Using Semantic Web for Internet of Things Interoperability

Abstract

The main vision of the Internet of Things (IoT) is to enable seamless connection between physical devices and information systems to improve the lives of people. One of the main obstacles to achieve this vision is the current lack of IoT interoperability. In this article, the authors are giving an overview on how semantics is used in IoT interoperability related research. To do this, they performed a systematic literature review and extracted data from 105 selected primary studies dealing with semantics in IoT interoperability. The authors have analysed the maturity level of this research field and when and where the relevant works were published. This article answers five main research questions about the following issues: what are semantics used for; what types of ontologies exist (which are used to give semantical descriptions); what are the main themes and suggestions for future work in these research articles; and what are other related areas.

Interoperability of the Time of Industry 4.0 and the Internet of Things

“…Consequently, we intend to limit our self to describing the current trends without a structured categorization. This problem is also outlined by Andročec et al [20]; the article is the most recent survey at the time of writing. The authors were forced to limit the survey to scientific contributions published until 2016, clearly outlining the difficulty of catching a moving target.…”

Popularity-Driven Ontology Ranking Using Qualitative Features

“…We propose to derive a popularity measure based on corresponding scientific publications associated with an ontology. We are inspired to follow this approach as a large number of ontologies for WoT application domains emerge from research projects, as evidenced in [1,10,13,16]. Furthermore, it overcomes several limitations of other approaches: (i) as previously discussed, LOD does not provide a reliable source for ontology reuse in WoT application domains; (ii) deriving relevance through user click logs requires access to closed back-ends of existing ontology search engines with a large user base; (iii) human labeling is costly and, unlike mining relevance from scholarly data, does not come with the benefit of being reproducible.…”

“…The large number of available ontologies and the fast-paced developments in domains often make it difficult to find and select the most appropriate ontologies. For the WoT case, this is evidenced through extensive surveys in the literature [1,10,13,16]. This does not only concern ontologies with regard to sensors and sensor network setups, but further to sensor observations [13] (e.g., in the context of smart city use cases with regard to the environment, transportation, health, homes, and factories).…”

Performance Evaluation of the Semantic Web Reasoners

“…Here we present highlights of the major paper reviewed. [1] In their paper did an extensive analysis of large scale reasoning algorithms which works on the increasing volume of semantically interlinked data. The paper also presented a structured review of the literature where scalable reasoning approaches were used over different OWL profile languages.…”