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arco - Core Ontology (ArCo network) https://w3id.org/arco/ontology/core The Core module represents general-purpose concepts orthogonal to the whole network, which are imported by all other ontology modules (e.g. part-whole relation, classification). @en -
cdesc - Context Description Ontology (ArCo network) https://w3id.org/arco/ontology/context-description The Context Description module includes models for the context of a cultural property, in a broad sense: agents (e.g.: author, collector, copyright holder), objects (e.g.: inventories, bibliography, protective measures, other cultural properties, collections etc.), activities (e.g.: surveys, conservation interventions), situations (e.g.: commission, coin issuance, estimate, legal situation) related, involved or involving the cultural property. Thus it represents attributes that do not result from a measurement of features in a cultural property, but are associated with it. @en -
pd - Personal Data Categories https://w3id.org/dpv/pd Extension to the Data Privacy Vocabulary (DPV) providing additional categories of personal data @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 -
pghdprovo - Patient Generated Health Data Provenance Ontology https://w3id.org/pghdprovo Patient Generated Health Data (PGHD) refer to health data collected by patient or their relatives. This ontology seeks to capture information about the data, the provenance and data quality associated with PGHD shared with an EHR. @en -
foio - The SEAS Feature of Interest ontology. https://w3id.org/seas/FeatureOfInterestOntology 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 -
seasbo - The SEAS Building Ontology https://w3id.org/seas/BuildingOntology The SEAS Building ontology describes a taxonomy of buildings, building spaces, and rooms. Some categorizations are based on the energy efficiency related to their insulation etc., although the actual values for classes depend the country specific regulations and geographical locations. Other categorizations are based on occupancy and activities. There is no single accepted categorization available. This taxonomy uses some types selected from: - International building occupancy based categories (USA) - The Classification of Types of Constructions (EU) - Finnish building categorization VTJ2000 (Finland) - Wikipedia category page for Rooms: https://en.wikipedia.org/wiki/Category:Rooms @en -
pko - Procedural Knowledge Ontology (PKO) https://w3id.org/pko The Procedural Knowledge Ontology (PKO) addresses the Procedural Knowledge (PK) domain, and models procedures, their executions, and related resources and agents. @en -
sulo - Simplified Upper Level Ontology https://w3id.org/sulo/sulo/ The Simplified Upper Level Ontology (SULO) is ontology with a minimal set of classes and relations to guide the development of a personal health knowledge graph. @en -
modsci - ModSci, Modern Science Ontology. https://w3id.org/skgo/modsci# ModSci is a reference ontology for modelling different types of modern sciences and related entities, such as scientific discoveries, renowned scientists, instruments, phenomena ... etc. @en -
seo - The Scientific Events Ontology https://w3id.org/seo The vocabulary allows for the description of data about scientific events such as conferences, symposiums and workshops. @en -
usability - Usability https://w3id.org/usability Ontology 'Usability' created to describe and store information about interactions of user with a software user interface @en -
vair - Vocabulary of AI Risks https://w3id.org/vair VAIR is a taxonomy of AI and risk concepts. @en -
gleif-repex - Global Legal Entity Identifier Foundation Reporting Exception Ontology https://www.gleif.org/ontology/ReportingException/ Ontology for representing exceptions to reporting of parents, for entities registered with a Legal Entity Identifier. The Global Legal Identifier System (GLEIS) requires that legal entities with an LEI provide information on their ultimate and direct accounting consolidating parents. Relationship reporting is mandatory with exceptions allowed for certain well-defined reasons. This ontology provides a simple structure for recording reasons for each exception by LEI. @en -
yoga - Yoga Ontology https://yogaontology.org/ontology/ Yoga Ontology is the list of vocabularies that define the yogic practice. Where Yoga is the union of the mind and body. @en