Linked Open Vocabularies

This vocabulary describes the entities which may be derived from a URI and the relationships between them, such as Internet Domains, prototcols, file suffixes etc. It was initially issued as part of an April 1st gag, but has utility beyond the initial joke. @en

summa- SUMMA Vocabulary

http://purl.org/voc/summa/

The SUMMA Vocabulary enables to request and represent summarized RDf resources. It should be used in context to the SUMMA API definition. @en

xapi- xAPI Controlled Vocabulary Ontology

http://purl.org/xapi/ontology#

This ontology contains a list of the classes and properties that can be used when for creating and publishing a controlled vocabulary dataset for xAPI communities of practice. @en

rsctx- Recommender System Context

http://softeng.polito.it/rsctx

This ontology represent context which may be interesting in providing recommendations to users. @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

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

rains- The RAInS Ontology

https://w3id.org/rains

An ontology to model accountability of AI systems which use machine learning. @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

saont- The System Accountability Ontology

https://w3id.org/sao

An ontology to model accountability of generic systems. @en

stax- RDF Stream Taxonomy (RDF-STaX)

https://w3id.org/stax/ontology

RDF-STaX is an OWL 2 DL ontology that enables describing the types of RDF streams and defines relations between them. @en

server- YANG Server Ontology

https://w3id.org/yang/server#

Ontology that defines core concepts for representing YANG servers, including connection details and the available YANG datastores, along with operations for retrieving YANG data from a YANG server. The goal of this ontology is to enable the declarative and abstract of the interactions with YANG servers for monitoring and configuration purposes. In this sense, the ontology can become the basis for building a knowledge graph from YANG data obtained from YANG servers. @en

ws- An ontology for describing Workspaces.

https://www.w3.org/ns/pim/space

This ontology is for use in describing Workspaces. Workspaces are places where data is stored and associated policies of privacy. A given application typically stores information in several different workspaces, some being user private, some shared, and some public. it is crucial that the user has easy control over the destiny of information. @en