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Measurement Ontology for IP traffic (MOI)

The present document identifies the requirements that should characterise an ontology for the semantic conceptualisation of information related to IP traffic measurements. The requirements are obtained through the analysis of use cases spanning across a variety of related application categories and domains of interest, as well as the consideration of additional qualitative needs, such as the protection of personal data. Additional inputs arise from user experience, as well as the 'GS/MOI-010' Work Item study, entitled "Report on information models for IP traffic measurement" . The general difficulty of setting limits to an ontology, taking concepts from outside is also dealt within the present document that states MOI focus on IP traffic measurement concepts and let's side ontologies dealing with other subjects, an easy way to link. Thus a rather practical approach to define MOI ontology will be laid so that further QoS, traffic monitoring and Internet governance issues can be built on top of it by means of semantic tools.

W3C Thing Description (TD) Ontology

The Thing Description (TD) ontology is an RDF axiomatization of the TD information model, one of the building blocks of the Web of Things (WoT). Besides providing an alternative to the standard JSON representation format for TD documents, the TD ontology can also be used to process contextual information on Things and for alignments with other WoT-related ontologies.

ISO/IEC 21823-3:2021 Internet of things (IoT) - Interoperability for IoT systems - Part 3: Semantic interoperability

This document provides the basic concepts for IoT systems semantic interoperability, as described in the facet model of ISO/IEC 21823-1, including: - requirements of the core ontologies for semantic interoperability; - best practices and guidance on how to use ontologies and to develop domain-specific applications, including the need to allow for extensibility and connection to external ontologies; - cross-domain specification and formalization of ontologies to provide harmonized utilization of existing ontologies; - relevant IoT ontologies along with comparative study of the characteristics and approaches in terms of modularity, extensibility, reusability, scalability, interoperability with upper ontologies, and so on, and; - use cases and service scenarios that exhibit necessities and requirements of semantic interoperability.

ISO/IEC 21823-3:2021

W3C Semantic Sensor Network Ontology

The Semantic Sensor Network (SSN) ontology is an ontology for describing sensors and their observations, the involved procedures, the studied features of interest, the samples used to do so, and the observed properties, as well as actuators. SSN follows a horizontal and vertical modularization architecture by including a lightweight but self-contained core ontology called SOSA (Sensor, Observation, Sample, and Actuator) for its elementary classes and properties. With their different scope and different degrees of axiomatization, SSN and SOSA are able to support a wide range of applications and use cases, including satellite imagery, large-scale scientific monitoring, industrial and household infrastructures, social sensing, citizen science, observation-driven ontology engineering, and the Web of Things. Both ontologies are described below, and examples of their usage are given.

SAREF4INMA: extension for the Industry and Manufacturing domains

SAREF4INMA focuses on extending SAREF for the industry and manufacturing domain to solve the lack of interoperability between various types of production equipment that produce items in a factory and, once outside the factory, between different organizations in the value chain to uniquely track back the produced items to the corresponding production equipment, batches, material and precise time in which they were manufactured.

SAREF4CITY: extension for the Smart Cities domain

SAREF4CITY is an extension of SAREF for the Smart Cities domain. This extension has been created by investigating resources from potential stakeholders of the ontology, such as standardization bodies, associations, IoT platforms and European projects and initiatives. Taking into account ontologies, data models, standards and datasets provided by the identified stakeholders, a set of requirements were identified and grouped in the following categories: Topology, Administrative Area, City Object, Event, Measurement, Key Performance Indicator, and Public Service.

SAREF4BLDG: extension for the Building domain

SAREF4BLDG is an extension of the SAREF ontology that was created based on the Industry Foundation Classes (IFC) standard for building information. It should be noted that not the whole standard has been transformed since it exceeds the scope of this extension, which is limited to devices and appliances within the building domain.

ISO/IEC DIS 21838-3 Information technology - Top-level ontologies (TLO) - Part 3: Descriptive ontology for linguistic and cognitive engineering (DOLCE)

The Descriptive Ontology for Linguistic and Cognitive Engineering (DOLCE) is a top-level ontology (TLO) conforming to ISO/IEC 21838-1. It contains definitions of its terms and relational expressions and formal representations in OWL 2 and in Common Logic (CL). DOLCE is a top-level ontology aimed at making explicit people-s assumptions about the nature and structure of the world, as reflected by natural language, cognition and human common sense. DOLCE is widely used by a diverse array of domain ontologies in areas like enterprise and process modeling, engineering, robotics, geographical information systems, socio-technical systems and digital humanities. The natural language specification of the DOLCE signature supports human maintenance and use of the ontology, including use in development of conformant domain ontologies. The adoption of the Web Ontology Language (OWL) as a W3C standard was motivated by the need to have a decidable ontology representation language as the basis for the Semantic Web. The OWL 2 formalization of DOLCE supports use of the ontology in computing, including enabling DOLCE to be used in tandem with other ontologies expressed in OWL and in related languages, and in allowing ontology quality control through use of OWL reasoners. The CL formalization of DOLCE provides the expressivity needed to provide an axiomatization whose models are the intended models of DOLCE. This axiomatization has a modular structure (see Figure 2 where the arrows represent the relation of extension of theories). This document conforms to ISO/IEC 21838-1.

ISO/IEC DIS 21838-3