Constructing Event Processing Systems of Layered and Heterogeneous Events with SPARQL

  • Mikko Rinne
  • , Esko Nuutila

Research output: Contribution to journalArticleScientificpeer-review

3 Citations (Scopus)
35 Downloads (Pure)

Abstract

SPARQL was originally developed to process queries over finite-length datasets encoded as RDF graphs. Processing of infinite data streams can be enabled through continuous incremental evaluation of an incoming event stream. SPARQL Update provides tools for interconnecting queries, enabling event processing applications to be constructed out of multiple incrementally processed collaborating rules. These rule networks can perform event processing on heterogeneous event structures. Heterogeneous event support combined with the capability to synthesise new events enables the creation of layered event processing networks. In this paper, we review the different types of complex event processing building blocks presented in the literature and show their translations to SPARQL Update rules through examples, supporting a modular and layered approach. The interconnected examples demonstrate the creation of an elaborate network for solving event processing tasks. The performance of the example event processing network is verified on the INSTANS platform.
Original languageEnglish
Pages (from-to)57-69
Number of pages13
JournalJournal on Data Semantics
Volume6
Issue number2
Early online date23 Sept 2016
DOIs
Publication statusPublished - Jun 2017
MoE publication typeA1 Journal article-refereed

Keywords

  • Complex event processing
  • SPARQL
  • heterogeneous events
  • Stream processing

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