Information designer Giorgia Lupi, founder and design director at Accurat looks for visual metaphors in music notations and architectural drawings. Her goal is to replicate that “digested beauty” in composition with data and find the right balance between innovative approaches and conventional visual keys. In this interview, Giorgia told us about her workflows and the works she is especially proud of – and also shared her thoughts on how journalists should approach data visualizations.
Where do you look for inspiration for your work?
In the last year I took the chance of a few public talks and articles to try to frame my thoughts around my inspiration process that mainly relies on the idea of getting clues and fascinations from various fields and not necessarily form already existent data visualizations not only for amusement, but also as a necessary practice for designers:
It is very important to keep a curious and critical eye on everything that strikes your attention, and to understand why it did, as a constant resource for inspiration, for transferring what we like, visually speaking, into our visual taste.
Looking for clues in unusual contexts can definitely be described as an attempt to discover and dissect the aesthetic qualities of all the things that we naturally like, in order to be able to abstract them and introduce them as core principles and guidelines in building visual compositions.
I ask myself the questions: “What is that I like of what I see? What elements, aspects and features am I appreciating and why?”
And I realized I am mostly inspired by visual languages that are somehow already conventional, the aesthetics of which are familiar to our minds: if a set of aesthetic rules for shapes, for colors, and for spatial composition works in a context I observe, I believe there should be a way to apply them to the designs I am working on. The visual contexts I am referring to are abstract art, but also the repetitive aesthetics of music notations, especially contemporary music notations, or the layering systems of architectural drawings, or even the shapes and features of objects and natural elements: visual environments our minds can refer to even without really getting it.
I thus come up with ideas by looking at different kind of images, abstracting what I like and also redrawing these features to make them mine (I use drawing as my primarily form of understanding, abstracting, and getting inspired) and finally replicating that “digested beauty” in composition with data.
Which visualization project are you especially proud of?
I really still like very much one of the first projects we started back in 2012, and which is an ongoing collaboration for La Lettura, the Sunday cultural supplement of Corriere della Sera, the main Italian newspaper.
We regularly publish our work there and every time we chose the topic we want to explore, we find our own datasets and information to correlate and combine, we try to find the most interesting points of view through which tell the story, or the stories, we imagine a visual model, and we visualize.
And purposely, we aim at composing rich visual narratives: maintaining the informative richness of the data analysis we perform, but making this richness more accessible and understandable through visualization.
We call what we do here a “multilayered storytelling” with a first story that have to be visually clear at a glance, but then can lead readers to get lost in details, in marginal possible explorations and secondary stories. It is like if we could reach a level of interactivity on these static pieces.
Our aim in this project, visually speaking, is really to experiment with customized and even unusual “visual models” – as I would call them – for the data we are analyzing: customized visuals that are 100% fit for that piece, for that moment, for that data, and never starting from any standards.
Every time it takes us few days to find the datasets and to analyze them, and then approximately 2 days to visualize.
Another project that I really liked is a more “simple” one, that is a collaboration with Maria Popova called “Famous Writers’ Sleep Habits vs. Literary Productivity”.
It explores the relationship between famous writers’ productivity and the time they used to wake up, for whom we found these data in diaries or interviews. We then added the main prizes they’ve been awarded with, and their life length, to provide a further context for the readers. And we had this simple idea to build the visualization around Wendy MacNaughton’s portraits, and using the 12-hours ring of the clock as a visual metaphor, so that each authors’ portrait is hypothetically surrounded by a 12-hours clock with a visual mark to point the time they used to wake up; and from this point on the clock, quantitative data on their productivity are visualized.
You yourself don’t code. Do you think that data journalists need to learn how to code?
I don’t code, but in the company we really rely on the multi-disciplinarity of our team for our projects: so far we are around 15 people: interaction designers and visual and graphic designers, software engineers, developers, data scientists and analysts, and content curators. Static data visualizations can definitely be done even without coding, by simply switching from Excel to Adobe Illustrator.
I think the best option for data-journalists would be to have the possibility to collaborate with developers rather than necessarily learning to code themselves.
You have created a lot of visualizations for such media as Corriere della Sera. What are your favorite ones?
I really like one of our first ones, called “Painters in the makings”, where we represented 8 centuries or art and artists displaying the most important 90 painters represented through their main pieces.
This is particularly interesting because for each artist we selected to represent the masterpiece according to the Garzanti Art Encyclopedia, compared with the first Google images result for the author’s name and surname search, plus we represented further information on their ages at the date of paintings, and the main colors, sizes and painting techniques used.
I also like one of our lasts “My reign for a solved paradox” because of the topic which is very fascinating: exploring the 80 most important mathematical problems in history through the year of the formulation, the typology, the status and type of solution and the number of years needed to reach the solution.
One of the most well-known piece of ours is “Nobels no degrees” that won the Information is Beautiful Kantar award last fall.
What is so special about media visualizations in comparison to scientific or business intelligence visualizations?
The possibility to be conceived and developed as entertaining pieces, in these cases we as designers can definitely experiment with non-common aesthetics, balancing convention (i.e. familiar forms, terms our minds are already familiar with) and novelty: new features that can engage and delight people in the hope they will stick around our visualizations a bit longer.
Do you think that visual metaphors like those in “Visualizing painters’ lives” can be implemented in journalism as well or do they tend to be more like art?
They are particular aesthetics that work well to represent articulated datasets and overlapping layers of information: rich narratives, as I’d describe them, where readers are supposed to spend time, and get lost in details.
In fact, whenever the main purpose of visualizations is to open readers’ eyes to new knowledge and to reveal something new about the world, or to engage and entertain the audience about a topic, it’s kind of impractical to avoid a certain level of visual complexity: catching new points of view, or discovering something that you didn’t know before often cannot happen at a glance, this process of “revelation” often needs and require an in-depth investigation of the context.
I think that all of those journalistic pieces that purposely requires to convey such richness can benefit to adopt visual metaphors from visual languages that are already conventional (such as music notation, abstract art) to represent densities of information.
I also think, though, that this process of adopting visual metaphors from different fields is very personal and it really depends on the goals at hand and on the sensibility of the designers.
How would you define successful visual designs?
I define successful visual designs as the ones able to balance convention (i.e. familiar forms, terms our minds are already familiar with) and novelty: new aesthetic representations able to catch readers’ eyes. Sometimes, the act of loading an analytical representation with emotional investment produces attention rather than distraction, creates worlds that are evocative and nameless at the same time, able to inspire sensations, as long as we always respect the values in the data and we don’t manipulate the information.
I think the question to ask here, and now, is “how far can we imagine to go?”, or at least, this is the one I’ve been asking myself for a while.
How can we keep on exploring, guessing, imagining, hunching, trying combinations and trying to inspire feelings, as visual communicators who use images and symbols rather than words and numbers?
There isn’t a unique truth or answer in data-visualization. Instead, there’re many answers to this question, more or less appropriate and effective depending on the scopes and the goals, on the data and on the readers, on the situation and context. Our job with our aesthetic research is not to provide finite and definitive answers. I hope it can rather start a prolific dialogue among practitioners and enthusiasts.
This blog post was originally written for the Open Data Hack Day Blog.