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  • The Person Core Vocabulary provides a minimum set of classes and properties for describing a natural person @en
  • The Registered Organization Vocabulary is a profile of the Organization Ontology for describing organizations that have gained legal entity status through a formal registration process, typically in a national or regional register. @en
  • FOAF is a project devoted to linking people and information using the Web. Regardless of whether information is in people's heads, in physical or digital documents, or in the form of factual data, it can be linked. @en
  • This document specifies a vocabulary for describing an IBIS (issue-based information system). @en
  • This ontology models personalized tourist experiences by representing cities, points of interest, events, accommodations, restaurants, transportation, and their relationships. This ontology is part of a university project. @en
  • The development of the SAREF4GRID ontology has been partially funded by the IA4TES project (MIA.2021.M04.0008), funded by the Spanish Ministry of Economic Affairs and Digital Transformation and by the NextGenerationEU program @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
  • 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 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
  • A vocabulary to represent relations that should be more transparent, usually between powerfull people or institutions @en
  • AIRO represents AI risk concepts and relations based on the AI Act draft and ISO 31000 standard series. @en
  • The Cultural Event module models cultural events, i.e. events involving cultural properties. @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