Towards efficient processing of RDF Data Streams

Llaves Arellano, Alejandro and Corcho, Oscar and Fernández García, Javier D. (2014). Towards efficient processing of RDF Data Streams. In: "3rd International Workshop on Ordering and Reasoning", 20 Oct 2014, Riva del Garda, Italia. pp. 55-60.

Description

Title: Towards efficient processing of RDF Data Streams
Author/s:
  • Llaves Arellano, Alejandro
  • Corcho, Oscar
  • Fernández García, Javier D.
Item Type: Presentation at Congress or Conference (Article)
Event Title: 3rd International Workshop on Ordering and Reasoning
Event Dates: 20 Oct 2014
Event Location: Riva del Garda, Italia
Title of Book: OrdRing 2014 Ordering and Reasoning
Título de Revista/Publicación: CEUR Workshop Proceedings
Date: 2014
Volume: 1303
Subjects:
Freetext Keywords: RDF Stream Processing; Adaptive Query Processing; RDF Com- pression
Faculty: E.T.S. de Ingenieros Informáticos (UPM)
Department: Inteligencia Artificial
Creative Commons Licenses: Recognition - No derivative works - Non commercial

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Abstract

In the last years, there has been an increase in the amount of real-time data generated. Sensors attached to things are transforming how we interact with our environment. Extracting meaningful information from these streams of data is essential for some application areas and requires processing systems that scale to varying conditions in data sources, complex queries, and system failures. This paper describes ongoing research on the development of a scalable RDF streaming engine.

Funding Projects

TypeCodeAcronymLeaderTitle
FP7FP7/2007-2013UnspecifiedUnspecifiedEuropean Union's Seventh Framework Programme
Government of SpainTIN2013-46238-C4-2-RUnspecifiedUnspecified"4V: Volumen, Velocidad,Variedad y Validez en la Gestin Innovadora de Datos

More information

Item ID: 36784
DC Identifier: http://oa.upm.es/36784/
OAI Identifier: oai:oa.upm.es:36784
Official URL: http://ceur-ws.org/Vol-1303/
Deposited by: Memoria Investigacion
Deposited on: 16 Mar 2016 12:23
Last Modified: 16 Mar 2016 12:23
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