190
results
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Simple and direct pricing ontology for Cloud Computing Services. This ontology allows to define model of prices used in large cloud computing providers such as Amazon, Azure, etc., including options for regions, type of instances, prices specification, etc. @en
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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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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 Identifier Ontology models non-RDF based Identifiers for resources. It is used to maintain a mapping between RDF resources identifiers and their equivalent IDs in an alternate, non-RDF based domain. @en
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The DBpedia ontology provides the classes and properties used in the DBpedia data set. @en
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An OWL representation of parts of the Geographic Metadata model described in ISO 19115:2003 with Corrigendum 2006 - LI Package @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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R4R is a light-weight ontology for representing general relationships of resource for publication and reusing. It asserts that a certain reusing context occurred and determined by its two basic relations, namely, isPackagedWith and isCitedBy. The isPackagedWith relation declares the resource is ready to be reused by incorporating License and Provenance information. The Cites relation is an exceptional to isCitedBy which occurs only two related objects cite each other at the same time. Five resource objects including article, data, code, provenance and license are major class concepts to represent in this ontology. The namespace for all R4R terms is http://guava.iis.sinica.edu.tw/r4r/ @en
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This vocabulary set can represent 5W1H (Who, What, When, Where, Why, How) in event (scene) descriptions. This file is also provided in Knowledge Graph Reasoning Challenge. @en
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This ontology offers OWL-Lite definition for object list. It is a restricted version of OWL-S ObjectList @en
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Transport Administration Ontology (TAO) for describing data from Swedish Transport Administration Web site. @en
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An ontology for describing vehicles and their emissions. @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