The Fuzziness of Data by London College of Communication

As data visualisations have ‘the potential for meaning-making’ (Engebretsen and Kennedy, 2020), it is important for the general public to have expertise with the fuzziness of data (Cairo, 2017) (uncertainty and fallibility) (Brodlie, Allendes Osorio and Lopes, 2012).
My project focuses on ‘how can we support people’s critical engagement with data by surfacing and making physical the possible uncertainty, fallibility and limitations of data using weather data as an example’.
My project aimed to represent the uncertainty of data, to make it readable by my audience – the general public. However, through my research, I discovered how there is a need to explain and unveil these features of data to raise awareness.

I chose to let the weather inspire the datafication of the forecast. By creating a physical structure that could create shapes on paper based on the discrepancies between forecasts and reported weather I wanted to embody the idea of uncertainty, limitations and fallibility.
To realise my outcome I decided to use a cyanotype treated paper, not only because visually the strong blue connects to the main topic of the weather, but also because is a process where I used the sunlight and the rain – recreated artificially with the dripping – to create the shape of the data.