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This ontology aims to model generic Medical Data Acquisition Instruments, which can be interoperable across different clinical data management systems. The ontology is developed in the context of the MedRed project (https://www.hevs.ch/en/rad-institutes/institute-of-information-systems/projects/medical-research-data-acquisition-platform-14092) @en
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The ontology is applied to an application to compute the touristic paths in the city of Saragossa. @en
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RiC-O (Records in Contexts-Ontology) is an OWL ontology for describing archival record resources. As the second part of Records in Contexts standard, it is a formal representation of Records in Contexts Conceptual Model (RiC-CM). The current official version is <html:strong>v0.2</html:strong>; it is compliant with RiC-CM v0.2 full draft, that will be published in February or March 2021, and that is slightly different from <html:a href="https://www.ica.org/sites/default/files/ric-cm-0.2_preview.pdf">RiC-CM v0.2 preview, that was published in December 2019. RiC-O provides a generic vocabulary and formal rules for creating RDF datasets (or generating them from existing archival metadata) that describe in a consistent way any kind of archival record resource. It can support publishing RDF datasets as Linked Data, querying them using SPARQL, and making inferences using the logic of the ontology. @en
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This ontology aims to model RDF streams, their metadata, and access endpoints for publishing and consuming these streams @en
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The Description of a Project (DOAP) vocabulary, described using W3C RDF Schema and the Web Ontology Language. @en
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Lemon: The lexicon model for ontologies is designed to allow for descriptions of lexical information regarding ontological elements and other RDF resources. Lemon covers mapping of lexical decomposition, phrase structure, syntax, variation, morphology, and lexicon-ontology mapping. @en
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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
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The VAS ontological model enables the semantic integration of the heterogeneous observations used in ASOTVAS project ( https://robotica.uv.es/proyectos/ASOTVAS/ ), including ground measurements, UAV acquisitions and satellite products. Built as an extension of the W3C SOSA ontology (Janowicz et al., 2018), it incorporates a domain-specific vocabulary tailored to the needs of the Valencia Anchor Station as a CEOS LPV supersite. The model provides additional classes and properties to represent, in a homogeneous way, the different observational platforms: field sensors installed at VAS stations, UAVs equipped with multispectral cameras, and satellite missions such as Sentinel-2 and Sentinel-3. All observations follow a common SOSA pattern and share the same structure for results, units and timestamps. By aligning field, UAV and satellite observations under a unified semantic framework, the VAS ontology supports interoperable data access, consistent representation across scales, and integrated analysis of the multi-source measurements collected in ASOTVAS. @en
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