A few weeks ago I attended ‘field.work‘ an event arranged by Havas who’ve just published some of the keynotes and breakout sessions. Nathalie Miebach spoke at the event, an artist who “translates science data into sculpture, installation and musical scores”. Here’s one of Nathalie’s sculptures.
Insights ‘stand out’ in 3D models
At first look I found this an impenetrable ball of wires and flags — not a sculpture I’d necessarily want to display and admire (and definitely not dust!). However, when Nathalie started to talk through the data points that she’d used, and how she’d constructed the sculpture piece by piece, it took on new meaning.
Natalie starts to build her sculptures using a timeline basis – imagine a clock face representing duration as the foundations. From there, she takes other data such as high tides, low tides, peak and trough temperatures etc. and builds these out from the timeline to create a 3D object. What I found most interesting was that in a 3D object, the anomalies were far more evident than they were within the report she was using as the basis, they literally ‘stood out’ (or sank back).
Kinesthetic learning provides tangible highlights and lowlights
Much of our earliest learning is by ‘doing’ rather than sitting, listening and transcribing. As we grow up, the opportunities for this ‘kinesthetic learning’ tend to decline as we lean towards written and spoken communication. This is certainly the case in the corporate world – the interpretation of ‘big data’ and analytics is primarily through spreadsheets, reports, dashboards etc. Nathalie’s approach suggests that there are other ways of (quite literally) modelling data – that can provide immediate insight rather than picking out trends and anomalies amongst seas of numbers – data realisation rather than visualisation.
Are experts needed for interpretation?
Having an object that needs an expert/creator to provide context in order to understand it, is not ideal, however even with a small amount of unaided effort inspecting the object – the anomalies in the weather data were evident. As a method of serving up data I think Nathalie’s data sculptures are an interesting approach to providing insight and I wonder how 3D printing might be used to build models of data in a similar way.
The intersection of ‘maker movement’ and ‘big data’
Extending the notion of 3D printing to interpret ‘big data’, Nathalie’s data sculptures feel like an intersection between the ‘maker movement‘ with its strong focus on using and learning practical skills and applying them to reference designs, and the world of big data and analytics – a new approach to data insight that provides, quite literally, tangible results.