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A vocabulary to represent relations that should be more transparent, usually between powerfull people or institutions @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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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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This ontology describes a person character as a vector of demographic traits, each dimension refers to a concept contained within a specific taxonomy or to an instance of a wikidata item. @en
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The Data Privacy Vocabulary (DPV) provides terms (classes and properties) to represent information about processing of personal data, for example - purposes, processing operations, personal data, technical and organisational measures. @en
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Extension to the Data Privacy Vocabulary (DPV) providing additional categories of personal data @en
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An ontology that represents concepts in the legal domain. @en
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An ontology for describing changes between OWL ontology versions @en
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The Geometry Metadata Ontology contains terminology to Coordinate Systems (CS), length units and other metadata (file size, software of origin, etc.). GOM is designed to be at least compatible with OMG (Ontology for Managing Geometry) and FOG (File Ontology for Geometry formats), and their related graph patterns. In addition, GOM provides terminology for some experimental data structures to manage (marked as vs:term_status = unstable): * transformed geometry (e.g. a prototype door geometry that is reused for all doors of this type). This is closely related to the transformation of Coordinate Systems @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 is the provenance module of Materials Design Ontology. @en
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INTRO is an ontology for the fields of literary studies, art studies and intermediality studies for the representation of intertextual, interpictorial, and intermedial relations. It enables the presentation and categorization of diverse features of both textual and pictorial origin and their linking. Its subject area includes the scholarly discourse on these texts/images, interrelations, and features, insofar as research results are also understood as texts with features and relations. @en
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The ISO Property (ISOProps) ontology maps the data model of the ISO 23386 for the describing, creating, and maintenance of properties in interconnected data dictionaries. The namespace for ISOProps terms is [https://w3id.org/isoprops](https://w3id.org/isoprops) The preferred prefix for the ISOProps namespace is `isoprops`. ## Ontology Overview  ## Assigning an ISOProps Property to a Feature of Interest  ## Relation between DCAT vocabulary and the ISOProps ontology  @en
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The Level of Information Need (LOIN) Ontology is defined for specifying information requirements for delivery of data in a buildings' life cycle. The LOIN ontology is based on the standard BS EN 17412-1 (2020). Furthermore, it is extended with vocabulary for connecing Information Delivery Specifications (IDS) and Information containers for linked document delivery (ICDD) as per ISO 21597-1 (2020). @en
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Metadata for Ontology Description and publication @en