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  • 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
  • rma - Verisav RMA / Ticketing Vocabulary
    https://ns.verisav.fr/rma#
    Vocabulary for Return Merchandise Authorization (RMA) and service ticket management, standardizing communication between consumers, retailers, and repairers. @en
  • dpp - Verisav Digital Product Passport Vocabulary
    https://ns.verisav.fr/dpp#
    Vocabulary for Digital Product Passports (DPP) managing product lifecycle, warranties, repairs, and compliance with EU regulations (ESPR EU 2024/1781). Aligned with GS1 Digital Link standards, including GTIN, GLN, granularity (model/batch/serial) and compound identifier support. @en
  • eqp - Aircraft Equipment Vocabulary
    https://data.nasa.gov/ontologies/atmonto/equipment#
    Defines aircraft models, aircraft systems / subsystems, and aircraft characteristics @en
  • wty - Verisav Warranty & Contracts Vocabulary
    https://ns.verisav.fr/wty#
    Vocabulary for machine-readable warranties and contracts, enabling complete automation of payment decisions and coverage assessment in after-sales service. @en
  • psn - Product Supply Network Vocabulary
    https://purl.org/psn/vocab#
    A small ontology to model supply networks (supply chains) from all industries through products that are interlinked based on derivational dependencies. @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
  • 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
  • s4inma - SAREF4INMA: an extension of SAREF for the industry and manufacturing domain
    https://saref.etsi.org/saref4inma/
    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
  • 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
  • IIoT - Ontology for Industrial Internet of Things systems
    https://w3id.org/IIoT
    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
  • gsn - OntoGSN
    https://w3id.org/OntoGSN/ontology
    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
  • cmd - Compound Measure Description
    https://w3id.org/cmd#
    This document is a vocabulary to describe compound measures, i.e. measures with several metric or item that are organized with serveral dimensions. The description of such a measure relies on a Tree-Structure of Requirement (TSoR): a set of requirements structured hierarchicaly with analysis element. A TSoR represents the main measure. Several information may be added to explicitely indicate how the overall score on the measure should be calculated based on the hierarchy, relative importance of the node of the hierarchy and an aggregation function. The measure can be described completely and unambiguously from the organisation to the requirements and the implementation. @en
  • cdc - CDC: Construction Dataset Context ontology
    https://w3id.org/cdc
    The Construction Dataset Context (CDC) ontology is an extension of DCAT v2.0, a W3C Recommendation ontology for describing (RDF and non-RDF) datasets published on the Web. Using this extension, it becomes possible to describe a context for construction-related datasets that are being distributed using Web technology as well as datasets that are not shared outside an organization such as local copies, work in progress and other datasets that remain internal. This dataset metadata encompasses the temporal context (period or snapshot), the type of content of the dataset (as-built, design, etc.) and relations between contextualized datasets (previous as-built, requirements related to a design, etc.). In addition, this DCAT extension also provides terminology for managing dataset distributions that are scoped to a certain (named or default) graph of an RDF file or quadstore. @en