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  • The euBusinessGraph (`ebg:`) ontology represents companies, type/status/economic classification, addresses, identifiers, company officers (e.g., directors and CEOs), and dataset offerings. It uses `schema:domainIncludes/rangeIncludes` (which are polymorphic) to describe which properties are applicable to a class, rather than `rdfs:domain/range` (which are monomorphic) to prescribe what classes must be applied to each node using a property. We find that this enables more flexible reuse and combination of different ontologies. We reuse the following ontologies and nomenclatures, and extend them where appropriate with classes and properties: - W3C Org, W3C RegOrg (basic company data), - W3C Time (officer membership), - W3C Locn (addresses), - schema.org (domain/rangeIncludes and various properties) - DBpedia ontology (jurisdiction) - NGEO and Spatial (NUTS administrative divisions) - ADMS (identifiers), - FOAF, SIOC (blog posts), - RAMON, SKOS (NACE economic classifications and various nomenclatures), - VOID (dataset descriptions). This is only a reference. See more detail in the [EBG Semantic Model](https://docs.google.com/document/d/1dhMOTlIOC6dOK_jksJRX0CB-GIRoiYY6fWtCnZArUhU/edit) google document, which includes an informative description of classes and properties, gives examples and data provider rules, and provides more schema and instance diagrams. @en
  • 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
  • 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
  • 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
  • This vocabulary describes the contact points of the postal agencies network in France. @en
  • Ontology for public services and organizations @en
  • The Semantic Web Conference ontology (SWC) is an ontology for describing academic conferences @en
  • The DBpedia ontology provides the classes and properties used in the DBpedia data set. @en
  • 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
  • The Genealogisches Orts-Verzeichnis (GOV) contains information about current and historical political, ecclesiastical and legal administrative affiliations of settlements and administrative units. In addition several time-dependent values (such as names, population numbers, postal codes etc.) are given. @en
  • This ontology offers OWL-Lite definition for object list. It is a restricted version of OWL-S ObjectList @en
  • The Linked Earth Ontology aims to provide a common vocabulary for annotating paleoclimatology data @en
  • ProVoc (Product Vocabulary) is a vocabulary that can be used to represent information and manipulate them through the Web. This ontology reflects: 1) The basic hierarchy of a company: Group (Company), Divisions of a Group, Brand names attached to a Division or a Group, and 2) The production of a company: products, ranges of products (attached to a Brand), the composition of a product, packages of products... @en