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Data sonification: A tool for public engagement? Sumeet Kulkarni shares insights from his reporting

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In this segment, CivicSciTV’s Questions of the Day Host Fanuel Muindi talks with Sumeet Kulkarni, an Astrophysics PhD candidate (at the time of recording) from the University of Mississippi and a science writer with a passion for science communication and education. The topic? The landscape of the fascinating world of data sonification – the practice of converting scientific data into sound. The conversation is anchored on Kulkarni’s article titled “The sounds of science” which he published as a science news intern at the LA Times during his stint in the 2022 AAAS Mass Media Fellowship program. Kulkarni takes us into the inspiration behind the article and shares insights on what he learned about the evolving landscape of data sonification and its potential to transform the way we understand scientific discoveries and engage the broader public.

References

Sumeet Kulkarni: https://www.latimes.com/people/sumeet…

Sounds of Science: https://www.latimes.com/science/story…

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Transcript

Fanuel Muindi
So what does science sound like well, this is a question I had been pondering about for quite some time. Then I came across an article titled The sounds of science, written by Sumeet Kulkarni, who joins me today. Sumeet, welcome,

Sumeet Kulkarni
Hi. Thanks for inviting me

Fanuel Muindi
so at the top of your article in the LA Times, it reads and I quote, why just look at your data when you could listen. Scientists are turning their data into sound to gain new insights into things as small as DNA and as large as galaxies. End. Quote, Sumeet, tell me how did you come to even be writing this article? Take us back a little bit

Sumeet Kulkarni
Sure. Out of the whole spectrum you just described, I think I was motivated by it, by on its larger end, which is the galaxies. That’s how I first came across this term called Data sonification, which is the practice of converting scientific data or an image into sound. And I was quite enthralled. And the specific application I first came across was a sonification by NASA’s Chandra X Ray Observatory. And what they really wanted to do was convert one of the X ray images of, I think it was like a supernova remnant from from an object known as the grab Nebula, into sound. And I was, I, first of all, I just thought, that’s a really I was like, Wow, can can you convert an image into sound? And when I read more about it, like I it made total sense, because astronomy, which is what I’ve been studying for the past few years as well, it’s such a visual field. Because, like, we always see pictures, like recently from the James Webb Space Telescope, it is completely visual. And they really came forward and thought, like, we need to make this accessible to the visually impaired, like, because, like, everyone needs to appreciate the universe like it’s not just because we’re collecting pictures, doesn’t mean that we should keep it hidden from from those who can’t actually see their picture. So this was an effort by them to, like, represent various parts of the image, and kind of captured the excitement of of the far away based on that. So I thought that was really cool. And when I was at the LA Times writing as a working with the science desk as a mass media fellow in the summer of 2022, I decided to write about it.

Fanuel Muindi
That’s and and for those who are listening, please do click down below and read the article. So tell us a little bit. What did you discover in your research to write this article? Because you know you you talk to quite a at least in your article, you cover a lot of some of these scientists that are using data certification right, not only as a means to showcase the science, but actually to discover. Right for discovery as a process for discovery. Tell us what you learned as you wrote this article.

Sumeet Kulkarni
Yeah, that was one of the things I was most excited to learn about for sure, like so when you when you start out in science writing, they always say, write about, write a story, and not just about a topic. And I knew I wanted to write about the topic of sonification, but it was through a conversation with my editor when we kind of chalked out, you know how to write it as a story. And that’s when I started, like talking to people about because I knew from NASA’s application that accessibility is one way sonification is used, and it’s used in a really impactful manner, but there have to be other. Motivations, why people do it. And I think it was my editor who also thought about asking around, just, is someone using this for analyzing data? And I just thought that was that was a cool thing. So this is when I found out this group at the University of Illinois, Urbana Champaign, who work on studying how proteins fold and unfold, and that’s something that can that’s really important in studying neurodegenerative diseases like Alzheimer’s, because they are caused due to the misfolding of proteins. And they, they really, I think that was the first application I found when where people were actually directly converting their sound into data and learning more about the data in that process. Because these, these processes that they were studying, they are so incredibly they they’re either incredibly fast and complex, like even if you do the simulations of the proteins and watch it in slow motion, there are details that you can miss which you would not if you just converted that into sound because our ears have a different, almost like a different way of pattern identification than what our eyes can do, or what even software that we write can do. And in fact, a lot of the software that we use for data analysis are inspired by how we listen to sounds. And the other example, which I could not write about since I was working in the field, and there was a conflict of interest, is, is the field of gravitational wave astronomy, where we study these ripples in space time given off by events like colliding black holes and neutron stars. And the data that we get through gravitational waves is it lies in the exact sound spectrum that that corresponds to our audible range. So we can actually they are layout these collisions of black holes, and they kind of sound like zip and the way we analyze these signals from a lot of noise, the way we pick out these from a lot of noises, like we use algorithms that have also been used for, say, analyzing music or analyzing, like time series spectrum, spectra corresponding to audio. So that was, like, the second thing like, I found about so there’s accessibility, there’s like, how you can actually do data analysis using sound. And then the third thing was, I found people who were just doing it because they wanted to produce music. So these were, like, artistically inclined scientists. So some of them were like drummers for, you know, a band that played in the 80s and and they, yeah, they just wanted, they saw beauty in their data.

