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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
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Information about authentication providers which might be identity providers or other services such as ones providing JSON Web Tokens. @en
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The ISO Property (ISOProps) ontology maps the data model of the ISO 23386 for the describing, creating, and maintenance of properties in interconnected data dictionaries. The namespace for ISOProps terms is [https://w3id.org/isoprops](https://w3id.org/isoprops) The preferred prefix for the ISOProps namespace is `isoprops`. ## Ontology Overview  ## Assigning an ISOProps Property to a Feature of Interest  ## Relation between DCAT vocabulary and the ISOProps ontology  @en
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An ontology for metadata about legal texts represented using the LegalHTML format @en
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The Level of Information Need (LOIN) Ontology is defined for specifying information requirements for delivery of data in a buildings' life cycle. The LOIN ontology is based on the standard BS EN 17412-1 (2020). Furthermore, it is extended with vocabulary for connecing Information Delivery Specifications (IDS) and Information containers for linked document delivery (ICDD) as per ISO 21597-1 (2020). @en
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INTRO is an ontology for the fields of literary studies, art studies and intermediality studies for the representation of intertextual, interpictorial, and intermedial relations. It enables the presentation and categorization of diverse features of both textual and pictorial origin and their linking. Its subject area includes the scholarly discourse on these texts/images, interrelations, and features, insofar as research results are also understood as texts with features and relations. @en
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This is the provenance module of Materials Design Ontology. @en
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Metadata for Ontology Description and publication @en
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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
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An ontology for describing software and their links to inputs, outputs and variables. The ontology extends schema.org and codemeta vocabularies @en
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A reference implementation of the OntoUML metamodel in OWL. @en
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Specification of the metadata used to describe models in the OntoUML/UFO Catalog. @en
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An ontology to model accountability of AI systems which use machine learning. @en
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## 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
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Ontology with metadata needed to generate documentation of datasets, distributions, profiles, etc. in RiverBench @en