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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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The PropBank module of the PreMOn ontology extends the core module for representing concepts specific to PropBank. @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 VerbNet module of the PreMOn ontology extends the core module with classes and properties specific to the VerbNet predicate model. The modelling is based on the VerbNet Annotation Guidelines. @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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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 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 General Ontology for Linguistic Description (GOLD) was created primarily for applications involving descriptive linguistics. @en
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This vocabulary aims at providing interoperability between SKOS and ISO 25964 ‐ 1:2011, the new standard for thesauri @en
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OLiA Annotation Model for Uby Parts of Speech (Gurevych et al, 2012) extracted from the Uby DTD (http://purl.org/olia/ubyCat.owl, version of Nov 21th, 2012). References Iryna Gurevych, Judith Eckle-Kohler, Silvana Hartmann, Michael Matuschek, Christian M. Meyer and Christian Wirth, 2012, Uby - A Large-Scale Unified Lexical-Semantic Resource, Proceedings of the 13th Conference of the European Chapter of the Association for Computational Linguistics (EACL 2012), Avignon, France. The DTD is made available under a Creative Commons Attribution-ShareAlike 3.0 Unported (CC BY-SA 3.0) license which is available at http://creativecommons.org/licenses/by-sa/3.0/ You are free to share (copy, distribute and transmit) the work, to develop your own extensions (adapt, remix) of the work, and to make commercial use of the work. @en
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OPMV, the Open Provenance Model Vocabulary, provides terms to enable practitioners of data publishing to publish their data responsibly. @en
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The Provenance Vocabulary Core Ontology provides the main classes and properties required to describe provenance of data on the Web. @en
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Extends the Provenance Vocabulary by defining subclasses of the types of provenance elements introduced in the core ontology. @en