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This term list includes all currently valid terms that have been defined in the core Audubon Core namespace ac:. @en
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ADMS is a profile of DCAT, used to describe semantic assets (or just 'Assets'), defined as highly reusable metadata (e.g. xml schemata, generic data models) and reference data (e.g. code lists, taxonomies, dictionaries, vocabularies) that are used for eGovernment system development. @en
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The AGLS Metadata Terms Namespace provides URIs for the AGLS Metadata Terms Vocabulary in the context of AGLS Metadata Standard, a set of metadata properties and associated usage guidelines to improve the visibility, manageability and interoperability of online information and services. Vocabulary terms are declared using RDF Schema language to support RDF applications. It will be updated according to AGLS Working Group decisions. @en
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Metadata vocabularies are used in various domains of study. It provides an in-depth description of the resources. In this work, we develop Algorithm Metadata Vocabulary (AMV), a vocabulary for capturing and storing the metadata about the algorithms (a procedure or a set of rules that is followed step-by-step to solve a problem, especially by a computer). The snag faced by the researchers in the current time is the failure of getting relevant results when searching for algorithms in any search engine. AMV is represented as a semantic model and produced OWL file, which can be directly used by anyone interested to create and publish algorithm metadata as a knowledge graph, or to provide metadata service through SPARQL endpoint. To design the vocabulary, we propose a well-defined methodology, which considers real issues faced by the algorithm users and the practitioners. The evaluation shows a promising result. @en
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A metadata vocabulary for describing comic books and comic book collections. @en
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The Creative Commons Rights Expression Language (CC REL) lets you describe copyright licenses in RDF @en
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CHAMEO is a domain ontology designed to model the common aspects across the different characterisation techniques and methodologies. @en
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This vocabulary defines a number of concepts peculiar to content strategy which are not accounted for by other vocabularies. @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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OWL pattern for describing activity models as abstract dependencies among classes. @en
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DBpedia Data ID is an ontology with the goal of describing LOD datasets via RDF files in a uniform way. Established vocabularies like DCAT, VoID, Prov-O and SPARQL Service Description are used for maximum compatibility. @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 DNB RDF Vocabulary (dnb:) is a collection of classes, properties and datatypes used within the DNB's linked data service.It complements the GND Ontology (gndo:) which is specifically geared towards authority data from the Integrated Authority File (GND), whereas this vocabulary is more general-purpose. @en
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The data.gov.au Dataset Ontology is an OWL ontology designed to describe the characteristics of datasets published on data.gov.au. The ontology contains elements which describe the publication, update, origin, governance, spatial and temporal coverage and other contextual information about the dataset. The ontology also covers aspects of organisational custodianship and governance. By using this ontology to describe datasets on data.gov.au publishers increase discoverability and enable the consumption of this information in other applications/systems as Linked Data. It further enables decentralised publishing of catalogs and facilitates federated dataset search across sites, e.g. in datasets that are published by the States. Other publishers of Linked Data may make assertions about data published using this ontology, e.g. they may publish information about the use of the dataset in other applications. @en