IoT-Stream: A Lightweight Ontology for Internet of Things Data Streams

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(From the article abstract)

In recent years, the development and deployment of Internet of Things (IoT) devices has led to the generation of large volumes of real world data. Analytical models can be used to extract meaningful insights from this data. However, most of IoT data is not fully utilised, which is mainly due to interoperability issues and the dif´Čüculties to analyse data collected by heterogeneous resources. To overcome this heterogeneity, semantic technologies are used to create common models to share variousdata originated from heterogeneous sources. However, semantics add further overhead to data delivery, and the processing time to annotate the data with the model can increase the latency and complexity in publishing and querying the annotated data. In this paper, we present a lightweight semantic model to annotate IoT streams. The metadata descriptions that are provided in the models are used for search and discovery of the data using various attributes such as value and type. The proposed model extends commonly used ontologies such as W3C/OGC SSN ontology and its recent lightweight core, SOSA, and includes conceptsto describe streaming IoT data. We also show use cases, tools and applications where the proposed model has been used.

We propose a lightweight semantic model for the annotation of stream data, IoT-Stream, that extends SOSA, (and by extension SSN) ontology, and therefore is fully compatible with SOSA. In our proposal we have centred the attention around the stream data.

T. Elsaleh, M. Bermudez-Edo, S. Enshaeifar, S. T. Acton, R. Rezvani & P. Barnaghi

University of Surrey, University of Granada, Granada, Spain

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