78
results
-
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 Knowledge Model to describe a smart city, that interconnect data from infomobility service, Open Data and other source @en
-
Extension to the Data Privacy Vocabulary (DPV) providing additional categories of personal data @en
-
The SeaLiT Ontology is a formal ontology intended to facilitate the integration, mediation and interchange of heterogeneous information related to maritime history. It aims at providing the semantic definitions needed to transform disparate, localised information sources of maritime history into a coherent global resource. It also serves as a common language for domain experts and IT developers to formulate requirements and to agree on system functionalities with respect to the correct handling of historical information. The ontology uses and extends the CIDOC Conceptual Reference Model (ISO 21127:2014), in particular version 7.1.1, as a general ontology of human activity, things and events happening in space and time. @en
-
The ReSIST Courseware Ontology represents the various educational courses and resources within the ReSIST project @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
-
This is the human and machine readable Vocabulary/Ontology governed by the European Union Agency for Railways. It represents the concepts and relationships linked to the sectorial legal framework and the use cases under the Agency´s remit. Currently, this vocabulary covers the European railway infrastructure and the vehicles authorized to operate over it. It is a semantic/browsable representation of the RINF and ERATV application guides that were built by domain experts in the RINF and ERATV working parties. Since version 2.6.0, the ontology includes the routebook concepts described in appendix D2 \"Elements the infrastructure manager has to provide to the railway undertaking for the Route Book\" (https://eur-lex.europa.eu/eli/reg_impl/2019/773/oj) and the appendix D3 \"ERTMS trackside engineering information relevant to operation that the infrastructure manager shall provide to the railway undertaking\". @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
-
The EUropean Research Information Ontology (EURIO) conceptualises, formally encodes and makes available in an open, structured and machine-readable format data about resarch projects funded by the EU's framework programmes for research and innovation. @en
-
Ontology for public services and organizations @en
-
Open 311 Ontology This ontology generalizes the concepts that appear in 311 open data files published by several cities (Toronto, New York, Chicago, Vancouver) across North America. It provides a generis representation of 311 data that other cities can map their data onto and be used as a means of achieving interoperability. @en
-
This ontology defines concepts related to federation of internet infrastructures. @en
-
The Project Documents Ontology models the inherent structure and concepts of various documents in a project-specific setting, like meeting minutes, status reports etc. @en
-
This ontology is a translation of the General Transit Feed Specification towards URIs. Its intended use is creating an exchange platform where the Linked GTFS model can be used as a start to get the right data into the right format. @en