Linked Music Data from Global Music Charts

Abstract

Accessing data on the Web in order to obtain useful information has been a challenge in the past decade. The technologies of the Semantic Web have enabled the creation of the Linked Data Cloud, as a concrete materialization of the idea to transform the Web from a web of documents into a web of data. The Linked Data concept has introduced new ways of publishing, interlinking and using data from various distributed data sources, over the existing Web infrastructure. On the other hand, music represents a big part of the everyday life for many people in the world, and therefore, understandably, the Web contains loads of data from the music domain. Given the fact that Linked Data enables new, advanced use-case scenarios, the music domain and its users can also benefit from this new data concept. Besides being provided with additional information about their favorite artists and songs, the users can also potentially get an overview of the dynamics of the global music playlists and charts, from the aspects of artists, countries, genres, etc. In this paper, we describe the process of transforming one- and two-star music playlists and charts data from various global radio stations, into five-star Linked Data, in order to demonstrate these benefits. We also present the design of our Playlist Ontology necessary for our data model. We then demonstrate – via SPARQL queries and a web application – some of the new use-case scenarios for the users over the published linked dataset, which are otherwise not available over the isolated datasets on the Web.