A Query Model to Capture Event Pattern Matching in RDF Stream Processing Query Languages

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.


Editor(s):
Blomqvist, E
Ciancarini, P
Poggi, F
Vitali, F
Published in:
Knowledge Engineering And Knowledge Management, Ekaw 2016, 10024, 145-162
Presented at:
20th International Conference on Knowledge Engineering and Knowledge Management (EKAW), Bologna, ITALY, NOV 19-23, 2016
Year:
2016
Publisher:
Cham, Springer Int Publishing Ag
ISSN:
0302-9743
ISBN:
978-3-319-49004-5
978-3-319-49003-8
Laboratories:




 Record created 2017-03-27, last modified 2018-09-13


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