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The Occupancy Profile ontology has been developed to represent people’s behavior inside building spaces. @en
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A Multilingual and Multicultural Ontology Representing Family Relationships. @en
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The ontology of agent relationships, AgRelOn, defines relations of persons to other persons and to organisations @en
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The Cochrane Core ontology describes the entities and concepts that exist in the domain of evidence based healthcare. It is used for the construction of the Cochrane Linked Data Vocabulary containing some 400k terms including Interventions (Drugs, Procedures etc), Populations (Age, Sex, Condition), and clinical Outcomes. @en
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The PICO ontology provides a machine accessible version of the PICO framework. It essentially provides a model for describing evidence in a consistent way. The model allows the specifying of complex populations, detailed interventions and their comparisons as well as the outcomes considered. The PICO ontology was originally designed to model the questions asked and answered in Cochrane's systematic reviews. As a leader in the field of evidence based healthcare Cochrane uses the PICO model when framing and publishing evidence based questions. The PICO model is widely adopted for describing healthcare evidence, furthermore is equally applicable in other evidence-based domains. It essentially provides a model for describing evidence in a consistent way. @en
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The ontology of the taxonomy "European Skills, Competences, qualifications and Occupations". The ontology considers three ESCO pillars (or taxonomy) and 2 registers. The three pillars are: - Occupation - Skill (and competences) - Qualification For the construction and use of the ESCO pillars, the following modelling artefacts are used: - Facetting support to specialize ESCO pillar concepts based on bussiness relevant Concept Groups (e.g. species, languages, ...) - Conept Groups, Thesaurus array and Compound terms (as detailed in ISO 25964) to organize faceted concepts - SKOS mapping properties to relate ESCO pillar concepts to concepts in other (external) taxonomies (e.g. FoET, ISCO88 and ISCO08. More mappings can be added in the future.) - Tagging ESCO pillar concepts by other (external) taxonomies (NUTS, EQF, NACE, ...) - Capture gender specifics on the labels of the ESCO pillar concepts - Rich ESCO concept relationships holding a description and other specific characteristics of the relation between two ESCO pillar concepts. ESCO maintains two additional registers: - Awarding Body - Work Context Awarding Bodies typically are referenced by ESCO qualifications. Occupations can have one or more work context. @en
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This vocabulary describes the contact points of the postal agencies network in France. @en
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Ontology for public services and organizations @en
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The Semantic Web Conference ontology (SWC) is an ontology for describing academic conferences @en
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The DBpedia ontology provides the classes and properties used in the DBpedia data set. @en
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The ontology aims at modelling the data on cultural institutes or sites such as data regarding the agents that play a specific role on cultural institutes or sites, the sites themselves, the contact points, all multimedia files which describe the cultural institute or site and any other information useful to the public in order to access the institute or site. Moreover, the ontology represents events that can take place in specific cultural institutes or sites. @en
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The ontology describing the Shoah domain, proposed here in beta version, aims to formally describe concepts and relationships that characterize the process of persecution and deportation of Jews in Italy between 1943 and 1945. @en
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Person ontology in Dutch @en
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A vocabulary to express information about people and their relations with Organizations, Companies, etc. @en
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Erlangen CRM / OWL - An OWL DL 1.0 implementation of the CIDOC Conceptual Reference Model, based on: Nick Crofts, Martin Doerr, Tony Gill, Stephen Stead, Matthew Stiff (eds.): Definition of the CIDOC Conceptual Reference Model (http://cidoc-crm.org/). This implementation has been originally created by Bernhard Schiemann, Martin Oischinger and Günther Görz at the Friedrich-Alexander-University of Erlangen-Nuremberg, Department of Computer Science, Chair of Computer Science 8 (Artificial Intelligence) in cooperation with the Department of Museum Informatics of the Germanisches Nationalmuseum Nuremberg and the Department of Biodiversity Informatics of the Zoologisches Forschungsmuseum Alexander Koenig Bonn. The Erlangen CRM / OWL implementation of the CIDOC Conceptual Reference Model is licensed under a Creative Commons Attribution-ShareAlike 3.0 Unported License. @en