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  CLDFBench: Give your cross-linguistic data a lift

Forkel, R., & List, J. M. (2020). CLDFBench: Give your cross-linguistic data a lift. In N. Calzolari, F. Béchet, P. Blache, K. Choukri, C. Cieri, T. Declerck, et al. (Eds.), Proceedings of the 12th Conference on Language Resources and Evaluation (LREC 2020) (pp. 6995-7002). Paris: European Language Resources Association (ELRA). doi:10.17613/8t0e-w639.

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Datensatz-Permalink: https://hdl.handle.net/21.11116/0000-0007-5474-8 Versions-Permalink: https://hdl.handle.net/21.11116/0000-0007-5475-7
Genre: Konferenzbeitrag

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Forkel_CLDFBench_Proceedings-Of-The-12th-Conference-On-Language-Resources-and-Evaluation_2020.pdf (Verlagsversion), 2MB
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https://hdl.handle.net/21.11116/0000-0007-5476-6
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Forkel_CLDFBench_Proceedings-Of-The-12th-Conference-On-Language-Resources-and-Evaluation_2020.pdf
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Copyright Datum:
2020
Copyright Info:
©European Language Resources Association (ELRA), licensed under CC-BY-NC
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https://creativecommons.org/licenses/by-nc/3.0/de/

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Urheber

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 Urheber:
Forkel, Robert1, Autor           
List, Johann Mattis, Autor
Affiliations:
1Linguistic and Cultural Evolution, Max Planck Institute for the Science of Human History, Max Planck Society, ou_2074311              

Inhalt

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Schlagwörter: Cross-linguistic data; Retro-standardization, Data curation
 Zusammenfassung: While the amount of cross-linguistic data is onstantly increasing, most datasets produced today and in the past cannot be considered
FAIR (findable, accessible, interoperable, and reproducible). To remedy this and to increase the comparability of cross-linguistic resources,
it is not enough to set up standards and best practices for data to be collected in the future. We also need consistent workflows for the “retro-standardization” of data that has been published during the past decades and centuries. With the Cross-Linguistic Data Formats initiative, first standards for cross-linguistic data have been presented and successfully tested. So far, however, CLDF creation was hampered by the fact that it required a considerable degree of omputational proficiency. With cldfbench, we introduce a framework for the retro-standardization of legacy data and the curation of new datasets that drastically simplifies the creation of CLDF by providing a consistent, reproducible workflow that rigorously supports version control and long term archiving of research data and code. The framework is distributed in form of a Python package along with usage information and examples for best practice. This study introduces the new framework and illustrates how it can be applied by showing how a resource containing structural and lexical data for Sinitic languages can be efficiently retro-standardized and analyzed.

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Sprache(n): eng - English
 Datum: 2020-05-192020
 Publikationsstatus: Erschienen
 Seiten: 8
 Ort, Verlag, Ausgabe: -
 Inhaltsverzeichnis: -
 Art der Begutachtung: -
 Identifikatoren: DOI: 10.17613/8t0e-w639
Anderer: shh2600
 Art des Abschluß: -

Veranstaltung

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Titel: 12th Conference on Language Resources and Evaluation [postponed due to Corona]
Veranstaltungsort: Marseille
Start-/Enddatum: 2020-05-11 - 2020-05-16

Entscheidung

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Projektinformation

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Projektname : CALC
Grant ID : 715618
Förderprogramm : Horizon 2020 (H2020)
Förderorganisation : European Commission (EC)

Quelle 1

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Titel: Proceedings of the 12th Conference on Language Resources and Evaluation (LREC 2020)
Genre der Quelle: Konferenzband
 Urheber:
Calzolari, Nicoletta, Herausgeber
Béchet, Frédéric, Herausgeber
Blache, Philippe, Herausgeber
Choukri, Khalid, Herausgeber
Cieri, Christopher, Herausgeber
Declerck, Thierry, Herausgeber
Goggi, Sara, Herausgeber
Ishara, Hitoshi, Herausgeber
Maegaard, Bente, Herausgeber
Mariani, Hélène Mazo, Herausgeber
Moreno, Asuncion, Herausgeber
Odijk, Jan, Herausgeber
Piperidis, Stelios, Herausgeber
Affiliations:
-
Ort, Verlag, Ausgabe: Paris : European Language Resources Association (ELRA)
Seiten: 7251 Band / Heft: - Artikelnummer: - Start- / Endseite: 6995 - 7002 Identifikator: ISBN: 979-10-95546-34-4