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Coreon – Your Multilingual Knowledge System

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Model multilingual taxonomies, thesauri, classifications and concept systems.

Visually explore large terminology collections.

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Coreon. See how it works.

Try our life system with three public repositories. Explore and experience Coreon. You can search and browse the repositories, expand the map, get your hands on the multilingual terminology. If you want to have the full experience with editing and manipulating the data, please sign up as user.

Eurovoc

European Union's multilingual thesaurus

EUROVOC is the European Union’s multilingual thesaurus. It has been converted from SKOS/rdf. This data set is highly multilingual, covering 20+ languages.

The data is caracterised by a very structured, levelled approach. Upper levels contain classificatory numbers (/ 36 science / 3611 humanities …). Through Coreon’s multilingual concept map approach the data is explorable in any of the available languages. For instance, switch to Spanish as source language and see immediately how the concept map is rendered in Spanish.

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MeSH

Medical Subject Headings

This repository contains the Medical Subject Headings from the U.S. National Library of Medicine. This thesaurus is a controlled vocabulary produced by the National Library of Medicine and used for indexing, cataloging, and searching for biomedical and health-related information and documents. The converted data contains the so-called Descriptors data (from 14 July 2015).

The data set, with its significant size (approx. 80,000 nodes, 240,000 terms and 100,000 relations), clearly illustrates how important it is to visualise semantic context.

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Advanced Multilingual Taxonomy

This repository contains content from study and research carried out at the FH Cologne (Fachhochschule Köln), in the framework of diploma thesis at the Institute for Translation and Multilingual Communication.

The content illustrates how Coreon brings together full-featured terminological information with conceptual relations. Each term is attributed with extensive descriptive meta data, it demonstrates Coreon’s flexibility.

The conceptual relations in this data set illustrate that Coreon’s concept maps are not only simple trees but in fact cater for multiple parent-child relations which go beyond simple tree/folder explorers. For instance, search for the concept white balance and see how it is linked to three parent concepts.

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