Fanuel Muindi
And then I think you are referring to graduate student Noah girolas, that’s right, because you have the jazz of ocean chemicals, right? And so I, like you, kind of have separated these two camps, right? You have those who are using sound as a vehicle to actually, you know, make discoveries right and understand the data right in new ways, and there are others who are just curious about the music that it creates as well, right? Is there where I know this is still an early field. People were doing this for quite some time. Is there one camp that is doing more than the other? Like, is there sort of more of more of the music side or more of the data side?

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Sumeet Kulkarni
I would say there are more people possibly doing on the music side, because, because few people consider sonification as an option to or explore it as an option to do data analysis. I think it’s not widely known, and that is something maybe you know. If we if more people learn about the story, they might think about ways to incorporate it into their own research, whereas on the music side, I think it’s just people who sort of see it as a hobby, see it as an extension of their work, what they do in the lab, and maybe try to find new inspiration through the music.

Fanuel Muindi
Could it be used? Do you think on the music side. It as a vehicle for public engagement.

Sumeet Kulkarni
Absolutely, I think it’s one of the best ways you can, you know, just, you know, play a sound that’s kind of out of the, you know, out of the pop music, or out of the ordinary, and then get people hooked on to asking questions like, Okay, what? What is this exactly? And you can tell them, Oh, this is actually my DNA, or, you know, one on one gene that’s that’s been, you know, encoded from my own body and, and how cool is that, right? So it’s, it’s something I think, that can be used very effectively in public engagement. The other thing also is, like, if you think about community science initiatives, there are a lot of these which demand the user to, you know, maybe have an app or do some visual data analysis and that that’s that’s great, but if you think about like, why people want to take part in these initiatives, it could be that they are just motivated by that particular area of science, like I would, I would personally spend a lot of time, you know, identifying or classifying galaxies, for example. But as also, as someone who also spends a lot of time at their computer, you want other avenues to be spending that time. So if, if I get a chance to do that kind of exercise through audio instead, I think that would be, that would be an another, another way to contribute to science, and at the same time not doing something like not staring at the screen for for a long time. So I think that’s there are ways in which you can creatively, like, catch, catch on to people’s attention. Yeah.

Fanuel Muindi
And since is publication. So you, you published this back in February 2023, can you share what was the response like? What kinds of responses did you get from people, if any?

Sumeet Kulkarni
Yeah, I think people were just like, oh, this is this is cool. This is something that I didn’t seen before, a lot of, I think, let me try to, yeah, it was largely like, positive and largely about, like, how cool it is, if I had to, you know, encapsulate this in a few words,

Fanuel Muindi
yeah, because, because it’s not, it’s not new, it’s just not well known, right? And it’s not done in volumes that where, for example, we’re not having concerts, right? Of sounds of new, sounds of science, no, I would like to see, by the way, which, which will be cool, by the way, right? But, but, yeah, because that’s the feeling that I’m curious about, in terms of, is there a potential here, right, to really use this as a vehicle to to bring in the public? Right? Actually, maybe do. It’s even that some citizen science using sound, is all these sounds maybe have been created. It’s use people’s ears to, like, detect things, right? We already do this for light. Why not sound

Sumeet Kulkarni
absolutely and the other thing that really touched me was the the story of Amy Bauer, who is, who is a visually impaired scientist, and something as a student in science myself, we take for granted absolutely all the time is like, we always report results in terms of plots visualizations that is like that, that just leaves out a sizable chunk of people. I think even like leaves out the entry for people visually impaired people into the sciences, and that’s something we definitely need to do better. I think I’ve heard some people think of ways to develop software that can produce the equivalent of a plot, but in terms of sound, and if you can, if you can streamline that, like there are so many tools that are widely used for data visualization, but if there are tools that are that get developed for data sonification, I think that’ll be a great thing,

Fanuel Muindi
yeah. And I think maybe even the word sonification probably scares a whole ton of people away. And there’s a quote, actually, from what you were just talking about by Martin grubele, the biochemist whom you talk to. And I quote, he writes, you have to think of that sound in the same way that you think about a graph as opposed to a painting. End quote, yeah. I love that quote. Yeah. And that’s so I think there’s, there’s a lot that can be done here. And I think there’s opportunities to engage the public, of course, opportunities for more data analysis, more unique ways, for example, and and I will say that this is what inspired us to even create the show sounds of science as well. So in terms of reactions to your article, well, there’s one whole new show was created with the same name.

Sumeet Kulkarni
I’d love to hear that. It’s that’s an honor. Thank you.

Fanuel Muindi
So Sumeet, you are a graduate student. You are. We’re talking to you 10 days away from your defense, actually, what did you What did you learn from this? Because you did this program as an intern at the LA Times during your graduate training. What did you learn from that experience that you’re now going to take away as you move on to other things after you graduate?

Sumeet Kulkarni
Well, I learned that I like, I personally like to report on science that’s happening across a broad range, as opposed to what I’ve been researching, which was like a very narrow corner of astrophysics. And I like stories that make an impact, so I hope to keep reporting on these kinds of stories, and and based on people’s response, you know, keep finding like, you know, unearthed gems like like this particular story, keep, you know, bringing out into The open things that that are not commonly talked about, and that’s that’s what I want to

Fanuel Muindi
do, one step at a time. Sumeet alkani, thank you so much for joining me today. We hope to have you back. You

Fanuel Muindi is a former neuroscientist turned civic science scholar-journalist and entrepreneur. He is a Professor of Practice in the College of Arts, Media, and Design at Northeastern University where he leads the Civic Science Media Lab. Dr. Muindi received his Bachelorโ€™s degree in Biology and PhD in Organismal Biology from Morehouse College and Stanford University respectively. He completed his postdoctoral training at MIT.

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