Memorias de investigación
Artículos en revistas:
Linked Open Vocabularies (LOV): a gateway to reusable semantic vocabularies on the Web
Año:2016

Áreas de investigación
  • Ciencias de la computación y tecnología informática

Datos
Descripción
One of the major barriers to the deployment of Linked Data is the difficulty that data publishers have in determining which vocabularies to use to describe the semantics of data. This systematic report describes Linked Open Vocabularies (LOV), a high-quality catalogue of reusable vocabularies for the description of data on the Web. The LOV initiative gathers and makes visible indicators such as the interconnections between vocabularies and each vocabulary?s version history, along with past and current editor (individual or organization). The report details the various components of the system along with some innovations, such as the introduction of a property-level boost in the vocabulary search scoring that takes into account the property?s type (e.g, dc:comment) associated with a matching literal value. By providing an extensive range of data access methods (full-text search, SPARQL endpoint, API, data dump or UI), the project aims at facilitating the reuse of well-documented vocabularies in the Linked Data ecosystem. The adoption of LOV by many applications and methods shows the importance of such a set of vocabularies and related features for ontology design and the publication of data on the Web.
Internacional
Si
JCR del ISI
Título de la revista
Semantic Web
ISSN
1570-0844
Factor de impacto JCR
1,786
Información de impacto
Volumen
8
DOI
Número de revista
Desde la página
437
Hasta la página
452
Mes
SIN MES
Ranking

Esta actividad pertenece a memorias de investigación

Participantes
  • Autor: Pierre-Yves Vandenbussche Fujitsu (Ireland) Limited
  • Autor: Ghislain A. Atemezing Mondeca
  • Autor: Maria Poveda Villalon UPM
  • Autor: Bernard Vatant Mondeca

Grupos de investigación, Departamentos, Centros e Institutos de I+D+i relacionados
  • Creador: Grupo de Investigación: Ontology Engineering Group
  • Departamento: Inteligencia Artificial