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An Ontology for Consumer Electronics Products and Services @en
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The Building Concrete Monitoring Ontology (BCOM) is defined for capturing information of concrete work, concrete curing and testing of concrete properties. Further Information on the development and usage of the Ontology can be found in the following publication: Liu et al. (2021): An ontology integrating as-built information for infrastructure asset management using BIM and semantic web. In: Proceedings of 2021 European Conference on Computing in Construction, Online eConference, URL: https://ec-3.org/publications/conferences/2021/paper/?id=167 @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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The Construction Dataset Context (CDC) ontology is an extension of DCAT v2.0, a W3C Recommendation ontology for describing (RDF and non-RDF) datasets published on the Web. Using this extension, it becomes possible to describe a context for construction-related datasets that are being distributed using Web technology as well as datasets that are not shared outside an organization such as local copies, work in progress and other datasets that remain internal. This dataset metadata encompasses the temporal context (period or snapshot), the type of content of the dataset (as-built, design, etc.) and relations between contextualized datasets (previous as-built, requirements related to a design, etc.). In addition, this DCAT extension also provides terminology for managing dataset distributions that are scoped to a certain (named or default) graph of an RDF file or quadstore. @en
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An ontology containing additional terminology for structuring and annotating RDFS/OWL taxonomies for describing constructions (components, materials, spatial zones, damages, construction tasks and properties). It also functions as an index for known taxonomies starting from root classes and properties. @en
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The Construction Tasks Ontology (CTO) describes tasks operating on construction elements, spatial zones and/or damages. The tasks are either planned or executed depending on the dataset metadata context of the dataset its used in. Five different types of tasks are defined: instalment, removal, modification, repair and inspection. Consequences of tasks on the dataset, i.e. added and/or deleted triples, are modeled using reified statements. The tasks can link to a reified statement using the CTO relations. @en
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Ontology that defines the topology of damages in constructions. @en
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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
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An ontology that describes the management of the traffic in a straight road with two lanes, both in the same direction. @en
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SAREF4INMA is an extension of SAREF for the industry and manufacturing domain. SAREF4INMA focuses on extending SAREF for the industry and manufacturing domain to solve the lack of interoperability between various types of production equipment that produce items in a factory and, once outside the factory, between different organizations in the value chain to uniquely track back the produced items to the corresponding production equipment, batches, material and precise time in which they were manufactured. SAREF4INMA is specified and published by ETSI in the TS 103 410-5 associated to this ontology file. SAREF4INMA was created to be aligned with related initiatives in the smart industry and manufacturing domain in terms of modelling and standardization, such as the Reference Architecture Model for Industry 4.0 (RAMI), which combines several standards used by the various national initiatives in Europe that support digitalization in manufacturing. The full list of use cases, standards and requirements that guided the creation of SAREF4INMA are described in the associated ETSI TR 103 507. @en
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Ontology for Cloud Computing Instances. Instance are classes of VM that comprise varying combinations of CPU, memory, storage, and networking capacity. This ontology allows to define the instantiation model of MVs used in large cloud computing providers such as Amazon, Azure, etc. @en
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Simple and direct pricing ontology for Cloud Computing Services. This ontology allows to define model of prices used in large cloud computing providers such as Amazon, Azure, etc., including options for regions, type of instances, prices specification, etc. @en
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Ontology for the definition of regions and zones of availability on CloudComputing platforms and services. This ontology allows to define model of regions used in large cloud computing providers such as Amazon, Azure, etc. @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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This ontology defines concepts related to federation of internet infrastructures. @en