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...
Enregistré dans:
| Dans: | URI:https://journals.openedition.org/jtei, |
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| Auteurs principaux: | , , , , , |
| Format: | Article ou chapitre numérique |
| Langue: | Anglais |
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Journal of the Text Encoding Initiative
2025
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| Sujets: | |
| Accès en ligne: | Accès Université d'Orléans et IFPM Accès Université d'Orléans et IFPM |
| Résumé: | 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. |
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