91
results
-
AIRO represents AI risk concepts and relations based on the AI Act draft and ISO 31000 standard series. @en
-
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
-
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
-
The Denotative Description module encodes the characteristics of a cultural property, as detectable and/or detected during the cataloguing process and measurable according to a reference system. Examples include measurements e.g. length, constituting materials e.g. clay, employed techniques e.g. melting, conservation status e.g. good, decent, bad. In this module are used as template the following Ontology Design Patterns: - http://www.ontologydesignpatterns.org/cp/owl/collectionentity.owl - http://www.ontologydesignpatterns.org/cp/owl/classification.owl - http://www.ontologydesignpatterns.org/cp/owl/descriptionandsituation.owl - http://www.ontologydesignpatterns.org/cp/owl/situation.owl @en
-
A vocabulary to describe a person's profile and history @en
-
The ontology has been developed in the framework of the Dem@Care project for representing the experimentation protocol towards diagnostic support and assessment of Dementia in a controlled environment. The aim of the protocol is to provide a brief overview of their health status of the participants during consultation (cognition, behaviours and function), and to correlate the system (sensor) data with the data collected using typical dementia care assessment tools. @en
-
A Knowledge Model to describe a smart city, that interconnect data from infomobility service, Open Data and other source @en
-
This ontology describes a person character as a vector of demographic traits, each dimension refers to a concept contained within a specific taxonomy or to an instance of a wikidata item. @en
-
The Data Privacy Vocabulary (DPV) provides terms (classes and properties) to represent information about processing of personal data, for example - purposes, processing operations, personal data, technical and organisational measures. @en
-
Extension to the Data Privacy Vocabulary (DPV) providing additional categories of personal data @en
-
The ontology of agent relationships, AgRelOn, defines relations of persons to other persons and to organisations @en
-
The Cochrane Core ontology describes the entities and concepts that exist in the domain of evidence based healthcare. It is used for the construction of the Cochrane Linked Data Vocabulary containing some 400k terms including Interventions (Drugs, Procedures etc), Populations (Age, Sex, Condition), and clinical Outcomes. @en
-
The PICO ontology provides a machine accessible version of the PICO framework. It essentially provides a model for describing evidence in a consistent way. The model allows the specifying of complex populations, detailed interventions and their comparisons as well as the outcomes considered. The PICO ontology was originally designed to model the questions asked and answered in Cochrane's systematic reviews. As a leader in the field of evidence based healthcare Cochrane uses the PICO model when framing and publishing evidence based questions. The PICO model is widely adopted for describing healthcare evidence, furthermore is equally applicable in other evidence-based domains. It essentially provides a model for describing evidence in a consistent way. @en
-
The ontology of the taxonomy "European Skills, Competences, qualifications and Occupations". The ontology considers three ESCO pillars (or taxonomy) and 2 registers. The three pillars are: - Occupation - Skill (and competences) - Qualification For the construction and use of the ESCO pillars, the following modelling artefacts are used: - Facetting support to specialize ESCO pillar concepts based on bussiness relevant Concept Groups (e.g. species, languages, ...) - Conept Groups, Thesaurus array and Compound terms (as detailed in ISO 25964) to organize faceted concepts - SKOS mapping properties to relate ESCO pillar concepts to concepts in other (external) taxonomies (e.g. FoET, ISCO88 and ISCO08. More mappings can be added in the future.) - Tagging ESCO pillar concepts by other (external) taxonomies (NUTS, EQF, NACE, ...) - Capture gender specifics on the labels of the ESCO pillar concepts - Rich ESCO concept relationships holding a description and other specific characteristics of the relation between two ESCO pillar concepts. ESCO maintains two additional registers: - Awarding Body - Work Context Awarding Bodies typically are referenced by ESCO qualifications. Occupations can have one or more work context. @en
-
Ontology for public services and organizations @en