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The Internet of Construction Ontology (IoC) construction process ontology is intended to represent a comprehensive solution of how processes in the construction industry can be modelled. Due to the iterative nature of creating an ontology, the construction process ontology presented here can at best be considered a working state at the time of publication. Our approach emphasizes the simplest and most comprehensive mapping possible, which is only extended based on insights from practical use when otherwise compelling limitations in usability and applicability arise. Thus, the extension and refinement of the developed construction process ontology strongly depends on the integration of further areas of the construction value chain and the connection of further domain ontologies. @en
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The Data Template (DT) Ontology is based on concepts and principles for creating templates from ISO 23387 and the associated XML data schema, which is currently under development. @en
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This ontology, called VIR, is an extension of CIDOC-CRM created to sustain propositions on the nature of visual elements and permit these descriptions to be published on the Web. With the term visual element, we refer to those signs identified in the visual space as distinct and documentable units, and subject to an analytical interpretation. The scope of this ontology is to s to provide a framework to support the identification, annotation and interconnections between diverse visual elements and presents and assist their documentation and retrieval. Specifically, the model aims to clarify the identity and the relation of these visual signs, providing the necessary classes to characterise their constituent elements, reference, symbolic content and source of interpretation. VIR expands on key entities and properties from CIDOC-CRM, introducing new classes and relationships responding to the visual and art historical community, specifically building up on the iconographical tradition. The result is a model which differentiates between interpretation and element identified, providing a clear distinction between denotation and signification of an element. As a consequence of such distinction, the ontology allows for the definition of diverse denotative criteria for the same representation, which could change based on traditions and perspective. Visual objects can be, in fact, polysemic and ambiguous, and it is not so easy to pin down a denotative or connotative meaning because they are very much context-dependent. @en
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The system ontology of Wikibase @en
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The AKT Reference Ontology has been designed to support the AKT-2 demonstrator ("AKTive Portal"), and subsequent activities @en
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An ontology to address the Research Management of the CRUE's Spanish University System (Sistema Universitario Español) by applying an encompassing model not only capable of addressing the universities of the CRUE but also more belonging to the European Union. @en
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The Data Knowledge Vocabulary allows for a comprehensive description of data assets and enterprise data management. It covers a business data dictionary, data quality management, data governance, the technical infrastructure and many other aspects of enterprise data management. The vocabulary represents a linked data implementation of the Data Knowledge Model which resulted from extensive applied research. @en
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Combined with the EBU Class Conceptual Data Model (CCDM) of simple business objects, EBUCore provides the appropriate framework for descriptive and technical metadata for use in Service Oriented Architectures and also in audiovisual ontologies for semantic web and linked data developments. @en
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Marl is a standardised data schema designed to annotate and describe subjective opinions expressed on the web or in particular Information Systems. @en
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Onyx is a vovabulary designed designed to annotate and describe the emotions expressed by user-generated content on the web or in particular Information Systems. @en
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The Vagueness Ontology (VO) allows one to specify vagueness characterisations of the TBox entities of an ontology. @en
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The ECLAP vocabulary provide classes and properties for the description of multimedia content related with performing arts. @en
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This ontology is intended to describe Semantic Actuator Networks, as a counterpoint to SSN definition of Semantic Sensor Networks. An actuator is a physical device having an effect on the world (see Actuator for more information). It is worth noticing that some concepts are imported from SSN, but not SSN as a whole. This is a design choice intended to separate as much as possible the definition on actuator from the definition of sensor, which are completely different concept that can be used independantly from each other. This ontology is used as a ontological module in IoT-O ontology. @en
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The Open NEE Configuration Model defines a Linked Data-based model for describing a configuration supported by a Named Entity Extraction (NEE) service. It is based on the model proposed in "Configuring Named Entity Extraction through Real-Time Exploitation of Linked Data" (http://dl.acm.org/citation.cfm?doid=2611040.2611085) for configuring such services, and allows a NEE service to describe and publish as Linked Data its entity mining capabilities, but also to be dynamically configured. @en
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Intended to represent sequence schemas. It defines the notion of transitive and intransitive precedence and their inverses. It can then be used between tasks, processes, time intervals, spatially locate objects, situations, etc. @en