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  • A ontology developed for telecommunciation network systems with hybrid technologies, e.g., WiFi, LiFi, LTE, 2G/3G, optical, etc. @en
  • The TripleAccessControl Ontology is an extension to WebAccessControl Ontology to describe access control rules for RDF triples. @en
  • hRESTS is a vocabulary for describing RESTful Web services @en
  • Defines the element of Authorization and its essential properties, and also some classes of access such as read and write. @en
  • WSMO-Lite is a lightweight approach to the semantic annotation of Web service descriptions, defined by the STI2 working group Conceptual Models for Services @en
  • An ontology to model accountability of AI systems which use machine learning. @en
  • ## 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
  • The BDI Ontology provides a formal framework to model the Belief-Desire-Intention (BDI) architecture for rational agents. It defines key mental states—Beliefs, Desires, and Intentions—and their relationships, capturing the agent’s reasoning, motivation, and commitment to action. Supporting classes include Propositions (content of mental states), Justifications (rationale for mental states), Plans (action sequences for goals), and TimeIntervals (temporal validity of entities). Key properties like hasBelief, hasDesire, and hasIntention link agents to mental states, while fulfills, adoptsIntention, and motivatesDesire model dynamic interactions. Temporal properties enable reasoning about time-sensitive states and plans. Axioms ensure consistency, such as disjointness between mental states and domain-specific constraints. This ontology supports reasoning, querying, and analysis of agent behaviour, enabling applications in AI, multi-agent systems, and decision support. @en
  • 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
  • This is a helper ontology for NIF 2.0 to be able to log errors and warning messages. @en
  • 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
  • An ontology to create privacy preferences for Linked Data @en
  • An ontology to represent the content management systems and their interaction with the triplestore. @en
  • An ontology to model accountability of generic systems. @en
  • The AtomOWL ontology is inspired from the work done by the atom working group. This ontology is working off the rfc 4287 published among othe places at http://www.atompub.org/rfc4287.html . The AtomOWL ontology uses as much as possible the same terms as the format there to make the relation easy to understand. The AtomOWL name space is slightly different from the atom namespace [see post http://www.imc.org/atom-syntax/mail-archive/msg16476.html]. But this is a good thing as it helps distinguish the ontology from the rfc 4287 serialisation. @en