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This ontology extends the SAREF ontology for the environment domain, specifically for the light pollution domain, including concepts like photometers, light, etc. @en
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The present document is the technical specification of SAREF4SYST, a generic extension of [ETSI TS 103 264 SAREF](https://www.etsi.org/deliver/etsi_ts/103200_103299/103264/02.01.01_60/ts_103264v020101p.pdf) that defines an ontology pattern which can be instantiated for different domains. SAREF4SYST defines Systems, Connections between systems, and Connection Points at which systems may be connected. These core concepts can be used generically to define the topology of features of interest, and can be specialized for multiple domains. The topology of features of interest is highly important in many use cases. If a room holds a lighting device, and if it is adjacent with an open window to a room whose luminosity is low, then by turning on the lighting device in the former room one may expect that the luminosity in the latter room will rise. The SAREF4SYST ontology pattern can be instantiated for different domains. For example to describe zones inside a building (systems), that share a frontier (connections). Properties of systems are typically state variables (e.g. agent population, temperature), whereas properties of connections are typically flows (e.g. heat flow). SAREF4SYST has two main aims: on the one hand, to extend SAREF with the capability or representing general topology of systems and how they are connected or interact and, on the other hand, to exemplify how ontology patterns may help to ensure an homogeneous structure of the overall SAREF ontology and speed up the development of extensions. SAREF4SYST consists both of a core ontology, and guidelines to create ontologies following the SAREF4SYST ontology pattern. The core ontology is a lightweight OWL-DL ontology that defines 3 classes and 9 object properties. Use cases for ontology patterns are described extensively in [ETSI TR 103 549 Clauses 4.2 and 4.3](https://www.etsi.org/deliver/etsi_tr/103500_103599/103549/01.01.01_60/tr_103549v010101p.pdf). For the Smart Energy domain: - Electric power systems can exchange electricity with other electric power systems. The electric energy can flow both ways in some cases (from the Public Grid to a Prosumer), or in only one way (from the Public Grid to a Load). Electric power systems can be made up of different sub-systems. Generic sub-types of electric power systems include producers, consumers, storage systems, transmission systems. - Electric power systems may be connected one to another through electrical connection points. An Electric power system may have multiple connection points (Multiple Winding Transformer generally have one single primary winding with two or more secondary windings). Generic sub-types of electrical connection points include plugs, sockets, direct-current, single-phase, three-phase, connection points. - An Electrical connection may exist between two Electric power systems at two of their respective connection points. Generic sub-types of electrical connections include Single-phase Buses, Three-phase Buses. A single-phase electric power system can be connected using different configurations at a three-phase bus (RN, SN, TN types). For the Smart Building domain: - Buildings, Storeys, Spaces, are different sub-types of Zones. Zones can contain sub-zones. Zones can be adjacent or intersect with other zones. - Two zones may share one or more connections. For example some fresh air may be created inside a storey if it has two controllable openings to the exterior at different cardinal points. A graphical overview of the SAREF4SYST ontology is provided in Figure 1. In such figure: - Rectangles are used to denote Classes. The label of the rectangle is the identifier of the Class. - Plain arrows are used to represent Object Properties between Classes. The label of the arrow is the identifier of the Object Property. The origin of the arrow is the domain Class of the property, and the target of the arrow is the range Class of the property. - Dashed arrows with identifiers between stereotype signs (i.e. "`<< >>`") refer to OWL axioms that are applied to some property. Four pairs of properties are inverse one of the other; the property `s4syst:connectedTo` is symmetric, and properties `s4syst:hasSubSystem` and `s4syst:hasSubSystem` are transitive. - A symbol =1 near the target of an arrow denotes that the associated property is functional. A symbol ? denotes a local existential restriction.  @en
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This ontology extends the SAREF ontology for the water domain. This work has been developed in the context of the STF 566, which was established with the goal to create three SAREF extensions, one of them for the water domain. @en
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SAREF4WEAR is an extension of SAREF for Wearables @en
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The BCI ontology specifies a foundational metadata model set for real-world multimodal Brain Computing Interface (BCI) data capture activities. The ontology defines a minimalist and simple abstract metadata foundational model for real-world BCI applications that monitors human activity in any scenario. BCI multimodal domain applications are encouraged to extend and use this ontology in their implementations. @en
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This ontology defines a vocabulary for describing cyber physical systems for monitoring purpose. It contains two main concepts: CPSWatch#MonitoredSystem that is a top level description of a System that is modeled and CPSWatch#MonitoringSensor that is a top level description of a sensor used to monitor the CPSWatch#MonitoredSystem. @en
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The Internet of Things taxonomy is extended with semantic ontologies for IoT layers, containing classes, properties, individuals, and rules specific to IoT technologies, tools, and applications @en
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Ontology that defines the conceptual model for the Pilot 5 - Smart Building use case @en
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This ontology is intended to describe Semantic Actuator Networks, as a counterpoint to SSN definition of Semantic Sensor Networks. An actuator is a physical device having an effect on the world (see Actuator for more information). It is worth noticing that some concepts are imported from SSN, but not SSN as a whole. This is a design choice intended to separate as much as possible the definition on actuator from the definition of sensor, which are completely different concept that can be used independantly from each other. This ontology is used as a ontological module in IoT-O ontology. @en
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MOAC, the Management of a Crisis Vocabulary, is a lightweight vocabulary aiming to provide terms to enable practitioners to relate different "things" in crisis management activities together as Linked Data. The initial MOAC terms originated from the Inter Agency Standing Committee (IASC), Emergency Shelter Cluster in Haiti, UNOCHA 3W Who What Where Contact Database @en
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The Ontology of units of Measure (OM) 2.0 models concepts and relations important to scientific research. It has a strong focus on units, quantities, measurements, and dimensions. @en
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Arpenteur ontology is dedicated to photogrammetry, archeology and oceanology communities in order to perform tasks such as image processing, photogrammetry and modelling. @en
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A Knowledge Model to describe a smart city, that interconnect data from infomobility service, Open Data and other source @en
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domOS Common Ontology (dCO) represents a common information model to share a unified understanding for humans and machines and to ensure semantic interoperability in a heterogeneous IoT infrastructure. This ontology allows the decoupling of the infrastructure from the software services and applications. @en
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This ontology describes wildlife observations generated by sensors. @en