It’s impossible to describe the incandescent beauty of the Milky Way on a clear night, especially if you can get away from the city lights. Nor can you deny the role that stargazing has played in the arts and culture and history of humanity. How terrible, then, must it be to be robbed of this universal experience through failing eyesight?
This is the story of Dr Wanda Diaz Merced, a Puerto Rican astrophysicist who, in a cruelly ironic twist of fate, lost the use of her eyes while she was studying at university.
Most people, when faced with the task of conducting a principally visual science without the use of their eyes, would simply give up. But not Dr Merced. Instead, she embraced the challenge with characteristic pragmatism: she decided to listen to the stars instead.
Now, Dr Merced is pioneering the science of sonification – she uses computer software to translate radio or light waves from satellites and telescopes into sounds. Using this software, she can study the fluctuation in radio signals from a star, or singular astronomical events such as a coronal mass ejection (CME).
“I wanted to do science at the same level as my peers,” she says, matter-of-factly.
Speaking at this year’s Scifest Africa, she describes her work as the auditory analogue of data visualisation. “Each data set, each star and each instrument has its own voice,” she says. And from the smile on her face, she likes the way the choir sings.
Recorded at Scifest Africa 2015
Dr Merced would like her work on sonification to have an impact beyond just allowing her to study astrophysics. She thinks this technology can help sighted astrophysicists to study the skies in greater detail.
She gives the example of the Square Kilometre Array (SKA), the vast telescope currently under construction in the Karoo. When operational, the SKA will produce gigabytes of data every second, and processing this data will be one of the greatest scientific challenges of our time. She hopes that the sonification software that she and her colleagues are developing might help with this task.
“Technology has evolved so much, but we’re still using the same approach to analyse data, over and over again,” she says. “With such huge streams of data, we need to bring new perspectives to the field.”