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Linked music data from global music charts

Published: 04 September 2014 Publication History

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.

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Cited By

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  • (2022)Toward Building a Linked Open Data Cloud to Predict and Regulate Social Relations in the Saudi SocietyIEEE Access10.1109/ACCESS.2022.317409010(50548-50561)Online publication date: 2022

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Published In

cover image ACM Other conferences
SEM '14: Proceedings of the 10th International Conference on Semantic Systems
September 2014
161 pages
ISBN:9781450329279
DOI:10.1145/2660517
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

Sponsors

  • St. Pölten University: St. Pölten University of Applied Sciences, Austria
  • University of Potsdam: University of Potsdam
  • PoolParty: PoolParty (Semantic Web Company GmbH)
  • University of Vienna: University of Vienna
  • Wolters Kluwer: Wolters Kluwer, Germany
  • Semantic Web Company: Semantic Web Company
  • STII: STI International
  • DBpedia Association: DBpedia Association

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 04 September 2014

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Author Tags

  1. linked data
  2. music
  3. open data
  4. playlist ontology

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  • Research-article

Funding Sources

  • Faculty of Computer Science and Engineering, at the Ss. Cyril and Methodius University in Skopje

Conference

SEM '14
Sponsor:
  • St. Pölten University
  • University of Potsdam
  • PoolParty
  • University of Vienna
  • Wolters Kluwer
  • Semantic Web Company
  • STII
  • DBpedia Association

Acceptance Rates

SEM '14 Paper Acceptance Rate 22 of 59 submissions, 37%;
Overall Acceptance Rate 22 of 59 submissions, 37%

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Cited By

View all
  • (2022)Toward Building a Linked Open Data Cloud to Predict and Regulate Social Relations in the Saudi SocietyIEEE Access10.1109/ACCESS.2022.317409010(50548-50561)Online publication date: 2022

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