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2010•ACM SIGMOD RecordRequires access

Querying RDF streams with C-SPARQL

Davide Barbieri, Daniele Braga, Stefano Ceri, Emanuele Della Valle, Michael Grossniklaus

Open publisher page 180 citations

Abstract

Continuous SPARQL (C-SPARQL) is a new language for continuous queries over streams of RDF data. CSPARQL queries consider windows, i.e., the most recent triples of such streams, observed while data is continuously flowing. Supporting streams in RDF format guarantees interoperability and opens up important applications, in which reasoners can deal with knowledge evolving over time. Examples of such application domains include real-time reasoning over sensors, urban computing, and social semantic data. In this paper, we present the C-SPARQL language extensions in terms of both syntax and examples. Finally, we discuss existing applications that already use C-SPARQL and give an outlook on future research opportunities.

About this research paper

What this paper is about

Continuous SPARQL (C-SPARQL) is a new language for continuous queries over streams of RDF data. CSPARQL queries consider windows, i.e., the most recent triples of such streams, observed while data is continuously flowing. Supporting streams in RDF format guarantees interoperability and opens up important applications, in which reasoners can deal with knowledge evolving over time. Examples of such application domains include real-time reasoning over sensors, urban computing, and social semantic data. In this paper, we present the C-SPARQL language extensions in terms of both syntax and examples. Finally, we discuss existing applications that already use C-SPARQL and give an outlook on future research opportunities.

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OpenAlex reports 180 citations for this work. Citation counts describe recorded attention and do not establish research quality.

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Available abstract

Continuous SPARQL (C-SPARQL) is a new language for continuous queries over streams of RDF data. CSPARQL queries consider windows, i.e., the most recent triples of such streams, observed while data is continuously flowing. Supporting streams in RDF format guarantees interoperability and opens up important applications, in which reasoners can deal with knowledge evolving over time. Examples of such application domains include real-time reasoning over sensors, urban computing, and social semantic data. In this paper, we present the C-SPARQL language extensions in terms of both syntax and examples. Finally, we discuss existing applications that already use C-SPARQL and give an outlook on future research opportunities.

Key concepts: SPARQL, Computer science, Named graph, RDF, RDF Schema, Interoperability, Syntax, Linked data

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