analytics, particularly the process of transposing complex EEG data, with creativity to produce a beautifully complex and visceral work of art.

Anadol’s website details his artistic processes for creating Melting Memories, and I highly recommend you head over and give it a read.

Another example of data-inspired art that I love is Nathalie Miebach’s weather sculptures.

Nathalie Miebach’s weather sculptures

In this example, the artist used weather data to craft three-dimensional sculptures. Here’s how Miebach describes the project and its inspirations on her website:

Central to this work is my desire to explore the role visual aesthetics play in the translation and understanding of scientific information. By utilizing artistic processes and everyday materials, I am questioning and expanding the traditional boundaries through which science data has been visually translated.

Mieback has created many different sculptures based on the underlying weather data, all of which you can view on her website. But she has also explored other mediums, such as composing musical scores based on the same data. Needless to say, I’m a huge fan of Miebach’s work, and I especially love her underlying message around breaking from convention and exploring new ways to visualize data. Aside from her website, I also recommend watching her TED Talk where she talks about her art form and methods, which you can watch here.

Data As Art

In the two examples above, we looked at artistic works that were made possible by data. But in both cases, the underlying dataset that inspired the art is not really in-focus. That is, the data has been abstracted and is no longer recognizable or readable to the audience (i.e. you can’t see or make sense of the data in Miebach’s weather sculptures or Anadol’s Melting Memories). As a result, the data takes on new meaning and interpretation.

But there are many examples of data-driven art where the data is still visible and readable to the audience. Infographics are a common example of this, where information design is applied to make the process of reading data easier, more enjoyable, or both. However, not all infographics are beautiful works of art. In fact, it’s a medium where I see data visualization design sins frequently committed.

Probably the best curation of artistic data visualization can be found at David McCandless’ Information is Beautiful website. McCandless and team produce some of the most beautiful and compelling interactive dataviz around today, and you can easily lose hours exploring the site. Among his many books, Information is Beautiful and Knowledge is Beautiful are absolute must-haves for anyone even remotely interested in data visualization and information design (and I recommend buying the print edition over digital).

David McCandless - Information is Beautiful

But McCandless’ work aside, one of my favourite examples of Data as Art is Stefanie Posavec and Giorgia Lupi’s Dear Data.

Dear Data was a year long art project between Lupi and Posavec where, every day, each artist would hand draw a data visualization depicting a random data point about their life on a postcard. Then, they would send their postcard to each other (Lupi and Posavec lived on opposite sides of the Atlantic), and they later created a book that featured all of the postcards.

Dear Data By Stefanie Posavec and Giorgia Lupi

At first glance you might think Dear Data should fall into the Data Inspired Art category, particularly since most of their data visualizations appear to be abstract. But each postcard featured a legend, complete with instructions for how to read the graphic.

And so, unlike Anadol and Miebach’s art, which wasn’t meant to be interpreted objectively, Dear Data is different because Lupi and Posavec did want their audience to interpret the graphics and data objectively using the legend and instructions provided.

I really love Dear Data, not just for its artistic beauty but for the lessons it offers to be better communicators with data. Too many people today rely on a design language for data visualization dictated to us through software like Microsoft Excel. Dear Data challenges us to think outside the box by creating our own design language, and to move beyond ‘standard’ types of dataviz like pie or bar charts.

Another great example of creating a custom design language can be found in Fran Geurts dataviz below, which explores how small countries score on the six World Governance Indicators. Rather than use traditional charts like the ones you would find in programs like Excel or Tableau, Geurts created an entirely custom visualization, designed around the story he wanted to tell.

Fran Geurts World Governance Indicators Graphic

At first glance you may have a hard time understanding how to read the graphic, but just like Dear Data, Geurts has created a legend to help his readers understand his design language.

Fran Geurts World Governance Indicators Graphic Legend

Geurts has masterfully constructed this graphic. Having visualized a number of different variables while still making it easy (and enjoyable) to read. So, there are plenty of great learnings here when it comes to information design.

The Intersection of Data Inspired Art and Data As Art

Finally, my last example is probably my all time fav data visualization, and it sits right at the intersection of data-as-art and data-inspired-art. This is, of course, Jonathan Harris and Sep Kamvar’s We Feel Fine. Sadly, the project is now quite dated and the website won’t run on most modern browsers, but you can watch Harris talk about the project and see it in action on his Ted Talk from 2007.

We Feel Fine by Jonathan Harris and Sep Kamvar

As a brief overview, We Feel Fine was developed around an algorithm Harris and Kamvar wrote to crawl Blogger for posts with the text string “I feel…” or “I am felling…”. Once found the crawler would capture the string up to the end of the sentence and pull the data into a custom interactive dashboard. We Feel Fine wasn’t necessarily the first working example of social media monitoring, but in many ways the project inspired the wave of first generation social listening tools that would emerge in the following years.

The interactive dashboard built by Harris and Kamvar was nothing short of an artistic and technological masterpiece. Each "I feel…” post that was captured was then visualized as a single coloured particle, all of which would race around the screen allowing you to interact with. The platform they built also captured the location, date, gender and age of the author as well as the weather at the time of the post, which you were able to apply as filters to play with and analyze the data.

We Feel Fine was an achievement on many fronts, as it broke new ground in areas like data engineering, information design and digital art forms. It is simultaneously a beautiful work of art and sophisticated data visualization that invites its audience to explore and investigate the underlying dataset.

Do you have any other examples of data + creativity? I’d love to hear about it in the comments below. Thanks for reading.