I'm interested in how sound and music can make data more engaging. This data auralisation - a representation of data in sound - tells the story of the things I was most interested in in 2023, and how my content consumption varied across the year.
The data is from my Obsidian vault, a place where I gather extracts and notes from blogs, academic papers, YouTube, podcasts, books, and audiobooks. So this only shows the things I thought were so interesting that I made notes on them.
For each of the top ten topics I consumed the most information about, I chose a diad–two notes–to represent it. The pitch at which the diad is played back varies depending on the source media: low pitches represent weightier sources, books or audiobooks, and higher pitches represent lighter sources like articles or podcasts. The 'noise' sound you hear plays when something I read wasn't in the top ten topics. And, hopefully obviously, time is represented by time. Each bar of music is one day.
To mix in an element of qualitative data (and because I think it sounds cool), I included a snippet from a podcast or audiobook I listened to each month.
The result is what you hear when you press PLAY at the top of the page.