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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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CiteDCAT-AP is an extension of the DCAT application profile for data portals in Europe (DCAT-AP) for describing resources documented by using the DataCite metadata schema - the de facto standard for data citation, and used across scientific disciplines. Its basic use case is to make research data searchable on general data portals, thereby bridging the gap between scientific and public sector information. For this purpose, CiteDCAT-AP provides an RDF vocabulary and the corresponding RDF syntax binding for the metadata elements defined in DataCite. @en
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This document is a vocabulary to describe compound measures, i.e. measures with several metric or item that are organized with serveral dimensions. The description of such a measure relies on a Tree-Structure of Requirement (TSoR): a set of requirements structured hierarchicaly with analysis element. A TSoR represents the main measure. Several information may be added to explicitely indicate how the overall score on the measure should be calculated based on the hierarchy, relative importance of the node of the hierarchy and an aggregation function. The measure can be described completely and unambiguously from the organisation to the requirements and the implementation. @en
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The scope of the DIO is the domain of design intent or design rationale that needs to be documented while undertaking the design of any artifact @en
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OPMW is a OPMV profile to model the executions and definitions of scientific workflows. @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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This ontology models the Food domain. It allows to describe ingredients and food products. Ontology used by the Open Food Facts dataset @en
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A vocabulary for representing statistical data on the Web. Note :The SCOVO vocabulary is deprecated. We strongly advise to use the Data Cube Vocabulary instead. @en
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A small vocabulary for describing whisky varieties @en
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Vocabulary to describe the response to a incident by emergency services. This is NOT intended to describe the incident itself, it describes the response @en
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The Vocabulary for Ranking (vRank) is an RDF Schema vocabulary for materializing ranking computations. @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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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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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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The Counter Ontology specification provides basic concepts and properties for describing a general counter concept and some important sub counters @en