Sensors 2013, 13(9), 12581-12604; doi:10.3390/s130912581
Article

Ontology Alignment Architecture for Semantic Sensor Web Integration

Department of Computing Engineering, University of Alcala, Superior Polytechnic School, University Campus, Alcalá de Henares 28805, Madrid, Spain
* Author to whom correspondence should be addressed.
Received: 18 June 2013; in revised form: 24 August 2013 / Accepted: 12 September 2013 / Published: 18 September 2013
(This article belongs to the Section Sensor Networks)
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Abstract: Sensor networks are a concept that has become very popular in data acquisition and processing for multiple applications in different fields such as industrial, medicine, home automation, environmental detection, etc. Today, with the proliferation of small communication devices with sensors that collect environmental data, semantic Web technologies are becoming closely related with sensor networks. The linking of elements from Semantic Web technologies with sensor networks has been called Semantic Sensor Web and has among its main features the use of ontologies. One of the key challenges of using ontologies in sensor networks is to provide mechanisms to integrate and exchange knowledge from heterogeneous sources (that is, dealing with semantic heterogeneity). Ontology alignment is the process of bringing ontologies into mutual agreement by the automatic discovery of mappings between related concepts. This paper presents a system for ontology alignment in the Semantic Sensor Web which uses fuzzy logic techniques to combine similarity measures between entities of different ontologies. The proposed approach focuses on two key elements: the terminological similarity, which takes into account the linguistic and semantic information of the context of the entity’s names, and the structural similarity, based on both the internal and relational structure of the concepts. This work has been validated using sensor network ontologies and the Ontology Alignment Evaluation Initiative (OAEI) tests. The results show that the proposed techniques outperform previous approaches in terms of precision and recall.
Keywords: semantic sensor web; ontology alignment; fuzzy logic

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MDPI and ACS Style

Fernandez, S.; Marsa-Maestre, I.; Velasco, J.R.; Alarcos, B. Ontology Alignment Architecture for Semantic Sensor Web Integration. Sensors 2013, 13, 12581-12604.

AMA Style

Fernandez S, Marsa-Maestre I, Velasco JR, Alarcos B. Ontology Alignment Architecture for Semantic Sensor Web Integration. Sensors. 2013; 13(9):12581-12604.

Chicago/Turabian Style

Fernandez, Susel; Marsa-Maestre, Ivan; Velasco, Juan R.; Alarcos, Bernardo. 2013. "Ontology Alignment Architecture for Semantic Sensor Web Integration." Sensors 13, no. 9: 12581-12604.

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