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  • 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
  • uiot - Urban IoT Ontologies - Core Module
    http://www.w3id.org/urban-iot/core
    Core module of the suite of ontologies for urban IoT devices. @en
  • uiots - Urban IoT Ontologies - Sharing Mobility Module
    http://www.w3id.org/urban-iot/sharing
    Sharing Mobility module of the suite of ontologies for urban IoT devices. @en
  • solid - Solid terms
    http://www.w3.org/ns/solid/terms
    Solid terms @en
  • airs - Alliance of Information and Referral Services (AIRS) Vocabulary
    https://raw.githubusercontent.com/airs-linked-data/lov/latest/src/airs_vocabulary.ttl#
    The AIRS Linked Open Vocabulary is a way to describe human services information and referral (I&R) concepts. AIRS is the Alliance of Information and Referral Services (airs.org), which possesses over 1,000 member agencies primarily in the United States and Canada. The AIRS LOV is based on the AIRS XML Schema, available at: https://airs-xml.googlecode.com/hg/tags/3.1/airs.xsd @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
  • apco - African Public Contract Ontology
    https://purl.org/cm/onto/apco
    APCO is an ontology that allows the description of public procurement terms @en
  • saref - SAREF: the Smart Appliances REFerence ontology
    https://saref.etsi.org/core/
    The Smart Appliances REFerence (SAREF) ontology is a shared model of consensus that facilitates the matching of existing assets (standards/protocols/datamodels/etc.) in the smart appliances domain. The SAREF ontology provides building blocks that allow separation and recombination of different parts of the ontology depending on specific needs. @en
  • edifact-o - EDIFACT Ontology
    https://purl.org/edifact/ontology
    An Ontology for representing EDIFACT Messages. @en
  • pubsub - Eccenca Publish-Subscribe Vocabulary
    https://vocab.eccenca.com/pubsub/
    The eccenca Publish-Subscribe Vocabulary defines concepts and relations to create statements about publishers, subscribers and their subscriptions in a Publish-Subscribe environment based on the PubSubHubbub Core 0.4 specification. @en
  • s4ener - SAREF4EE: the EEbus/Energy@home extension of SAREF
    https://saref.etsi.org/saref4ener/
    This is the extension of SAREF for the EEBus and Energy@Home project. The documentation of SAREF4EE is available at http://ontology.tno.nl/SAREF4EE_Documentation_v0.1.pdf. SAREF4EE represents 1) The configuration information exchanged in the use case 'Remote Network Management' according to the EEBus Technical Report, Protocol Specification- Remote Network Management, version 1.0.0.2, 2015-09-19; 2) The scheduling information about power sequences exchanged in the use cases Appliance scheduling through CEM and remote start' and 'Automatic cycle rescheduling', according to the message structures described in General Message Structures, version 0.1.1, 2015-10-07; 3) The monitor and control information exchanged in the use case 'Communicate appliance status and info on manually planned cycles', according to the monitoring and control part of the Energy@Home Data Model, version 1.0; and 4) the event-based data exchanged in the use case 'Demand Response', according to General Message Structures, version 0.1.1, 2015-10-07. @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
  • arco - Core Ontology (ArCo network)
    https://w3id.org/arco/ontology/core
    The Core module represents general-purpose concepts orthogonal to the whole network, which are imported by all other ontology modules (e.g. part-whole relation, classification). @en
  • aeros - aerOS Continuum Ontology
    https://w3id.org/aerOS/continuum#
    Ontology for the orchestration of the aerOS continuum. @en