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Defines aircraft models, aircraft systems / subsystems, and aircraft characteristics @en
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Vocabulary for machine-readable warranties and contracts, enabling complete automation of payment decisions and coverage assessment in after-sales service. @en
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A small ontology to model supply networks (supply chains) from all industries through products that are interlinked based on derivational dependencies. @en
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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
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This document describes functions which transform HTTP representations, i.e., the actual literal payloads of HTTP messages. @en
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APCO is an ontology that allows the description of public procurement terms @en
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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
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An Ontology for representing EDIFACT Messages. @en
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SAREF4INMA is an extension of SAREF for the industry and manufacturing domain. SAREF4INMA focuses on extending SAREF for the industry and manufacturing domain to solve the lack of interoperability between various types of production equipment that produce items in a factory and, once outside the factory, between different organizations in the value chain to uniquely track back the produced items to the corresponding production equipment, batches, material and precise time in which they were manufactured. SAREF4INMA is specified and published by ETSI in the TS 103 410-5 associated to this ontology file. SAREF4INMA was created to be aligned with related initiatives in the smart industry and manufacturing domain in terms of modelling and standardization, such as the Reference Architecture Model for Industry 4.0 (RAMI), which combines several standards used by the various national initiatives in Europe that support digitalization in manufacturing. The full list of use cases, standards and requirements that guided the creation of SAREF4INMA are described in the associated ETSI TR 103 507. @en
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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
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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
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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
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The Internet of Things taxonomy is extended with semantic ontologies for IoT layers, containing classes, properties, individuals, and rules specific to IoT technologies, tools, and applications @en
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OntoGSN is an ontology for managing assurance cases in the Goal Structuring Notation (GSN). The goal of the ontology is to help users in linking the elements of their cases - claims and evidence - with the internationalized resource identifiers (IRIs) of represented concepts, events and data, and in evaluating the validity of their argument. @en
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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