One of the things we do as AS IF Center is to catalyze collaborations through Art-Science Matchmaking. I hope you enjoy this guest post by Judith Casseday about one such collaboration with Rob Dunn Lab. – nl
I have a keen interest in data sonification that furthers our understanding of the data. This blog post by Mark Ballaro and George Smoot increased my interest in exploring how modal/timbral shifts that are set in a familiar, well-tempered scale spectrum might illustrate data-driven relationships. Recently, I read a notice from AS IF about collaborating with Rob Dunn’s Lab on a project studying microbiology of sourdough. It felt like a dream! I have a two and half year old sourdough starter which is used to create 75% of the bread I eat, I recently studied cell biology and neurobiology, I have a deep interest in molecular chemistry about which I am just learning, and I am looking for a data sonification project. I sent the Dunn Lab an inquiry, they checked out my sound work, and I was invited to participate.
First I met with the sourdough folks at Rob Dunn’s Lab — Erin McKenney, post-Doctoral Fellow in Microbiome Research and Education and a research lead on the sourdough project, and Lauren Nichols, Dunn Lab Manager. I learned that the sourdough project is looking at the ecology of sourdough starter communities as relates to yeast and bacteria growth in flour when exposed to water and the local microbial environment. I attended a Dunn lab staff meeting and learned about the amazing research they are doing. All the projects are basically looking at how the smallest phenomena impact much larger phenomena and vice versa, the micro to macro to micro feedback loop. They keep finding that diversity is the key to sustainable growth and a healthy environment. I left the meeting excited and inspired! Next stop will be the AS IF Center in October, for a retreat with some of Rob Dunn’s collaborators on the sourdough project.
I wanted to sonify some data to prepare for the sourdough meeting, so I reached out to the Dunn Lab folks, and Erin McKenney sent me a data set to try my hand at. The data, from Erin’s dissertation study, is about nine lemur babies belonging to three different species, and enumerates how the microbial colonies in their guts evolve from birth to weaned. We have identifiable parameters that can be orchestrated to show changes over time. Perfect!
The lemur microbial data is on a massive spreadsheet with lots of terminology I don’t know… yet. This will be an interesting process as we work out exactly what the sonic illustration will depict. I sense that certain data will lend itself to sonification and that is the part I do not yet know. After spending some time studying the spreadsheet, I asked Erin how we can cluster some of the microbial data together, and she sent me the data sheets for the bacteria, classified at the phylum and class levels. The phylum-level data became my focus as there were only 35 phyla as opposed to 95 classes and 255 strains of bacteria. One of the lemur mothers had triplets so I decided to put together phylum-level profiles on this small group. Culling through the data for these specific individuals narrowed the number of phyla down to 24, then I made an arbitrary cutoff point of >.00 density for each phylum (Erin said this was fine and is actually a tool scientists use to declutter data). Now I was down to 15 phyla – a manageable number for timbral illumination.
The microbes were collected from the three lemur babies at six time points, from birth to nine months old. These time points were birth, nursing, introduction of solid foods, regular consumption of solid foods, and two times as they were weaning. Microbes were collected from the mother when she gave birth. Erin had the brilliant idea to have the mother’s phylum-level profile (which represents the stable adult community, and does not change over time) be a drone under the babies’ phylum-level profiles in the sound illustration. This allows you to hear when the profiles diverge and when they converge.
The sonic substance for all this is a phyla megachord that stretches from G1 to G5. Each phylum is voiced by a single pitch, so, for example, Protobacteria is G1. Since there are only thirteen pitches in a chromatic scale, some of the phyla would land on the same pitch, different octaves. There were five phyla that tended to have the highest presence in each sample, so I made them the Gs, and all the rest had separate, distinct pitches. I used amplitude to render the amount each phylum was present in each sample.
The next question was how to voice the individual profiles in order to hear the data as clearly as possible. After much experimentation, I decided to represent the mother’s voice as a woodwind with steady, slightly pulsing tone throughout. I chose bell-like voices for the three lemur baby profiles, letting each phase ring out four times over the mother’s profile. The idea is to listen and compare the mother’s profile with the babies’ profiles. Listen for the change (or lack of change) as the each stage rings in four times. What you hear is a uniformity of tone at birth that becomes more dense and dissonant as the phyla diversify with the babies’ diversifying diet. Then the final wean profile settles into more consonance with the mother’s profile.
You can listen to the lemur data sonification project here, and soon I’ll begin experimenting on sonifying data from the sourdough project.