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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
  • 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
  • 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
  • GConsent provides concepts and relationships for defining consent and its associated information or metadata with a view towards GDPR compliance. It is the outcome of an analysis of consent and requirements associated with obtaining, using, and changes in consent as per the GDPR. The ontology also provides an approach to using its terms in various scenarios and use-cases (see more information in the documentation) which is intended to assist in its adoption. @en
  • The General Data Protection Regulation (GDPR) is comprised of several articles, each with points that refer to specific concepts. The general convention of referring to these points and concepts is to quote the specific article or point using a human-readable reference. This ontology provides a way to refer to the points within the GDPR using the EurLex ontology published by the European Publication Office. It also defines the concepts defined, mentioned, and requried by the GDPR using the Simple Knowledge Organization System (SKOS) ontology. @en
  • GDPRov is an OWL2 ontology to express provenance metadata of consent and data lifecycles towards documenting compliance for GDPR. @en
  • 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
  • AIRO represents AI risk concepts and relations based on the AI Act draft and ISO 31000 standard series. @en
  • The Denotative Description module encodes the characteristics of a cultural property, as detectable and/or detected during the cataloguing process and measurable according to a reference system. Examples include measurements e.g. length, constituting materials e.g. clay, employed techniques e.g. melting, conservation status e.g. good, decent, bad. In this module are used as template the following Ontology Design Patterns: - http://www.ontologydesignpatterns.org/cp/owl/collectionentity.owl - http://www.ontologydesignpatterns.org/cp/owl/classification.owl - http://www.ontologydesignpatterns.org/cp/owl/descriptionandsituation.owl - http://www.ontologydesignpatterns.org/cp/owl/situation.owl @en
  • The Core module represents general-purpose concepts orthogonal to the whole network, which are imported by all other ontology modules (e.g. part-whole relation, classification). @en
  • The Context Description module includes models for the context of a cultural property, in a broad sense: agents (e.g.: author, collector, copyright holder), objects (e.g.: inventories, bibliography, protective measures, other cultural properties, collections etc.), activities (e.g.: surveys, conservation interventions), situations (e.g.: commission, coin issuance, estimate, legal situation) related, involved or involving the cultural property. Thus it represents attributes that do not result from a measurement of features in a cultural property, but are associated with it. @en
  • 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
  • Ontology that defines the conceptual model for the Pilot 5 - Smart Building use case @en
  • 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