A study of existing Ontologies in the IoT-domain

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.

A review of ontologies within the domain of smart and ongoing commissioning

“…Among the various ontologies used for dynamic data types, the SSN ontology was frequently reused in existing ontologies as it provides a comprehensive and clear definitions for sensors and actuators of a system, applicable to a wide variety of use cases. However, at present the Brick ontology [27] provides SCCx applications the most comprehensive BMS and contextual information within the building domain. Brick was developed using a base dataset of more than 17,700 data points in six buildings equipped with BMS from different vendors, and has been demonstrated to capture 98% of these points.…”

“…Beyond proposing comprehensive ontologies, evaluations methods such as using ontology scalability and extensibility checking tools [27] for testing proposed ontologies were inadequate in the literature. To check an ontology's completeness, conciseness, and consistency [81], four evaluation approaches were evident in the literature [82]: (1) ontology comparison, (2) domain-specific document comparison, (3) expert review, and (4) case studies.…”

“…Approach Reference Original ontology creation [61], [49], [14], [46], [52], [48], [37], [54], [29], [15], [67] Synthesis of existing ontologies [60], [62], [47], [24], [21], [50], [63], [51], [64], [53], [35], [55], [56], [57], [65], [66], [58], [68], [69], [59] Review and comparative analysis of existing ontologies [25], [22], [26], [27], [16], [28] The common building data types for which existing ontologies were reused included: indoor conditions and building systems/components, physical building information, simulation-based data, and other building data such as building location, as presented in Table 4. Since the extraction of some data types (e.g.…”

“…Likewise, Gerrish et al [26] explored the capabilities of the IFC schema to integrate a BIM model with building energy models and BMS data for building performance management. Bajaj et al [27] reviewed existing ontologies developed in the IoT domain since 2012. Their objective was to identify the useful concepts for developing a unified IoT ontology and to structure the existing IoT-related literature to help developers create a unified standard ontology.…”

A Cloud Computing Capability Model for Large-Scale Semantic Annotation

“…by annotating the different entities with metadata, fostering the efficiency of the cloud platform, with respect to service delivery across the different models; IaaS (Infrastructure-as-a-Service), PaaS (Platform-as-a-Service) and SaaS (Software-as-a-service). Currently, domain-specific ontologies exist for providing metadata for cloud entities' description [5]. However, rich-content domain ontologies for cloud services are yet to become popular.…”