Linked Open Vocabularies

ccp - Vocabulary for prices options in Cloud Computing Services

http://cookingbigdata.com/linkeddata/ccpricing

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

ccr - Vocabulary for Regions and Zones on Cloud Computing

http://cookingbigdata.com/linkeddata/ccregions

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

ccsla - Service Level Agreement for Cloud Computing

http://cookingbigdata.com/linkeddata/ccsla

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

cci - Ontology for Cloud Computing instances

http://cookingbigdata.com/linkeddata/ccinstances

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

ebg - euBusinessGraph ontology

http://data.businessgraph.io/ontology#

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

esco - The ESCO ontology

http://data.europa.eu/esco/model

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

pni - SNaP Identifier Ontology

http://data.press.net/ontology/identifier/

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

li - OWL representation of ISO 19115 (Geographic Information - Metadata - Lineage package)

http://def.seegrid.csiro.au/isotc211/iso19115/2003/lineage

An OWL representation of parts of the Geographic Metadata model described in ISO 19115:2003 with Corrigendum 2006 - LI Package @en

r4r - Relations for Reusing (R4R) Ontology

http://guava.iis.sinica.edu.tw/r4r

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

kgc - KGRC Ontology

http://kgc.knowledge-graph.jp/ontology/kgc.owl

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

trao - Transport Administration Ontology

http://linkeddata.finki.ukim.mk/lod/ontology/tao#

Transport Administration Ontology (TAO) for describing data from Swedish Transport Administration Web site. @en

veo - Vehicle Emissions Ontology

http://linkeddata.finki.ukim.mk/lod/ontology/veo#

An ontology for describing vehicles and their emissions. @en

kees - KEES Ontology

http://linkeddata.center/kees/v1

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

lsq - The Linked SPARQL Queries Vocabulary (LSQ(V))

http://lsq.aksw.org/vocab

The Linked SPARQL Queries Vocabulary (LSQ(V)), defined using RDF(S) and OWL, provides a machine readable vocabulary to help describe queries in SPARQL logs and their statistics. The vocabulary builds upon the SPIN vocabulary and the Service Description vocabulary. @en

cfrl - Corporate Financial Reports and Loans Ontology

http://linkeddata.finki.ukim.mk/lod/ontology/cfrl#

The Corporate Financial Reports and Loans Ontology (CFRL). @en

Patterns?:	type name both
Flatten?:	yes no

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