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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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This ontology describes terms concerning companies, their cross-border movements within the European Union (EU), and associated EU company legislation. @en
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A model for the representation of lexical information relative to ontologies. Variation and translation module. @en
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The Building Topology Ontology (BOT) is a simple ontology defining the core concepts of a building. It is a simple, easy to extend ontology for the construction industry to document and exchange building data on the web. Changes since version 0.2.0 of the ontology are documented in: https://w3id.org/bot/bot.html#changes The version 0.2.0 of the ontology is documented in: Mads Holten Rasmussen, Pieter Pauwels, Maxime Lefrançois, Georg Ferdinand Schneider, Christian Anker Hviid and Jan Karlshøj (2017) Recent changes in the Building Topology Ontology, 5th Linked Data in Architecture and Construction Workshop (LDAC2017), November 13-15, 2017, Dijon, France, https://www.researchgate.net/publication/320631574_Recent_changes_in_the_Building_Topology_Ontology The initial version 0.1.0 of the ontology was documented in: Mads Holten Rasmussen, Pieter Pauwels, Christian Anker Hviid and Jan Karlshøj (2017) Proposing a Central AEC Ontology That Allows for Domain Specific Extensions, Lean and Computing in Construction Congress (LC3): Volume I – Proceedings of the Joint Conference on Computing in Construction (JC3), July 4-7, 2017, Heraklion, Greece, pp. 237-244 https://doi.org/10.24928/JC3-2017/0153 @en
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A model for the representation of lexical information relative to ontologies. Core module. @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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NiceTag Ontology is an ontology which describes as generally as possible tags or rather tag actions understood as a speech acts occurring on the Web @en
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Arpenteur ontology is dedicated to photogrammetry, archeology and oceanology communities in order to perform tasks such as image processing, photogrammetry and modelling. @en
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This vocabulary defines temporal entities such as time intervals, their properties and relationships. @en
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LIME (LInguistic MEtadata) is a vocabulary for expressing linguistic metadata about linguistic resources and linguistically grounded datasets. @en
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Vocabulary for describing organizational structures, specializable to a broad variety of types of organization. @en
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A model for the representation of lexical information relative to ontologies. Syntax and semantics module. @en
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An ontology for using languages as resources @en
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A model for the representation of lexical information relative to ontologies. Decomposition module. @en
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The euBusinessGraph (`ebg:`) ontology represents companies, type/status/economic classification, addresses, identifiers, company officers (e.g., directors and CEOs), and dataset offerings. It uses `schema:domainIncludes/rangeIncludes` (which are polymorphic) to describe which properties are applicable to a class, rather than `rdfs:domain/range` (which are monomorphic) to prescribe what classes must be applied to each node using a property. We find that this enables more flexible reuse and combination of different ontologies. We reuse the following ontologies and nomenclatures, and extend them where appropriate with classes and properties: - W3C Org, W3C RegOrg (basic company data), - W3C Time (officer membership), - W3C Locn (addresses), - schema.org (domain/rangeIncludes and various properties) - DBpedia ontology (jurisdiction) - NGEO and Spatial (NUTS administrative divisions) - ADMS (identifiers), - FOAF, SIOC (blog posts), - RAMON, SKOS (NACE economic classifications and various nomenclatures), - VOID (dataset descriptions). This is only a reference. See more detail in the [EBG Semantic Model](https://docs.google.com/document/d/1dhMOTlIOC6dOK_jksJRX0CB-GIRoiYY6fWtCnZArUhU/edit) google document, which includes an informative description of classes and properties, gives examples and data provider rules, and provides more schema and instance diagrams. @en
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