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An RDF/OWL vocabulary to represent SRTI DATEX II profile (according the Commission Delegated Regulation (EU) No 886/2013) within the European LOD-RoadTran18 action "Supporting the cross-border use of Road Traffic Data with Linked Open Data based on DATEX II (LOD-RoadTran18)" (Agreement No: INEA/CEF/ICT/A2018/1803421, Action No: 2018-EU-IA-0088). The vocabulary is used for mapping between DATEX II and LOD formats. @en
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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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This is the human and machine readable Vocabulary/Ontology governed by the European Union Agency for Railways. It represents the concepts and relationships linked to the sectorial legal framework and the use cases under the Agency´s remit. Currently, this vocabulary covers the European railway infrastructure and the vehicles authorized to operate over it. It is a semantic/browsable representation of the RINF and ERATV application guides that were built by domain experts in the RINF and ERATV working parties. Since version 2.6.0, the ontology includes the routebook concepts described in appendix D2 \"Elements the infrastructure manager has to provide to the railway undertaking for the Route Book\" (https://eur-lex.europa.eu/eli/reg_impl/2019/773/oj) and the appendix D3 \"ERTMS trackside engineering information relevant to operation that the infrastructure manager shall provide to the railway undertaking\". @en
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MARC relators are defined as both RDF properties and SKOS concepts @en
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The DogOnt ontology supports device/network independent description of houses, including both controllable and architectural elements. @en
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EUPont is an ontology to model high level rules for Internet of Things End User Programming (IoT-EUP). @en
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Lemon: The lexicon model for ontologies is designed to allow for descriptions of lexical information regarding ontological elements and other RDF resources. Lemon covers mapping of lexical decomposition, phrase structure, syntax, variation, morphology, and lexicon-ontology mapping. @en
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An ontology for natural language terms description, including scripts, languages and meanings. The Lexvo.org ontology is still under development and may not be able to address all needs. Please also consider using the Lingvoj Ontology and the GOLD ontology, whereever appropriate. @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