The Gouda Time Machine Ontology describes the geo-temporal classes and properties used within the Gouda Time Machine. @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
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-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
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
Smart home ontology for weather phenomena and exterior conditions @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
mso-em- MSO-EM: Ontologies for modelling, simulation, optimization (MSO) and epistemic metadata (EM)
https://www.purl.org/mso-em
MSO-EM is a system of ontologies for documenting the knowledge status of models and data; the aim is to make models and data explainable-AI-ready (XAIR). @en
sur- The Survey Ontology
https://www.w3id.org/survey-ontology
Ontology for surveys based on the Coney data model. @en