What is my PhD about?

I've written academically about my PhD, but I feel for it to be useful, the average person needs to understand what I'm doing from a more foundational standpoint.

So, my PhD title is: Safe listening in music venues: scalable technologies for citizen science and knowledge building.

In simple terms

Safe listening in music venues is to do with providing an environment where people can go to music venues and enjoy them, without dealing with the aftermath of loud sound exposure.

Many of us are aware of how loud music venues are. Some of us actively avoid them due to their volume. Not to mention that it can and does cause hearing loss for a lot of people. Studies suggest over 1 billion young people are at risk of hearing loss due to it.

Scalable technologies for citizen science and knowledge building sounds a lot more complicated than it is:

• Scalable technologies refer to tech solutions, think Google, SQL or even this website!
• Citizen science is to do with the study of the general public, more importantly, including them in the research process
• Knowledge building is the practice of increasing the knowledge base around a given topic a.k.a providing ways to learn more about a situation

So in simple terms, I'm working on building tech tools to support the analysis of citizens involved in music venues, such that further knowledge can be built around safe listening in music venues.

Phew.

Is what I do, actually research?

It's been on my mind recently, as my PhD feels more building-focused rather than insights-driven. A lot of my peers have more analytical PhDs where they can analyse data and gather insights. Mine is more "I built this cool thing and I think it works?".

It is still considered research, and I would go as far to say that it's an application of R&D (Research and development). I'm building things that don't yet exist, or iterating over existing platforms to make them better for my domain, safe listening in music venues!

It's pretty cool - cause whilst we have a lot of data on the impacts loud sounds have on individuals, we don't have a huge amount of data on how these impact individuals themselves. It's one thing to know "this venue reached a sound level of 80dB" which is considered to be on the high end. But it's another to know what that means for individuals in that space.

That's sorta the justification for my PhD. If we know more about how individuals feel about sound exposure in music venues, we can use that knowledge to implement better procedures and principles that support safe listening in music venues.

So, what am I actually building?

Currently, I've been working on a common data model for sound data. The motivation behind this is to create a standard format for sound data to follow, such that analysis of sound data can be generalised.

At the moment, sound data is quite scattered and the formats vary so much. This makes it hard to translate insights from varying sources of sound data. Think on a global scale, sound data from the UK is hard to compare against sound data in Amsterdam due to the formatting differences.

Introducing, my data model! It aims to provide one format that everyone can use to analyse their sound data. It bridges that communication gap and reduces a lot of friction on the data analysis process.

I've mostly completed this project, with some presentations and a paper along the way.

What's coming up?

I want to explore whether there's any way to build a tool to gather insights from audience members. As I said before, that's the biggest knowledge gap in the safe listening space.

Some ideas involve building an app where event goers can share their experiences of a music venue, symptoms or any other sensations. Currently, we tend to get this data in the aftermath of a music event, meaning that a lot of it can be inaccurate due to recall bias (this means that it can be hard to accurately remember how something was after it happened).

It's bound to be a fun project to work on. Alongside this, there's potential to pair this tool with the data model I built earlier, to build a comprehensive view of the sound exposure in a music venue and how it impacts individuals.

What kind of tasks do I do?

I'm either coding or writing. Most of my work relies on my coding skills so I spend a lot of time on that. Though nowadays I've been writing a lot more, as documenting my research is just as important as doing it.

I code primarily in Python or SQL. Though I feel I should learn R and Matlab instead of ignoring them. I managed to avoid them in my comp-sci masters and now I hear researchers love using them. Chaos.

That's about it

It's a bit of a ramble, but that's basically what I do, how I do it, and what I'll be doing in my PhD. I might update this post overtime, but yeah. That's it, lol.