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A metadata vocabulary for describing comic books and comic book collections. @en
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The EUropean Research Information Ontology (EURIO) conceptualises, formally encodes and makes available in an open, structured and machine-readable format data about resarch projects funded by the EU's framework programmes for research and innovation. @en
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R4R is a light-weight ontology for representing general relationships of resource for publication and reusing. It asserts that a certain reusing context occurred and determined by its two basic relations, namely, isPackagedWith and isCitedBy. The isPackagedWith relation declares the resource is ready to be reused by incorporating License and Provenance information. The Cites relation is an exceptional to isCitedBy which occurs only two related objects cite each other at the same time. Five resource objects including article, data, code, provenance and license are major class concepts to represent in this ontology. The namespace for all R4R terms is http://guava.iis.sinica.edu.tw/r4r/ @en
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MARC relators are defined as both RDF properties and SKOS concepts @en
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An ontology for natural language terms description, including scripts, languages and meanings. The Lexvo.org ontology is still under development and may not be able to address all needs. Please also consider using the Lingvoj Ontology and the GOLD ontology, whereever appropriate. @en
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An OWL vocabulary to include and exploit probabilistic information in SHACL validation reports @en
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An OWL vocabulary for describing uncertainty metadata. @en
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The Open Provenance Model is a model of provenance that is designed to meet the following requirements: (1) To allow provenance information to be exchanged between systems, by means of a compatibility layer based on a shared provenance model. (2) To allow developers to build and share tools that operate on such a provenance model. (3) To define provenance in a precise, technology-agnostic manner. (4) To support a digital representation of provenance for any 'thing', whether produced by computer systems or not. (5) To allow multiple levels of description to coexist. (6) To define a core set of rules that identify the valid inferences that can be made on provenance representation. @en
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The NLP Interchange Format (NIF) is an RDF/OWL-based format that aims to achieve interoperability between Natural Language Processing (NLP) tools, language resources and annotations. @en
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This document specifies a vocabulary for asserting the existence of official endorsements or certifications of agents, such as people and organizations. @en
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This ontology is a reduced-in-scope version of the [W3C Decisions and Decision-Making Incubator Group](https://www.w3.org/2005/Incubator/decision/)'s Decision Ontology (DO) which can be found at <https://github.com/nicholascar/decision-o>. It has been re-worked to align entirely with the W3C's [PROV ontology](https://www.w3.org/TR/prov-o/) since it is widely recognised that analysing the elements of decisions *post hoc* is an exercise in provenance. Unlike the original DO, this ontology cannot be used for *normative* scenarios: it is only capable of recording decisions that have already been made (so-called *data-driven* use in the DO). This is because PROV, to which this ontology is completely mapped, does not have a templating system which can indicate what *should* occur in future scenarios. This ontology introduces only one new element for decision modelling over that which was present in the DO: an Agent which allows agency in decision making to be recorded. @en
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The Dublin Core Metadata Element Set is a vocabulary of fifteen properties for use in resource description. The name "Dublin" is due to its origin at a 1995 invitational workshop in Dublin, Ohio; "core" because its elements are broad and generic, usable for describing a wide range of resources. @en
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an up-to-date specification of all metadata terms maintained by the Dublin Core Metadata Initiative, including properties, vocabulary encoding schemes, syntax encoding schemes, and classes. @en
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The Data Quality Management Vocabulary - An Ontology for Data Requirements Management, Data Quality Monitoring, Data Quality Assessment, and Data Cleansing @en
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Vocabulary to include sample codes in a schema. Can work with XSLT (http://purl.org/net/ns/ns-schema.xsl) to present schema as XHTML list with examples. @en