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swemls - Semantic-Web Machine Learning System (SWeMLS) Ontology https://w3id.org/semsys/ns/swemls An ontology to describe a Semantic-Web Machine Learning System (SWeMLS) @en -
stax - RDF Stream Taxonomy (RDF-STaX) https://w3id.org/stax/ontology RDF-STaX is an OWL 2 DL ontology that enables describing the types of RDF streams and defines relations between them. @en -
tido - The Threat Intelligence Decision Ontology https://w3id.org/tido# The TIDO ontology can be used to describe the decision processes within the threat intelligence domain @en -
seo - The Scientific Events Ontology https://w3id.org/seo The vocabulary allows for the description of data about scientific events such as conferences, symposiums and workshops. @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 -
usability - Usability https://w3id.org/usability Ontology 'Usability' created to describe and store information about interactions of user with a software user interface @en -
tree - TREE https://w3id.org/tree A hypermedia specification for fragmenting collections. @en -
tribont - TribOnt ontology https://w3id.org/tribont The goal is to represent the tribological experiments by relaying on the representation included in the core,, sample and equipment modules. @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-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 -
vair - Vocabulary of AI Risks https://w3id.org/vair VAIR is a taxonomy of AI and risk concepts. @en -
gleif-repex - Global Legal Entity Identifier Foundation Reporting Exception Ontology https://www.gleif.org/ontology/ReportingException/ Ontology for representing exceptions to reporting of parents, for entities registered with a Legal Entity Identifier. The Global Legal Identifier System (GLEIS) requires that legal entities with an LEI provide information on their ultimate and direct accounting consolidating parents. Relationship reporting is mandatory with exceptions allowed for certain well-defined reasons. This ontology provides a simple structure for recording reasons for each exception by LEI. @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 -
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