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Ontology for the definition of regions and zones of availability on CloudComputing platforms and services. This ontology allows to define model of regions used in large cloud computing providers such as Amazon, Azure, etc. @en
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Service Level Agreement for Cloud Computing Services. This ontology allows to define model of SLA/SLO used in large cloud computing providers such as Amazon, Azure, etc., including terms, claims, credit, compensations, etc @en
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Ontology for Cloud Computing Instances. Instance are classes of VM that comprise varying combinations of CPU, memory, storage, and networking capacity. This ontology allows to define the instantiation model of MVs used in large cloud computing providers such as Amazon, Azure, etc. @en
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An ontology for describing the shape and the location of topographic entities @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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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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An OWL representation of part of the model for geometry and space from ISO 19107:2003 Geographic Information - Spatial Schema @en
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The DBpedia ontology provides the classes and properties used in the DBpedia data set. @en
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A vocabulary for specifying geographical regions in RDF @en
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A vocabulary for describing topological relations between features @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
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An ontology for publishing descriptions of historical events as Linked Data, and for mapping between other event-related vocabularies and ontologies. @en
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KEES (Knowledge Exchange Engine Schema ) ontology describes a knowledge base configuration in terms of ABox and TBox statements together with their accrual and reasoning policies. This vocabulary is designed to drive automatic data ingestion in a graph database according KEES and Linked (Open) Data principles. @en
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Transport Administration Ontology (TAO) for describing data from Swedish Transport Administration Web site. @en
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OpenVocab is a community maintained vocabulary intended for use on the Semantic Web, ideal for properties and classes that don't warrant the effort of creating or maintaining a full schema. OpenVocab allows anyone to create and modify vocabulary terms using their web browser. @en