I chose to reverse engineer Linked Jazz, a digital humanities research project developed from Semantic Lab at Pratt that builds a network of relationships between jazz musicians. I always loved listening to music and exploring different genres, and jazz is one that doesn’t get a whole lot of attention in the modern world. Linked Jazz tries to bring back that spotlight that jazz used to have and reveal the interconnectedness of the jazz community. The main purpose of this project is to uncover meaningful connections related to the personal and professional lives of jazz musicians and to develop broadly applicable tools and methods for working with Linked Open Data, or LOD.
Linked Open Data is a method of publishing structured data so that it can be easily connected. Linked Jazz does this by means of a huge web diagram. In a genre within a field with an ever-growing number of artists, how does one find every single connection between thousands of artists? Semantic Lab at Pratt developed multiple tools, such as a transcript analyzer, a name mapping and curator tool, and a crowdsourcing tool. These tools read and analyze interview transcripts, figure out which people are being mentioned, and let the public confirm the validity of these transcripts or add information. The transcripts are written records of oral history interviews capturing the conversations between an interviewer and a musician. They are drawn from archives like the Rutgers Institute of Jazz Studies, and the information in these transcripts ranges from personal experiences to careers and collaborations. These are the sources of Linked Jazz.
Through the transcript analyzer and the name mapping and curator tool, the processes involve identifying names, relationships, and mentions from other artists. To add accuracy to the processes, Linked Jazz implemented a feature called 52nd Street, which is the crowdsourcing tool. There, the jazz community refined the data, stating the context and correcting names and relationships.
The presentation is what makes Linked Jazz especially effective. Its network visualizations allow users to observe how musicians are connected across time, emphasizing collaboration over individual fame. Seeing this made me realize how foolish it is to focus on a single individual without acknowledging the other artists and community that helped shape the genre. This can be applied to multiple areas such as sports or history.
One question that I have about this project is what brings together a group of people to commit so much of their time and effort to make something like this. Not only does it require skills such as programming and data analysis, but also research and attention to detail. What was the spark that got everyone on board?