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The Patch Request Ontology provides a schema to describe desired changes in Linked Data. By wrapping the Graph Update Ontology (guo) patch requests can be formulated to add, modify or delete particular triples (or subgraphs) within a dataset. @en
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The GoodRelations ontology provides the vocabulary for annotating e-commerce offerings (1) to sell, lease, repair, dispose, or maintain commodity products and (2) to provide commodity services. @en
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Quality metrics can be (in principle) calculated on various forms of data (such as datasets, graphs, set of triples etc...). This vocabulary allow the owner/user of such RDF data to calculate metrics on multiple (and different) resources. @en
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The FIESTA-IoT ontology takes inspiration from the well-known Noy et al. methodology for reusing and interconnecting existing ontologies. To build the ontology, we leverage a number of core concepts from various mainstream ontologies and taxonomies, such as Semantic Sensor Network (SSN), M3-lite (a lite version of M3 ontology), WGS84, IoT-lite, Time, and DUL ontology. @en
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This is the Hydrogen Ontology (HOLY). HOLY is a domain ontology for describing the complex structure of hydrogen-based markets. HOLY contributes to the systemic modeling of the hydrogen domain with a focus on its value chain. Hence, it provides a foundation for retrieval, storage, and delivery of market insights. @en
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Ontology for healthcare metadata - especially metadata found in DICOM files (Digital Imaging and Communications in Medicine, see http://dicom.nema.org/). Author: Michael Brunnbauer, Bonubase GmbH (www.bonubase.com). The author's email address is brunni@netestate.de. See http://purl.org/healthcarevocab/v1help for explanations. @en
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Under this name space new properties and classes needed for the lobid.org service are defined . Already existing properties and classes which are (re)used in lobid.org aren't documented here. @en
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In order to enable and encourage the sharing, distribution, syndication, and aggregation of media content, the authors propose the Media RDF vocabulary, an open standard for distributed media metadata. @en
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The Modular and Unified Tagging Ontology (MUTO) is an ontology for tagging and folksonomies. It is based on a thorough review of earlier tagging ontologies and unifies core concepts in one consistent schema. It supports different forms of tagging, such as common, semantic, group, private, and automatic tagging, and is easily extensible. @en
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The objective of gUFO is to provide a lightweight implementation of the Unified Foundational Ontology (UFO) [1-5] suitable for Semantic Web OWL 2 DL applications. Intended users are those implementing UFO-based lightweight ontologies that reuse gUFO by specializing and instantiating its elements. There are three implications of the use of the term lightweight. First of all, we have employed little expressive means in an effort to retain computational properties for the resulting OWL ontology. Second, we have selected a subset of UFO-A [1, 2] and UFO-B [3] to include here. In particular, there is minimalistic support for UFO-B (only that which is necessary to establish the participation of objects in events and to capture historical dependence between events). Third, a lightweight ontology, differently from a reference ontology, is designed with the purpose of providing an implementation artifact to structure a knowledge base (or knowledge graph). This has driven a number of pragmatic implementation choices which are discussed in comments annotated to the various elements of this implementation. The 'g' in gUFO stands for gentle. At the same time, "gufo" is the Italian word for "owl". For the source repository, see: <https://github.com/nemo-ufes/gufo> @en
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This vocabulary allows multi-dimensional data, such as statistics, to be published in RDF. @en
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This vocabulary extends the data cube vocabulary to support publication of statistical data in RDF, using an information model based on SDMX @en
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Defines subclasses and instances of codes used in SDMX, such as currencies, decimals, frequencies ... @en
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A Vocabulary for Incorporating Predictive Models into the Linked Data Web @en
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The General Ontology for Linguistic Description (GOLD) was created primarily for applications involving descriptive linguistics. @en