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  • vartrans - Lexicon Model for Ontologies - Vartrans
    http://www.w3.org/ns/lemon/vartrans
    A model for the representation of lexical information relative to ontologies. Variation and translation module. @en
  • oso - Observatories of the Seas Ontology (OSO)
    http://www.w3.org/ns/prov-o
    Ontology describing the relationships between Regional Facilities, Sites, Platforms, Research Infrastructures, Organisations, Cruises, and the persons in charge of each level. @en
  • ui - A user interface ontology
    http://www.w3.org/ns/ui
    An ontology suitable for describing forms, sequences in widgets @en
  • decision - Decision ontology
    https://decision-ontology.googlecode.com/svn/trunk/decision.owl
    Decision-making is a process that can result in some decision and decision is a situation of indicating one of the considered options. Decision Ontology provides means for precise distinguishing and distinct treatment of these two aspects. @en
  • ce - CityExplorer Ontology
    https://purl.org/cityexplorer
    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
  • cem - Crime Event Model (CEM)
    https://w3id.org/CEMontology
    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
  • tax - EUTaxO - EUdaphobase Taxonomy Ontology
    https://w3id.org/EUTaxO
    EUdaphobase Taxonomy Ontology for the European Soil-Biology Data Warehouse for Soil Protection @en
  • hht - Historical Hierarchical Territories
    https://w3id.org/HHT
    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
  • cevent - Cultural Event Ontology (ArCo network)
    https://w3id.org/arco/ontology/cultural-event
    The Cultural Event module models cultural events, i.e. events involving cultural properties. @en
  • aeros - aerOS Continuum Ontology
    https://w3id.org/aerOS/continuum#
    Ontology for the orchestration of the aerOS continuum. @en
  • dg - DINGO Ontology
    https://w3id.org/dingo/
    The DINGO ontology (Data Integration for Grant Ontology) defines the terms of the DINGO vocabulary and provides a machine readable extensible framework to model data relative to projects, funding, project and funding actors, and, notably, funding policies. It is designed to yield high modeling power and elasticity to cope with the huge variety in funding and project practices, which makes it applicable to many areas where funding is an important aspect: first of all research, but also the arts, cultural conservation, and many others. @en
  • foo - Forest Observatory Ontology (FOO)
    https://w3id.org/def/foo#
    This ontology describes wildlife observations generated by sensors. @en
  • bdi - Belief-Desire-Intention Ontology
    https://w3id.org/fossr/ontology/bdi/
    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
  • iadopt - I-ADOPT Framework ontology
    https://w3id.org/iadopt/ont
    The I-ADOPT Framework ontology @en
  • iddo - The Interconnected Data Dictionary Ontology (IDDO)
    https://w3id.org/iddo
    The interconnected data dictionary ontology maps the data model of the ISO 23386 for the describing, creating, and maintenance of properties in interconnected data dictionaries. @en