A study of existing Ontologies in the IoT-domain

TL;DR

This paper surveys existing semantic ontologies in the IoT domain, highlighting their features, limitations, and the need for a unified ontology to improve interoperability and data reuse across applications.

Contribution

It provides a comprehensive overview of current IoT ontologies, identifying gaps and advocating for a unified ontology to address interoperability issues.

Findings

Existing ontologies cover key concepts like sensor capabilities and context-awareness.

Many ontologies have limitations in scope and interoperability.

A unified ontology is needed for better IoT data integration.

Abstract

Several domains have adopted the increasing use of IoT-based devices to collect sensor data for generating abstractions and perceptions of the real world. This sensor data is multi-modal and heterogeneous in nature. This heterogeneity induces interoperability issues while developing cross-domain applications, thereby restricting the possibility of reusing sensor data to develop new applications. As a solution to this, semantic approaches have been proposed in the literature to tackle problems related to interoperability of sensor data. Several ontologies have been proposed to handle different aspects of IoT-based sensor data collection, ranging from discovering the IoT sensors for data collection to applying reasoning on the collected sensor data for drawing inferences. In this paper, we survey these existing semantic ontologies to provide an overview of the recent developments in this field. We highlight the fundamental ontological concepts (e.g., sensor-capabilities and context-awareness) required for an IoT-based application, and survey the existing ontologies which include these concepts. Based on our study, we also identify the shortcomings of currently available ontologies, which serves as a stepping stone to state the need for a common unified ontology for the IoT domain.