Memorias de investigación
Ponencias en congresos:
Guidelines for multilingual linked data
Año:2013
Áreas de investigación
  • Informática,
  • Lingüística computacional
Datos
Descripción
In this article, we argue that there is a growing number of linked datasets in different natural languages, and that there is a need for guidelines and mechanisms to ensure the quality and organic growth of this emerging multilingual data network. However, we have little knowledge regarding the actual state of this data network, its current practices, and the open challenges that it poses. Questions regarding the distribution of natural languages, the links that are established across data in different languages, or how linguistic features are represented, remain mostly unanswered. Addressing these and other language-related issues can help to identify existing problems, propose new mechanisms and guidelines or adapt the ones in use for publishing linked data including language-related features, and, ultimately, provide metrics to evaluate quality aspects. In this article we review, discuss, and extend current guidelines for publishing linked data by focusing on those methods, techniques and tools that can help RDF publishers to cope with language barriers. Whenever possible, we will illustrate and discuss each of these guidelines, methods, and tools on the basis of practical examples that we have encountered in the publication of the datos.bne.es dataset.
Internacional
Si
Nombre congreso
3rd International Conference on Web Intelligence, Mining and Semantics (WIMS'13)
Tipo de participación
960
Lugar del congreso
Madrid
Revisores
Si
ISBN o ISSN
978-1-4503-1850-1
DOI
Fecha inicio congreso
12/06/2013
Fecha fin congreso
14/06/2013
Desde la página
1
Hasta la página
11
Título de las actas
3rd International Conference on Web Intelligence, Mining and Semantics (WIMS'13)
Esta actividad pertenece a memorias de investigación
Participantes
Grupos de investigación, Departamentos, Centros e Institutos de I+D+i relacionados
  • Creador: Grupo de Investigación: Ontology Engineering Group
  • Departamento: Lingüistica Aplicada a la ciencia y a la Tecnología
  • Departamento: Inteligencia Artificial