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  • gleif-elf - Entity Legal Form Ontology
    https://www.gleif.org/ontology/EntityLegalForm/
    Ontology defining concepts for Entity Legal Forms and their abbreviations by jurisdiction, based on ISO 20275. Though used by Global Legal Entity Identifier Foundation (GLEIF) for Legal Entity Identifier registration, it is more broadly applicable. @en
  • gleif-geo - Global Legal Entity Identifier Foundation Geocoding Ontology
    https://www.gleif.org/ontology/Geocoding/
    Ontology defining concepts for Geocoding of addresses. It is based on the geocoding used in the Global Legal Entity Identifier Foundation (GLEIF) Golden Copy Data, but is more broadly applicable. @en
  • sdm - SPARQL endpoint metadata
    https://w3id.org/vocab/sdm
    A small vocabulary for representing SPARQL endpoint metadata on the web @en
  • xbrll - A lightweight XBRL vocabulary
    https://w3id.org/vocab/xbrll
    An attempt to publish XBRL standard following best practices on the Web. Not an official version from XBRL International and under development @en
  • vpa - ERA ontology for verified permissions
    https://w3id.org/vpa
    ERA ontology for verified permissions, as applied in vehicle(type) authorisations, registrations and approvals @en
  • gleif-L1 - Global Legal Entity Identifier Foundation Level 1 Ontology - Who Is Who
    https://www.gleif.org/ontology/L1/
    Ontology for legal entity identifier registration. It was designed for Global Legal Entity Identifier Foundation (GLEIF) Level 1 data corresponding to the Common Data Format version 2.1. It covers key reference data for a legal entity identifiable with an LEI. The ISO 17442 standard developed by the International Organization for Standardization defines a set of attributes or LEI reference data that comprises the most essential elements of identification. It specifies the minimum reference data, which must be supplied for each LEI: The official name of the legal entity as recorded in the official registers. The registered address of that legal entity. The country of formation. The codes for the representation of names of countries and their subdivisions. The date of the first LEI assignment; the date of last update of the LEI information; and the date of expiry, if applicable. @en
  • gleif-L2 - Global Legal Entity Identifier Foundation Level 2 Ontology - Who Owns Whom
    https://www.gleif.org/ontology/L2/
    Ontology for legal entity parent relationships. It was designed for Global Legal Entity Identifier Foundation (GLEIF) Level 2 data corresponding to the Relationship Record format, version 1.1. Legal entities that have or acquire an LEI report their ‘direct accounting consolidating parent’ as well as their ‘ultimate accounting consolidating parent’, or for International Branches ‘is an International Branch of'. Otherwise they must provide a Reporting Exception. @en
  • gleif-base - Global Legal Entity Identifier Foundation Base Ontology
    https://www.gleif.org/ontology/Base/
    Ontology defining generic concepts for reuse by other Global Legal Entity Identifier Foundation (GLEIF) ontologies. It defines generic classes for (legal) Entities and their relationships and statuses; and generic properties for different types of name and address. It makes use of the OMG Languages Countries and Codes (LCC) ontology (based on the ISO 3166 standard) for country and region information. @en
  • server - YANG Server Ontology
    https://w3id.org/yang/server#
    Ontology that defines core concepts for representing YANG servers, including connection details and the available YANG datastores, along with operations for retrieving YANG data from a YANG server. The goal of this ontology is to enable the declarative and abstract of the interactions with YANG servers for monitoring and configuration purposes. In this sense, the ontology can become the basis for building a knowledge graph from YANG data obtained from YANG servers. @en
  • wfont - Wind Farm Ontology (wfont)
    https://w3id.org/wfont
    The Wind Farm Ontology (wfont) describes wind farms and their components. It is inspired by the SANDIA Report SAND2009-1171 and DAEKIN project outcomes. It reuses the AffectedBy and EEP (Execution-Executor-Procedure) ontology design patterns to discover sensors or actuators that observe or act on a given quality or feature of interest. @en
  • hw - Home Weather
    https://www.auto.tuwien.ac.at/downloads/thinkhome/ontology/WeatherOntology.owl
    Smart home ontology for weather phenomena and exterior conditions @en
  • rml-core
    http://w3id.org/rml/core
  • rml-fnml
    http://w3id.org/rml/fnml/
  • ws - An ontology for describing Workspaces.
    https://www.w3.org/ns/pim/space
    This ontology is for use in describing Workspaces. Workspaces are places where data is stored and associated policies of privacy. A given application typically stores information in several different workspaces, some being user private, some shared, and some public. it is crucial that the user has easy control over the destiny of information. @en
  • w3c-ssn - Semantic Sensor Network Ontology
    https://www.w3.org/ns/ssn
    This ontology describes sensors and observations, and related concepts. It does not describe domain concepts, time, locations, etc. as these are intended to be included from other ontologies via OWL imports. @en