From 02dcee0cc3c9211748c0e7e3ade63b4fd4a9c95d Mon Sep 17 00:00:00 2001 From: Anna Kijas Date: Tue, 15 Oct 2024 14:24:59 -0400 Subject: [PATCH] updated link --- _posts/2019-02-19-rebalancing-music-canon.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/_posts/2019-02-19-rebalancing-music-canon.md b/_posts/2019-02-19-rebalancing-music-canon.md index ab791842dec3..9eadcf9ae5ef 100644 --- a/_posts/2019-02-19-rebalancing-music-canon.md +++ b/_posts/2019-02-19-rebalancing-music-canon.md @@ -5,7 +5,7 @@ date: 2019-02-19 description: permalink: /rebalancing-the-music-canon/ --- -I'd like to share news about a [project](https:/rebalancing-music-canon.com) that I have been thinking about starting since I gave my [keynote](https://medium.com/@kijas/https-medium-com-kijas-what-does-the-data-tell-us-926ba830702f) about the lack of women and people of color in digital music/data projects at the Music Encoding Conference in May 2018 at University of Maryland. I wanted to create a music data repository focused on works by un(der)-represented people with the aim of decentering the musical canon and making data-driven music scholarship more diverse and inclusive. In particular, the repository will contain a dataset of compositions spanning a large historical period by an un(der)-represented group (primarily women and people of color) that has generally been left out of (big) data driven scholarship work. +I'd like to share news about a [project](https://rebalancing-music-canon.com) that I have been thinking about starting since I gave my [keynote](https://medium.com/@kijas/https-medium-com-kijas-what-does-the-data-tell-us-926ba830702f) about the lack of women and people of color in digital music/data projects at the Music Encoding Conference in May 2018 at University of Maryland. I wanted to create a music data repository focused on works by un(der)-represented people with the aim of decentering the musical canon and making data-driven music scholarship more diverse and inclusive. In particular, the repository will contain a dataset of compositions spanning a large historical period by an un(der)-represented group (primarily women and people of color) that has generally been left out of (big) data driven scholarship work. There are a number of resources out there that can aid in the creation of this repository, one in particular stood out to me as a good candidate for the first corpus. I reached out to Molly Murdock (Eastman School of Music) and Ben Parsell (St. Olaf College) of [Music Theory Examples by Women](https://musictheoryexamplesbywomen.com/contributors/) and discussed my idea of encoding a small corpus of works by women, what the benefits of this would be, and how the data could be used by other scholars, students, and researchers for a variety of purposes, including rendering the scores from [MEI](https://music-encoding.org/) to HTML using a tool called [Verovio](https://www.verovio.org/index.xhtml).