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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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domOS Common Ontology (dCO) represents a common information model to share a unified understanding for humans and machines and to ensure semantic interoperability in a heterogeneous IoT infrastructure. This ontology allows the decoupling of the infrastructure from the software services and applications. @en
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Ontology that defines the topology of damages in constructions. @en
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The general purpose of this ontology is to provide a library of high level concepts that are used by the other modules within the whole OS Topographic ontology. The ontology also describes the relationships and instances common to more than one module. @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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IoT-O is a core domain Internet of Things ontology. It is intended to model horizontal knowledge about IoT systems and applications, and to be extended with vertical, application specific knowledge. It is constituted of different modules : - A sensing module, based on W3C's SSN (http://purl.oclc.org/NET/ssnx/ssn) - An acting module, based on SAN (http://www.irit.fr/recherches/MELODI/ontologies/SAN) - A service module, based on MSM (http://iserve.kmi.open.ac.uk/ns/msm/msm-2014-09-03.rdf) and hRest (http://www.wsmo.org/ns/hrests) - A lifecycle module, based on a lifecycle vocabulary (http://vocab.org/lifecycle/schema-20080603.rdf) and an iot-specific extension (http://www.irit.fr/recherches/MELODI/ontologies/IoT-Lifecycle) - An energy module, based on powerOnt (ttp://elite.polito.it/ontologies/poweront.owl) IoT-O developping team also contributes to the oneM2M IoT interoperability standard. @en
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The OntoMedia Space representation denotes areas of landscape. Expands on the AKT location ontology @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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An ontology describing the administrative divisions in France. @en
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Codes for describing coordinates reference systems consistently with ISO TC/211. French translations of terms and definitions are mainly taken from the multilingual glossary of ISO/TC 211 available online: http://www.isotc211.org/Terminology.htm @en