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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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The DBpedia ontology provides the classes and properties used in the DBpedia data set. @en
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LinkedGeoData ontology has been derived from concepts defined by Open Street Map @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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