We firmly believe that data visualisation has a wealth of exciting commercial applications, from communicating in new ways to developing new tools, apps and utilities for clients and consumers alike. So we’ve grown slightly frustrated by the rise of visualisations that are moderately pretty but add little in terms of real insight, utility or illumination.

We’re also, as we may have mentioned,  big fans of Manuel Lima here at Labs. So we were intrigued to see that he has authored an “Information Visualisation Manifesto”, a provocative (but characteristically generous and nuanced) take on the future of data visualisation which tackles head on the thorny questions at the heart of this ever-expanding field:

• Art versus Science
• Intrigue versus Immediacy
• Aesthetics versus apprehension.

 Manuel comes down firmly on the side of clarity of communication versus visualisation for visualisation’s sake, citing the discipline’s roots in the desire “to facilitate understanding and aid cognition” and a growing frustration with the “eye candy” approach to the craft. Many of his principles are rooted in this utilitarian approach, reading almost like a Bauhaus manifesto (and none the worse for that):

• Form follows Function
• Do not glorify Aesthetics
• Look for relevancy
• Aspire for Knowledge

It’s a bold, purist and punchy vision yet also acknowledges the power of narrative and the role of intrigue. Indeed the question of narrative seems to lie at the heart of this Manifesto; the need to pose a specific question of the data and to weave coherent themes and stories from it. These themes then drive the aesthetic approach. As Manuel puts it:

“Form doesn’t follow data. Data is incongruent by nature. Form follows a purpose, and in the case of Information Visualisation, Form follows Revelation”

This is perhaps the key distinction between Information Visualisation as defined here and what Manuel suggests we start thinking of as “Information Art”. Within this approach, artists will freely allow form to follow data, using the random-ness this creates to add texture and interest. Take, for example, Aaron Koblin’s desire to embrace the random-ness of a data set and indeed the richness and texture added to his famous Radiohead video by “interrupting the data”:

“I think it really gives character, because I think it’s really that kind of intricacy and detail that builds character and in a sense it’s the errors and flaws that make art”.

Incongruity making art: Aaron Koblin's "House of Cards" promo for Radiohead

As ever, then, we need to return to objectives, to ask what we are trying to achieve:

• Do we want to educate around an issue, making complex questions simple?
• To shift perceptions and provoke a response?
• To offer a fresh perspective on an infrastructure question for our clients?
• To offer our consumers better comprehension and control of their behaviours?  

Simply put, are we going to offer something that is either very, very useful or very, very beautiful? Either way, greater clarity of intent and greater discipline throughout the industry can only be an advantage in building credibility and engagement. Building that credibiltiy is vital if data viz is going to become not just an entertaining diversion but a vital tool for navigating a world generating more and richer data by the second.

If what we are building is neither very beautiful nor very useful, to Manuel’s final point “Avoid Gratuitous visualisations”: “Simply conveying data in a visual form, without shedding light on the portrayed subject, or even making it more complex, can only be considered a failure”. 

Or as William Morris put it: “Have nothing in your house that you do not know to be useful, or believe to be beautiful”.

I recently attended an excellent Made by Many event hosted at BBH which featured a re-presentation by Manuel Lima of his 2009 TED talk on data visualisation. Manuel is the curator of visualcomplexity.com and is an eloquent, modest, charming pioneer in this fascinating field.

As a novice myself, I could not help wondering why we are all so immediately and instinctively attracted to the best of data visualisation.To start with, I’m sure there is some fundamental truth that for most of us data become meaningful only when we can see scale, change, patterns and relationships. Seeing is understanding.

It’s also very reassuring to discover that complex, seemingly chaotic data sets and networks can be expressed as elegant, colourful, ordered maps and models. Perhaps there’s something akin to what the Enlightenment scientists felt as every new discovery revealed the endless beauty of nature.

Indeed the best examples of data visualisation have their own aesthetic beauty. (I felt a nostalgic pang as I recalled time spent with spirograph in my bedroom as a child.)

Like spirograph, but better: Email map by Christopher Baker

To some extent however this elegance, which makes data visualisation so immediately compelling, also represents a challenge. It’s possible that the translation of data, networks and relationships into visual beauty becomes an end in itself and the field becomes a category of fine art.

No harm in that perhaps.

But as a strategist one wants not just to see data, but to hear its story. And it can seem that for some visualisations the aesthetic overpowers the story. I spent many hours when younger staring at data tables, yearning for them to reveal a narrative. It is the prospect of bringing articulacy to hitherto cold, laconic facts that should be at the heart of the excitement around data visualisation.

The more compelling projects from Manuel’s archive did indeed seem to reveal some insightful truth about the relationships that they considered. Enron’s email patterns, the map of Segolene Royal’s supporters, the plotting of visitor eye traces in Barcelona, all looked extremely useful.

Enron Communication Graph, by Kitware Inc.

With this last instance in particular,  one can start to imagine how understanding the dynamic patterns of tourist traffic around the city and its most photographed areas might enable the development of all kinds of helpful tools and services for both tourist and city.

Tracing the Visitor's Eye by Fabien Girardin

Manuel himself talked about ‘turning tools of curiosity into tools of functionality’. In this respect he quoted Chaomei Chen: ‘A taxonomy of information visualization is needed so that designers can select appropriate techniques to meet given requirements.’ And clearly this desire to enable greater utility is driving Manuel’s own research into the different methods and models of visual representation.

As a pioneer in his field, Manuel discussed the opportunities emerging in interactive data maps and he described a Californian experiment in which it should be possible physically to interact with a huge data set distributed about a six storey building.  Blimey. I think I’ll leave that to the true data connoisseurs …

Finally, as a grey haired strategist, I found myself considering how the paucity of visual representation techniques had impacted the way we tackled problems in the past. I think we knew fundamentally that most events were precipitated by complex systemic pressures and relationships. But our limited power to disentangle the many elements in one system reduced us to characterising most strategic problems in rather monochrome ways.

So, this is progress indeed. Data visualisation has radically improved our understanding of these complexities. The real question is: what will we do with that understanding?