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The Shortcomings of Language Tags for Linked Data When Modeling Lesser-Known Languages
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Tittel, Sabine; Gillis-Webber, Frances. - : Schloss Dagstuhl - Leibniz-Zentrum fuer Informatik, 2019. : OASIcs - OpenAccess Series in Informatics. 2nd Conference on Language, Data and Knowledge (LDK 2019), 2019
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Abstract:
In recent years, the modeling of data from linguistic resources with Resource Description Framework (RDF), following the Linked Data paradigm and using the OntoLex-Lemon vocabulary, has become a prevalent method to create datasets for a multilingual web of data. An important aspect of data modeling is the use of language tags to mark lexicons, lexemes, word senses, etc. of a linguistic dataset. However, attempts to model data from lesser-known languages show significant shortcomings with the authoritative list of language codes by ISO 639: for many lesser-known languages spoken by minorities and also for historical stages of languages, language codes, the basis of language tags, are simply not available. This paper discusses these shortcomings based on the examples of three such languages, i.e., two varieties of click languages of Southern Africa together with Old French, and suggests solutions for the issues identified.
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Keyword:
click languages; Data processing Computer science; Khoisan languages; language codes; language tags; Linguistic Linked Data; Linked Data; N|uu; Resource Description Framework; ||'Au
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URN:
urn:nbn:de:0030-drops-103682
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URL: https://drops.dagstuhl.de/opus/volltexte/2019/10368/
https://doi.org/10.4230/OASIcs.LDK.2019.4
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The Shortcomings of Language Tags for Linked Data When Modeling Lesser-Known Languages ...
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