Beautiful data for complex humans


Can we visualise an individual’s emotions without violating his private life ?

Chorus is a speculative project developed for the “Make it Wearable” challenge. Chorus is a device that detects and shares your emotional state with you. Chorus is placed on your forehead, analyzing your brainwaves and heart rate. The device analyses the data and indicates your main emotional state via a light signal. The data collected is displayed on a digital platform allowing the user to observe the evolution of his or her emotional state in a respectful way. The purpose of this concept is to promote understanding of inner life, contextualise complex emotional states and eventually to offer a new way to visualise sensitive data. The Chorus project won the 2014 Visionary Track award presented by Intel in San Francisco.

Chorus is a proposal for complex and non-intrusive data visualization

The starting point of this research was the current fascination that we’re cultivating for data, from mining it to depicting it. Quantified self, big data, data visualization, all these terms have been coined more or less recently to embody one new reality: data equals money. In a consumer society data is the main tiller for marketing processes, data is widely used for economic purposes and is displayed to humans (understand consumers) in a very simplistic way. Secondly data is gathered using agressive methods reaping of any sort of private life we’ve been nursing. Therefore we’re consenting to this digital colonisation without any resistance. Chorus is a two-question proposal: Does data need to be represented in such a simple way? Does data analysis have to pierce every aspect of our privacy?

Emotions as data

We chose to work with emotions as they appear to us the most sensitive data nowadays. Emotions, as data, are also very difficult to depict with the simplistic data visualizations generally used. We designed a fake sensor that could record brain waves and heart rate and then interpret every emotional state that the wearer feels.  As we needed a theoretical framework for our data analysis we picked the Plutchik’s wheel of emotions which is one of the most influential classification approaches for general emotional responses. From this framework we determined a emotional data classification as shown above and below (Illustrations by Oscar Mantilla)

Depicting emotions should be a visual poetry not a statistical reviewing

Anatomy of an emotional drop

The challenge we faced was to conceive a data visualization method that would protect privacy but also depict the complex and beautiful cycle of emotions. Each individual feels in a unique way, if we would have force a dogmatic visualization it would have been restrictive and therefore not effective. The solution was to not intervene on the final representation so we designed a method inspired by natural fluid mechanics that would do the work for us.

Each recorded emotion is represented by a drop, this drop has fluid properties inspired by emotion: negative emotions will be more dense, positive emotions will be more soluble. The drop forming a circle will produced a gradient composed from recorded emotions. One by one, the drops will fall to the middle of a canvas. Therefore all fluids will have to work together in terms of solubility, as they are either incorporated into or rejected from the design, creating a never-ending visualization of emotions and providing us with meaningful maps.

Visualization should not aim for the answer

Using this method the final visualization is a natural cipher that can only be decoded by the individual that felt the depicted emotions. The aim of this visualization is not to provide an answer but to offer a natural representation of what can’t be seen but only felt. Bars, columns, charts will never be an effective answer for this kind of datasets. Data visualization methods will have to evolve with the datasets they’ve been provided because everything can’t be analytically depicted, especially when it comes to a human being.


Design and Direction  Oscar Mantilla & Gauthier Roussilhe
Engineering Yacine Remini
Photo— Ghislain Mirat
Fashion Design  Cae
Model Iris Johner
Date  Oct 2014



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