An Ear to the Sky: Intuitive Exploration & Discovery in Astronomical Data using Sonification

The recent decades of astronomy has seen an ever more detailed physical picture of our Universe emerge, with the enhanced sophistication of observations and physical models. However, the growing detail and volume of data presents its own problems; human data exploration can become overwhelming, despite its central role in historical scientific discovery.

Machine-learning tools have arisen to help, but human intuition for the data remains key to their development and interpretation. This problem afflicts how we interface with data at all levels, from high-level research, to presenting data to the public. What's more, the visual bias of data presentation excludes those with visual impairments, likely contributing to a strong underrepresentation of Visually Impaired (VI) researchers in the field.

For this program we propose development of novel tools and techniques for 'sonification' (encoding data into sound) to provide a unique perspective on astronomical data sets, in particular the STRAUSS code (Sonification Tools and Resources for Analysis Using Sound Synthesis).

This free and open source python library uses an object-oriented and abstracted approach to allow uses to 'sonify' their own data, analogous to how a plotting library can be used for visualisation. STRAUSS will be used to sonify light spectra for classification, and as the basis for a novel IFU explorer, allowing users to hear the third frequency axis as they explore the 2D-projected spatial axes.

We will also explore using STRAUSS to monitor high-volume data and as a way to present data to the public via a unique planetarium & VR show. Together, we intend to partner with commercial firms interested in human curation and exploration of big-data, as well as accessibility for a more inclusive society. Through commercial support we hope to maximise the broad societal and interdisciplinary benefits we perceive, establishing new intuition and accessibility for complex data in the global community.