Memorias de investigación
Ponencias en congresos:
SRBench: A Streaming RDF/SPARQL Benchmark
Año:2012
Áreas de investigación
  • Ciencias de la computación y tecnología informática
Datos
Descripción
We introduce SRBench, a general-purpose benchmark primarily designed for streaming RDF/SPARQL engines, completely based on real-world data sets from the Linked Open Data cloud. With the increasing problem of too much streaming data but not enough tools to gain knowledge from them, researchers have set out for solutions in which Semantic Web technologies are adapted and extended for publishing, sharing, analysing and understanding streaming data. To help researchers and users comparing streaming RDF/SPARQL (strRS) engines in a standardised application scenario, we have designed SRBench, with which one can assess the abilities of a strRS engine to cope with a broad range of use cases typically encountered in real-world scenarios. The data sets used in the benchmark have been carefully chosen, such that they represent a realistic and relevant usage of streaming data. The benchmark defines a concise, yet omprehensive set of queries that cover the major aspects of strRS processing. Finally, our work is complemented with a functional evaluation on three representative strRS engines: SPARQLStream, C-SPARQL and CQELS. The presented results are meant to give a first baseline and illustrate the state-of-the-art.
Internacional
Si
Nombre congreso
11th International Semantic Web Conference (ISWC2012)
Tipo de participación
960
Lugar del congreso
Boston (Estados Unidos)
Revisores
Si
ISBN o ISSN
978-3-642-35175-4
DOI
10.1007/978-3-642-35176-1_40
Fecha inicio congreso
10/11/2012
Fecha fin congreso
15/11/2012
Desde la página
641
Hasta la página
657
Título de las actas
The Semantic Web ? ISWC 2012
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: Inteligencia Artificial