85
results
-
Defines specific air traffic management concepts used in aircraft navigation through the US National Airspace System @en
-
Defines concepts related to the structure of the US National Airspace System (NAS) @en
-
Defines aircraft models, aircraft systems / subsystems, and aircraft characteristics @en
-
This ontology models personalized tourist experiences by representing cities, points of interest, events, accommodations, restaurants, transportation, and their relationships. This ontology is part of a university project. @en
-
The eccenca Publish-Subscribe Vocabulary defines concepts and relations to create statements about publishers, subscribers and their subscriptions in a Publish-Subscribe environment based on the PubSubHubbub Core 0.4 specification. @en
-
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
-
The notion of territory plays a major role in human and social sciences. In an historical context, most approaches are irrelevant as they rely on geometric data, which is not available. In order to represent historical territories,we conceived the HHT ontology (Hierarchical Historical Territory) to represent hierarchical historical territorial divisions, without having to know their geometry. This approach relies on a notion of building blocks to replace polygonal geometry @en
-
The Cultural Event module models cultural events, i.e. events involving cultural properties. @en
-
To ensure comparability between schemas from different data models, the Description of a Data Source (DSD) vocabulary has been developed. @en
-
The DNS Security Ontology (DSecO) project is a data model for representing and reasoning on Domain Name System (DNS) data. The ontology is developed using web technologies (e.g. RDF, OWL, SKOS) and is intended as a structure for realizing a DNS Knowledge Graph (KG) for administration and security assessment 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: - [ORG](https://www.w3.org/TR/vocab-org/) 0.8 - [UCO](https://github.com/ucoProject/uco) Release-0.8.0 @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
-
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
-
Information about authentication providers which might be identity providers or other services such as ones providing JSON Web Tokens. @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 ontology defines feature of interest and their properties, as an extension of the core classes of the SSN ontology (https://www.w3.org/ns/ssn/). A feature of interest is an abstraction of a real world phenomena (thing, person, event, etc). A feature of interest is then defined in terms of its properties, which are qualifiable, quantifiable, observable or operable qualities of the feature of interest. Alignments to other ontologies are proposed in external documents: - [SSNAlignment](https://w3id.org/seas/SSNAlignment) proposes an alignment to the [SSN ontology](http://www.w3.org/ns/ssn/). - [QUDTAlignment](https://w3id.org/seas/QUDTAlignment) proposes an alignment to the [QUDT ontology](http://qudt.org/). @en