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  • The AtomOWL ontology is inspired from the work done by the atom working group. This ontology is working off the rfc 4287 published among othe places at http://www.atompub.org/rfc4287.html . The AtomOWL ontology uses as much as possible the same terms as the format there to make the relation easy to understand. The AtomOWL name space is slightly different from the atom namespace [see post http://www.imc.org/atom-syntax/mail-archive/msg16476.html]. But this is a good thing as it helps distinguish the ontology from the rfc 4287 serialisation. @en
  • The ReSIST Courseware Ontology represents the various educational courses and resources within the ReSIST project @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
  • The EUropean Research Information Ontology (EURIO) conceptualises, formally encodes and makes available in an open, structured and machine-readable format data about resarch projects funded by the EU's framework programmes for research and innovation. @en
  • This vocabulary describes the contact points of the postal agencies network in France. @en
  • Press.net Asset Ontology describes news assets (text, images, video, data, etc), the relationships between them and how assets can be classified and semantically annotated. @en
  • Ontology for public services and organizations @en
  • Press.net Event Ontology models news-worthy events and their relationship to news assets and stuff (simple entities) in the world. @en
  • Press.net Stuff Ontology models real world entities. There are two kinds of stuff: tangibles and intangibles. Tangible stuff includes persons, locations and organizations. Intangibles are abstract concepts such as smoking, feminism or love. @en
  • The Semantic Web Conference ontology (SWC) is an ontology for describing academic conferences @en
  • A vocabulary to annotate RDF schemas (in particular SHACL shapes) with metadata to define mappings to GraphQL. @en
  • 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