spallanzani watches the walker

'Spallanzani watches the walker' is a performance that takes place in low light. It consists of three main components:

Data: A small audio device contained GPS data from a segment of a solitary bat walk I undertook in late 2014. Bat walking is a practice of walking at night with an ultrasound detector in order to locate bats in both rural and urban locations. It can be carried out systematically to build datasets, in groups as public engagement events, and by hobbyists and enthusiasts. The GPS data was sonified by using a music progamming language to translate the data into sine waves, pitch and panning. During the performance I listen to this through noise cancelling headphones. The sonification is never shared directly with the audience or with any other individual.
Body: My body, to be specific, that originally went on the nightwalk. It has had many capacities endowed or afforded to it that allowed it to go walking, alone, at night. It could have been another body, but perhaps not any body. Added to it are coins, keys and jewellery, all of which may be carried on nightwanders, all of which can generate sound at frequencies above human hearing. In the performance I shake and move my body according to the sonified GPS. The movements which may or may not convey attributes of the data.
Detector: Heterodyne ultrasound detectors, which tune into frequencies of ultrasound and render them at frequencies we can hear. Each one is tuned to a common frequency used for bat detecting in London. These detectors pick up the ultrasound generated by the coins, keys and jewellery as my body moves to the sonified GPS data. For the performance, two (or more) bat detectors are held by audience members.

Material constructed from the first performance is presented below. All elements contain audio that is automatically played. It is best appreciated in an environment where you are able to listen:

Closed with pitch

Visual analysis of hand movements and cut-up text

A shape in a meadow

GPS data and audio from performance slowed to logged walking time

Not nightly jumble

Visual analysis of knee movements and cut-up text

Notes and acknowledgements