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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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This ontology extends the SAREF ontology for the building domain by defining building devices and how they are located in a building. This extension is based on the ISO 16739:2013 Industry Foundation Classes (IFC) standard for data sharing in the construction and facility management industries. The descriptions of the classes and properties extracted from IFC have been taken from the IFC documentation. @en
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SAREF4WEAR is an extension of SAREF for Wearables @en
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The Crime Event Model is an ontology for the representation of crime events extracted from local newspapers. It could be employed for Crime Analysis purposes: extracting crime information from newspapers and enriching them with proper machine-readable semantics is a critical task to help law enforcement agencies at preventing crime, supporting criminal investigations and evaluating the action of law enforcement agencies themselves. The model is based on the fundamental 5W1H journalistic questions, that are Who?, What?, When?, Where?, Why? and How?. Another important requirement was the attempt to exploit existing knowledge graphs and ontologies such as the Simple Event Model (SEM) Ontology and the Schema.org data model for interoperability and interconnection. @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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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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Ontology that defines the conceptual model for the Pilot 5 - Smart Building use case @en
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This document is a vocabulary to describe compound measures, i.e. measures with several metric or item that are organized with serveral dimensions. The description of such a measure relies on a Tree-Structure of Requirement (TSoR): a set of requirements structured hierarchicaly with analysis element. A TSoR represents the main measure. Several information may be added to explicitely indicate how the overall score on the measure should be calculated based on the hierarchy, relative importance of the node of the hierarchy and an aggregation function. The measure can be described completely and unambiguously from the organisation to the requirements and the implementation. @en
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CiteDCAT-AP is an extension of the DCAT application profile for data portals in Europe (DCAT-AP) for describing resources documented by using the DataCite metadata schema - the de facto standard for data citation, and used across scientific disciplines. Its basic use case is to make research data searchable on general data portals, thereby bridging the gap between scientific and public sector information. For this purpose, CiteDCAT-AP provides an RDF vocabulary and the corresponding RDF syntax binding for the metadata elements defined in DataCite. @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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The scope of the DIO is the domain of design intent or design rationale that needs to be documented while undertaking the design of any artifact @en
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Digital Twin ontology used to define Digital Twins and Semantic Digital Twins and aggregations by dimensions using Web of Things. @en
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The Heat Pump Ontology (HPOnt) aims to formalize and represent all the relevant information of Heat Pumps. The HPOnt has been developed as part of the REACT project which has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement no. 824395. @en
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An ontology to describe experiments, evaluations and their relation. @en