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  • situ - Situation Pattern
    http://www.ontologydesignpatterns.org/cp/owl/situation.owl
    A pattern to represent contexts or situations, and the things that are contextualized. @en
  • tis - Time Indexed Situation
    http://www.ontologydesignpatterns.org/cp/owl/timeindexedsituation.owl
    A generic pattern usable for all situations that require a temporal indexing. @en
  • np - Nano publication ontology
    http://www.nanopub.org/nschema
    The nanopub ontology @en
  • tisc - Open Time and Space Core Vocabulary
    http://www.observedchange.com/tisc/ns#
    TISC, the Open Time and Space Core Vocabulary, is a lightweight spatiotemporal vocabulary aiming to provide spatial and temporal terms such as "happensAt", "locatedAt", "rightOf" to enable practitioners to relate their data to time and space. @en
  • sealit - SeaLiT Ontology
    http://www.sealitproject.eu/ontology/
    The SeaLiT Ontology is a formal ontology intended to facilitate the integration, mediation and interchange of heterogeneous information related to maritime history. It aims at providing the semantic definitions needed to transform disparate, localised information sources of maritime history into a coherent global resource. It also serves as a common language for domain experts and IT developers to formulate requirements and to agree on system functionalities with respect to the correct handling of historical information. The ontology uses and extends the CIDOC Conceptual Reference Model (ISO 21127:2014), in particular version 7.1.1, as a general ontology of human activity, things and events happening in space and time. @en
  • opmw - The OPMW Ontology
    http://www.opmw.org/ontology/
    OPMW is a OPMV profile to model the executions and definitions of scientific workflows. @en
  • msr - Measurement Ontology
    http://www.telegraphis.net/ontology/measurement/measurement#
    The Measurement Ontology is an ontology in which measurements may be rendered @en
  • mls - Machine Learning Schema
    http://www.w3.org/ns/mls
    ML-Schema is a collaborative, community effort with a mission to develop, maintain, and promote standard schemas for data mining and machine learning algorithms, datasets, and experiments @en
  • ssn - Semantic Sensor Network Ontology
    http://www.w3.org/ns/ssn/
    This ontology describes sensors, actuators and observations, and related concepts. It does not describe domain concepts, time, locations, etc. these are intended to be included from other ontologies via OWL imports. @en
  • tfo - Transformation Functions Ontology
    https://privatealpha.com/ontology/transformation/1#
    This document describes functions which transform HTTP representations, i.e., the actual literal payloads of HTTP messages. @en
  • ce - CityExplorer Ontology
    https://purl.org/cityexplorer
    This ontology models personalized tourist experiences by representing cities, points of interest, events, accommodations, restaurants, transportation, and their relationships. This ontology is part of a university project. @en
  • edifact-o - EDIFACT Ontology
    https://purl.org/edifact/ontology
    An Ontology for representing EDIFACT Messages. @en
  • cem - Crime Event Model (CEM)
    https://w3id.org/CEMontology
    The Crime Event Model is an ontology for the representation of crime events extracted from local newspapers. It could be employed for Crime Analysis purposes: extracting crime information from newspapers and enriching them with proper machine-readable semantics is a critical task to help law enforcement agencies at preventing crime, supporting criminal investigations and evaluating the action of law enforcement agencies themselves. The model is based on the fundamental 5W1H journalistic questions, that are Who?, What?, When?, Where?, Why? and How?. Another important requirement was the attempt to exploit existing knowledge graphs and ontologies such as the Simple Event Model (SEM) Ontology and the Schema.org data model for interoperability and interconnection. @en
  • hht - Historical Hierarchical Territories
    https://w3id.org/HHT
    The notion of territory plays a major role in human and social sciences. In an historical context, most approaches are irrelevant as they rely on geometric data, which is not available. In order to represent historical territories,we conceived the HHT ontology (Hierarchical Historical Territory) to represent hierarchical historical territorial divisions, without having to know their geometry. This approach relies on a notion of building blocks to replace polygonal geometry @en
  • cevent - Cultural Event Ontology (ArCo network)
    https://w3id.org/arco/ontology/cultural-event
    The Cultural Event module models cultural events, i.e. events involving cultural properties. @en