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Memorias de investigación
Ponencias en congresos:
A Linked Data Profiling Service for Quality Assessment
Año:2017
Áreas de investigación
  • Ciencias de la computación y tecnología informática
Datos
Descripción
The Linked (Open) Data cloud has been growing at a rapid rate in recent years. However, the large variance of quality in its datasets is a key obstacle that hinders their use, so quality assessment has become an important aspect. Data profiling is one of the widely used techniques for data quality assessment in domains such as relational data; nevertheless, it is not so widely used in Linked Data. We argue that one reason for this is the lack of Linked Data profiling tools that are configurable in a declarative manner, and that produce comprehensive profiling information with the level of detail required by quality assessment techniques. To this end, this demo paper presents the Loupe API, a RESTful web service that profiles Linked Data based on user requirements and produces comprehensive profiling information on explicit RDF general data, class, property and vocabulary usage, and implicit data patterns such as cardinalities, instance ratios, value distributions, and multilingualism. Profiling results can be used to assess quality either by manual inspection, or automatically using data validation languages such as SHACL, ShEX, or SPIN.
Internacional
Si
Nombre congreso
4th Workshop on Linked Data Quality (LDQ 2017) at ESWC 2017
Tipo de participación
960
Lugar del congreso
Portoroz, Eslovenia
Revisores
Si
ISBN o ISSN
978-3-319-70407-4
DOI
10.1007/978-3-319-70407-4_42
Fecha inicio congreso
29/05/2017
Fecha fin congreso
29/05/2017
Desde la página
335
Hasta la página
340
Título de las actas
In: Blomqvist E., Hose K., Paulheim H., ?awrynowicz A., Ciravegna F., Hartig O. (eds) The Semantic Web: ESWC 2017 Satellite Events. Lecture Notes in Computer Science, vol 10577. Springer, Cham
Esta actividad pertenece a memorias de investigación
Participantes
  • Autor: Freddy Priyatna . (UPM)
Grupos de investigación, Departamentos, Centros e Institutos de I+D+i relacionados
  • Creador: Grupo de Investigación: Ontology Engineering Group
  • Departamento: Inteligencia Artificial
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