FAIR Derived Data in TEI and Its Publication in the TextGrid Repository

Many research projects face legal restrictions on the publication of texts. In recent decades, several projects have circumvented these restrictions by both deleting some parts of the data and publishing derived data from the original files. We discuss the limitations of the commonly used ad-hoc sol...

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Bibliographic Details
Main Authors: José Calvo Tello, Mathias Göbel, Ubbo Veentjer, Stefan E. Funk, Nanette Rißler-Pipka, Keli Du
Format: Article
Language:deu
Published: Text Encoding Initiative Consortium 2025-03-01
Series:Journal of the Text Encoding Initiative
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Online Access:https://journals.openedition.org/jtei/5622
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Summary:Many research projects face legal restrictions on the publication of texts. In recent decades, several projects have circumvented these restrictions by both deleting some parts of the data and publishing derived data from the original files. We discuss the limitations of the commonly used ad-hoc solutions and the deprecation of the FAIR status that they cause. In contrast, we propose to model derived data in TEI, and present several variants with five corpora from different languages, genres, and periods. We also present the implementation of several features for publishing such data in the TextGrid Repository and the publication of derived data from a corpus of Spanish novels and a corpus of American plays.
ISSN:2162-5603