Linked Open Vocabularies

The goal is to represent the tribological experiments by relaying on the representation included in the core,, sample and equipment modules. @en

tribont-core- Core module

https://w3id.org/tribont/core

The goal of this module is to represent the common classes, and object and data properties included in two or more modules of the TribOnt ontology. @en

tribont-equipment- Equipment module

https://w3id.org/tribont/equipment

The goal of this module is to represent the equipment hierarchy model involved in the tribological experiments. @en

tribont-material- Material module

https://w3id.org/tribont/material

The goal of this module is to represent the materials that can be involved in the tribological experiments as part of the tested samples. @en

tribont-sample- Sample module

https://w3id.org/tribont/sample

The goal of this module is to represent the sample systems , and the undelaying samples, involved in the tribological experiments. @en

vair- Vocabulary of AI Risks

https://w3id.org/vair

VAIR is a taxonomy of AI and risk concepts. @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

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

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

jsonsc- JSON Schema in RDF

https://www.w3.org/2019/wot/json-schema#

Module for data schema specifications, part of the W3C Web of Things (WoT) Thing Description model @en

wotsec- Security mechanisms for the Web of Things

https://www.w3.org/2019/wot/security#

Security mechanisms for the the Web of Thing @en

td- Thing Description Ontology

https://www.w3.org/2019/wot/td

This ontology aims to model the Web of Things domain according to the W3C Interest Group (http://w3c.github.io/wot/) @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

sur- The Survey Ontology

https://www.w3id.org/survey-ontology

Ontology for surveys based on the Coney data model. @en