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  • omg - OMG: Ontology for Managing Geometry
    https://w3id.org/omg
    The Ontology for Managing Geometry (OMG) is an ontology for describing geometry descriptions of objects. It provides means to support the application of multiple geometry descriptions of the same object as well as the description of the geometry evolution over time. The OMG is based the concepts introduced in the Ontology for Property Management (OPM) ontology. This ontology was created within the research project SCOPE, funded by the German Federal Ministry for Economic Affairs and Energy (BMWi). The initial version of the ontology (v0.0.1) is documented in: Wagner, Anna, Bonduel, Mathias, Pauwels, Pieter & Rüppel, Uwe(2019). Relating Geometry Descroptions to its Derivatives on the Web. In Proceedings of the European Conference on Computing in Construction (EC3 2019). Chania, Greece. @en
  • ontouml - OntoUML Metamodel Vocabulary
    https://w3id.org/ontouml
    A reference implementation of the OntoUML metamodel in OWL. @en
  • ocmv - OntoUML/UFO Catalog Metadata Vocabulary
    https://w3id.org/ontouml-models/vocabulary
    Specification of the metadata used to describe models in the OntoUML/UFO Catalog. @en
  • sdont - The Software Description Ontology
    https://w3id.org/okn/o/sd
    An ontology for describing software and their links to inputs, outputs and variables. The ontology extends schema.org and codemeta vocabularies @en
  • okh - Open Know How (OKH) ontology
    https://w3id.org/oseg/ont/okh
    Used for indexing, searching and comparing Open Source Hardware projects @en
  • nno - The Neural Network Ontology
    https://w3id.org/nno/ontology
    This is the Neural Network Ontology. Designed by the AIFB (http://www.aifb.kit.edu/web/Web_Science) @en
  • pep - Process Execution ontology.
    https://w3id.org/pep/
    The process execution ontology is a proposal for a simple extension of both the [W3C Semantic Sensor Network](https://www.w3.org/TR/vocab-ssn/) and the [Semantic Actuator Network](https://www.irit.fr/recherches/MELODI/ontologies/SAN.owl) ontology cores. @en
  • pghdprovo - Patient Generated Health Data Provenance Ontology
    https://w3id.org/pghdprovo
    Patient Generated Health Data (PGHD) refer to health data collected by patient or their relatives. This ontology seeks to capture information about the data, the provenance and data quality associated with PGHD shared with an EHR. @en
  • seas-stats - The SEAS Statistics ontology.
    https://w3id.org/seas/StatisticsOntology
    This ontology defines common evaluation interpretation concepts for statistics. @en
  • seas-eval - The SEAS Evaluation ontology
    https://w3id.org/seas/EvaluationOntology
    The Evaluation ontology describes evaluation of [`seas:Property`ies](https://w3id.org/seas/Property). There may be: - direct evaluations, or - qualified evaluations. @en
  • rbdoc - RiverBench documentation ontology
    https://w3id.org/riverbench/schema/documentation
    Ontology with metadata needed to generate documentation of datasets, distributions, profiles, etc. in RiverBench @en
  • rb - RiverBench metadata ontology
    https://w3id.org/riverbench/schema/metadata
    Ontology for describing datasets and profiles in the RiverBench benchmark suite. @en
  • rains - The RAInS Ontology
    https://w3id.org/rains
    An ontology to model accountability of AI systems which use machine learning. @en
  • pko - Procedural Knowledge Ontology (PKO)
    https://w3id.org/pko
    The Procedural Knowledge Ontology (PKO) addresses the Procedural Knowledge (PK) domain, and models procedures, their executions, and related resources and agents. @en
  • 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