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  • An Ontology for representing EDIFACT Messages. @en
  • The eccenca Publish-Subscribe Vocabulary defines concepts and relations to create statements about publishers, subscribers and their subscriptions in a Publish-Subscribe environment based on the PubSubHubbub Core 0.4 specification. @en
  • A vocabulary & data model for describing RDF changes and revisions. It defines the Commit & Revision classes together with their expected properties. @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
  • 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
  • OntoGSN is an ontology for managing assurance cases in the Goal Structuring Notation (GSN). The goal of the ontology is to help users in linking the elements of their cases - claims and evidence - with the internationalized resource identifiers (IRIs) of represented concepts, events and data, and in evaluating the validity of their argument. @en
  • 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
  • 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
  • EUdaphobase Taxonomy Ontology for the European Soil-Biology Data Warehouse for Soil Protection @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
  • A vocabulary to represent relations that should be more transparent, usually between powerfull people or institutions @en
  • Ontology that defines the conceptual model for the Pilot 5 - Smart Building use case @en
  • The notion of territory plays a major role in human and social sciences. In an historical context, most approaches are irrelevant as they rely on geometric data, which is not available. In order to represent historical territories,we conceived the HHT ontology (Hierarchical Historical Territory) to represent hierarchical historical territorial divisions, without having to know their geometry. This approach relies on a notion of building blocks to replace polygonal geometry @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