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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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An ontology to describe competences and human capabilities @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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A vocabulary for the Social and Solidarity Economy (SSE). This vocabulary is designed to be used in combination with the metadata schemes/vocabularies/ontologies: dcterms, good relations, foaf, vcard, organization and schema.org - this is defined in the Dublin Core Application Profile of the SSE. Developed by the ESSGlobal group of the Intercontinental Network for Promoting the Social and Solidarity Economy (RIPESS) Organisation. @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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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
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This vocabulary provides supplementary terms for organisations wishing to publish open data about themselves. @en
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This version of the OSLO Exchange Standard provides a minimum set of classes and properties for describing a natural person, i.e. the individual as opposed to any role they may play in society or the relationships they have to other people, organisations and property; all of which contribute significantly to the broader concept of identity. The vocabulary is closely integrated with the Person, Organisation and Location Vocabularies published by the W3C in the Gov Linked Data Project. The OSLO specification is the result of a public-private partnership initiated by V-ICT-OR, the Flemish Organization for ICT in Local Government. @en
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PAV is a lightweight ontology for tracking Provenance, Authoring and Versioning. PAV specializes the W3C provenance ontology PROV-O in order to describe authorship, curation and digital creation of online resources. @en
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The participation ontology is a simple model for describing the roles that people play within groups. It is intended that specific domains will create subclasses of roles within their own areas of expertise. @en
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This vocabulary defines a set of terms for describing changes to resource descriptions. @en
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The Muninn Military Ontology marks up information about military people, organizations and events. @en