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An ontology to model accountability of AI systems which use machine learning. @en
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The Procedural Knowledge Ontology (PKO) addresses the Procedural Knowledge (PK) domain, and models procedures, their executions, and related resources and agents. @en
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An ontology to describe a Semantic-Web Machine Learning System (SWeMLS) @en
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The TIDO ontology can be used to describe the decision processes within the threat intelligence domain @en
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A vocabulary specifying concepts and structures needed to represent different data cubes needed for the Smart Readiness Indicator. @en
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The goal of this module is to represent the sample systems , and the undelaying samples, involved in the tribological experiments. @en
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A hypermedia specification for fragmenting collections. @en
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The goal is to represent the tribological experiments by relaying on the representation included in the core,, sample and equipment modules. @en
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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
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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
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The goal of this module is to represent the equipment hierarchy model involved in the tribological experiments. @en
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VAIR is a taxonomy of AI and risk concepts. @en
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The Gouda Time Machine Ontology describes the geo-temporal classes and properties used within the Gouda Time Machine. @en
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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
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ERA ontology for verified permissions, as applied in vehicle(type) authorisations, registrations and approvals @en