A query model to capture event pattern matching in RDF stream processing query languages

Dell’Aglio, Daniele (Department of Informatics University of Zurich, Switzerland) ; Dao-Tran, Minh (Dipartimento di Elettronica, Informatica e Bioingegneria, Politecnico of Milano, Italy) ; Calbimonte, Jean-Paul (University of Applied Sciences and Arts Western Switzerland (HES-SO Valais-Wallis)) ; Le Phuoc, Danh (Technical University of Berlin, Germany) ; Della Valle, Emanuele (Dipartimento di Elettronica, Informatica e Bioingegneria, Politecnico of Milano, Italy)

The current state of the art in RDF Stream Processing (RSP) proposes several models and implementations to combine Semantic Web technologies with Data Stream Management System (DSMS) operators like windows. Meanwhile, only a few solutions combine Semantic Web and Complex Event Processing (CEP), which includes relevant features, such as identifying sequences of events in streams. Current RSP query languages that support CEP features have several limitations: EP-SPARQL can identify sequences, but its selection and consumption policies are not all formally defined, while C-SPARQL offers only a naive support to pattern detection through a timestamp function. In this work, we introduce an RSP query language, called RSEP-QL, which supports both DSMS and CEP operators, with a special interest in formalizing CEP selection and consumption policies. We show that RSEP-QL captures EP-SPARQL and C-SPARQL, and offers features going beyond the ones provided by current RSP query languages.


Faculty:
Economie et Services
School:
HEG-VS
Institute:
Institut Informatique de gestion
Subject(s):
Informatique
Publisher:
Cham, Springer, Cham, Springer
Date:
Cham, Springer
Cham, Springer
2016
Pagination:
pp. 145-162
Published in:
Knowledge engineering and knowledge management : 20th International Conference, EKAW 2016, Bologna, Italy, November 19-23, 2016, Proceedings
DOI:
ISBN:
978-3-319-49003-8
Appears in Collection:

Note: The status of this file is: restricted


 Record created 2017-11-26, last modified 2019-08-19

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