This document describes a semantic-driven complex event processing (CEP) approach for delivering personalized information streams from data-intensive monitoring systems. The approach combines semantic web technologies like ontologies and SPARQL queries with CEP engines to analyze runtime events and match them to predefined patterns and rules. An architecture is proposed that uses an ontological model, a runtime event processor using predefined rules, information source adapters to transform data, and an information dispatcher to deliver personalized data to applications. The implementation separates each layer as a Java application and uses technologies like Jena, Drools Fusion, and ZeroMQ for communication.

1. Semantic-Driven CEP for Delivery of
Information Streams in Data-
Intensive Monitoring Systems
•Date: July, 2015
•Linked to: RTD at FAST
Contact information
Tampere University of Technology,
FAST Laboratory,
P.O. Box 600,
FIN-33101 Tampere,
Finland
Email: fast@tut.fi
www.tut.fi/fast
Conference: 13th IEEE International
Conference on Industrial Informatics,
INDIN 2015. Cambridge, United Kingdom
– July 22-24 2015
Title of the paper: Semantic-Driven CEP
for Delivery of Information Streams in
Data-Intensive Monitoring Systems
Authors: Yulia Evchina, Jose L. Martinez
Lastra
If you would like to receive a reprint of
the original paper, please contact us
Email of the corresponding author: yulia.evchina@tut.fi

2. Semantic-Driven CEP for Delivery of
Information Streams in Data-
Intensive Monitoring Systems
Yulia Evchina
Prof. Jose L. Martinez Lastra, Dr.Sc.
Tampere University of Technnology, Finland

3. Monitoring systems trends
• Heterogeneous and multiple devices
• More users and user groups
• Systems are hard to configure and information is
delivered regardless to user needs
• The aim is to deliver personalized information to
each user of the system
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4. Approach. Combination of
Semantic Web and CEP
• Semantic Web (SW) technologies are the W3C
standards for describing and relating information
– OWL ontologies, SPARQL queries
• Complex Event Processing (CEP) is the method
for analyzing run-time events and matching
them with predefined patterns or rules
– CEP engines
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5. Proposed architecture
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• Ontological model & semantic
reasoner
– Models of users, devices,
places…
• Run-time event processor
– Predefined rules
• Information source adapters
– Transforming data to internal use
• Information dispatcher
– Transforming data to external
applications

6. Application ontology
overview
• Each concept has
underlying taxonomy
specific to domain
• Individuals of ontology
describe specific features
of the system
• Ontology with taxonomies
and individuals comprises
knowledge model of the
system
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7. Application ontology
example
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• The information from model is submitted to CEP engine
• CEP analyzes information from ontology and data from devices
• Configuration of the middleware assumes only changing knowledge
model

8. Implementation
• Each architecture layer is
separate java web
application
• The communication is done
via DPWS Web Services
(DPWS4J, JMEDS) and
ZeroMQ communication
library
• Ontology is manipulated with
Jena framework
• CEP engine is Drools Fusion
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9. Summary
• The number and diversity of devices result in
bulky information flows
• Combination of SW technologies and CEP
could enable selective information delivery
– CEP allows event-driven monitoring
– SW technologies allow easier
(re)configuration of the system
12.8.2015INDIN 2015 9