148
results
  • iadopt- I-ADOPT Framework ontology
    https://w3id.org/iadopt/ont
    The I-ADOPT Framework ontology @en
  • ctrl- CTRLont - An ontology to formally specify the control domain
    https://w3id.org/ibp/CTRLont
    CTRLont specifies concepts and relationships of control actors on a high level @en
  • ids- IDS Information Model
    https://w3id.org/idsa/core
    This ontology defines classes and properties for describing participants, infrastructure, data and services of the International Data Spaces (formerly known as Industrial Data Space). @en
  • authn_provider- Authentication Provider
    https://w3id.org/inrupt/namespace/vocab/authn_provider/
    Information about authentication providers which might be identity providers or other services such as ones providing JSON Web Tokens. @en
  • ifc- IFC4_ADD1
    https://w3id.org/ifc/IFC4_ADD1
    OWL ontology for the IFC conceptual data schema and exchange file format for Building Information Model (BIM) data @en
  • otl- The Open Traffic Lights ontology
    https://w3id.org/opentrafficlights
    This ontology provides the terms necessary to describe the status of traffic lights. @en
  • opm- OPM: Ontology for Property Management
    https://w3id.org/opm
    The Ontology for Property Management (OPM) extends the concepts introduced in the Smart Energy Aware Systems (SEAS) Evaluations ontology. @en
  • opti- Offshore Wind Power Platform Ontology for OPTiMAR
    https://w3id.org/optimar
    This ontology describes the components, failures, sensors, and events related to offshore wind platforms. @en
  • noria- The NORIA Ontology
    https://w3id.org/noria/ontology/
    The NORIA-O project is a data model for IT networks, events and operations information. The ontology is developed using web technologies (e.g. RDF, OWL, SKOS) and is intended as a structure for realizing an IT Service Management (ITSM) Knowledge Graph (KG) for Anomaly Detection (AD) and Risk Management applications. The model has been developed in collaboration with operational teams, and in connection with third parties linked vocabularies. Alignment with third parties vocabularies is implemented on a per class or per property basis when relevant (e.g. with `rdfs:subClassOf`, `owl:equivalentClass`). Directions for direct instanciation of these vocabularies are provided for cases where implementing a class/property alignment is redundant. Alignment holds for the following vocabulary releases: - [BBO](https://hal.archives-ouvertes.fr/hal-02365012/) 1.0.0 - [BOT](https://w3id.org/bot/) 0.3.2 - [DevOps-Infra](https://oeg-upm.github.io/devops-infra/) 1.0.0 - [FOLIO](https://github.com/IBCNServices/Folio-Ontology) 1.0.0 - [ORG](https://www.w3.org/TR/vocab-org/) 0.8 - [PEP](https://w3id.org/pep/) 1.1 - [SEAS](https://w3id.org/seas/) 1.1 - [SLOGERT](https://sepses.ifs.tuwien.ac.at/ns/log/index-en.html) 1.1.0 - [UCO](https://github.com/ucoProject/uco) Release-0.8.0 @en
  • ofo- Occupant Feedback Ontology
    https://w3id.org/ofo#
    The aim of the Occupant Feedback Ontology is to semantically describe passive and active occupant feedback and to enable integration of this feedback with linked building data. @en
  • seasd- The SEAS Device ontology
    https://w3id.org/seas/DeviceOntology
    The SEAS Device ontology defines `seas:Device` as physical system that are designed to execute one or more procedures that involve the physical world. @en
  • seasfo- The SEAS Forecasting ontology
    https://w3id.org/seas/ForecastingOntology
    The SEAS Forecasting ontology extends the [Procedure Execution ontology (PEP)](https://w3id.org/pep/) @en
  • peco- The Provenance of Emission Calculations Ontology
    https://w3id.org/peco
    This ontology defines a vocabulary for describing provenance traces of carbon emission calculations by capturing the quantifiable measurements of carbon emission sources used by some activities (e.g., electricity used by a machinery to produce a product, petrol used to make a car journey, etc.) and emission conversion factors used to estimate the carbon emissions produced by these. In addition, the ontology provides the ability to capture various data transformations that occurred before energy estimates may be used with relevant conversion factors. For example, sensors may provide raw readings about a water flow of an irrigation rig in an agri-food operation which is then used as a proxy to estimate the total volume of fertilisers used. @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
  • rdfp- The RDF Presentation ontology
    https://w3id.org/rdfp/
    ## RDF Presentation and RDF Presentation Negotiation An RDF graph can be presented in several ways, using different media types. Examples of RDF media types include `application/rdf+xml`, `text/turtle`, `application/json+ld`. Today, most of the content consumed/produced/published, on the Web is not presented in RDF. In the Web of Things, HTTP servers and clients would rather exchange lightweight documents, potentially binary. Currently, most existing RDF Presentations generically apply to any RDF graph, at the cost of being heavy text-based documents. Yet, lightweight HTTP servers/clients could be better satisfied with consuming/producing/publishing lightweight documents, may its structure be application-specific. @en