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I’ve composed the sound and music for this work – Exhibition at MOD, Adelaide from 1 Feb, 2022

https://trackerdataproject.com/

Adam Goodes, Angie Abdilla, Baden Pailthorpe, Ngapulara Ngarngarnyi Wirra, Tracker Data Project (2022).

Multimedia Installation: External space: 2 x synchronised 4k projections, 4-channel audio surround sound. Screen dimensions: 5120 (h) x 3200 (w) mm Digital files: 2 x mp4 video files (3840 x 2160p) with unique video and stereo audio tracks (representing Ararru & Mathari (North & South)). Internal space: 2 x synchronised HD videos, stereo sound, and wall text. Digital files: 2 x mp4 video files (1920 x 1080p) with the same stereo audio track (representing Ararru & Mathari (North & South)).

Every AFL game Adam Goodes played, his body was tracked 10 times per second via a global network of satellites and a small device on his back.

Adam’s phenomenal spatial awareness and ability to see and predict patterns within time and space is derived from an alternate world view.

This is expressed through a deep connection to Country and heightened spatial awareness.

When Adam played at his best, he felt guided by his ancestors. As such his vast dataset is culturally significant.

Yet this significance has remained invisible until now…

This exhibition reveals the cultural significance of Adam’s data through the Adnyamathanha kinship system. This system is based on two Moieties (blood groups) with specific characteristics: Ararru (North Wind) and Mathari (South Wind). Adam belongs to the Ararru Moiety.

The Ararru (North Wind) and Mathari (South Wind) in the exhibition space were recorded on Adnyamathanha Yarta as they swirled around the Wirra (tree). The wind moves through this space via speakers on the North and South side.

nside the Wirra, Adnyamathanha Elder Uncle Terrence Coulthard tells the Adnyamathana Muda of Ikara (Wilpena Pound) in the Adnyamathanha Yura Ngawarla (language).

You can also hear the voice of Adam Goodes echoing key sections of this Muda in Ngawarla (language), with footage of Adnyamathanha Yarta (Country) playing on two screens.

We trained a machine learning model to translate this key Adnyamathanha Muda into the sound of the Ararru (North) and Mathari (South) winds by programming their characteristics into an algorithm.

This materialises the connection between Country and Kinship systems through an embodied experience enabled by the cultural initiation of machine learning.

CREDITS

Dataset: Adam Goodes

Audio & video recording on Country: Angie Abdilla, Baden Pailthorpe, James Alberts

Drone piloting on Country: James Alberts, Baden Pailthorpe

3D scanning on Country: Baden Pailthorpe

Composer/sound design: James Brown

Machine learning: Rupert Parry

Video editor & language recording/engineering: John Gillies

Project Manager: Eloise Hastings

Web designer/developer: Mitchell Whitelaw