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  1. Home > Articles & Issues >
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  3. A reproducible frame ...
Article

A reproducible framework to publish and reuse Collections as data: the case of the European Literary Bibliography

Gustavo Candela ORCID (1), Cezary Rosiński ORCID (2), Arkadiusz Margraf ORCID (3)
(1) University of Alicante
(2) Institute of Literary Research of the Polish Academy of Sciences
(3) Institute of Bioorganic Chemistry of the Polish Academy of Sciences
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Submitted on
November 12, 2024
Accepted on
April 3, 2025
Published on
June 16, 2025
Last modified on
August 28, 2025
Volume 1
Workflows
Metadata-based workflows
DOI
10.46298/transformations.14729
License
Attribution 4.0 International (CC BY 4.0)
European Commission
101132163
Advancing FronTier Research In the Arts and hUManities
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1377
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576
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A reproducible framework to publish and reuse Collections as data: the case of the European Literary Bibliography

Gustavo Candela ORCID (1), Cezary Rosiński ORCID (2), Arkadiusz Margraf ORCID (3)
(1) University of Alicante
(2) Institute of Literary Research of the Polish Academy of Sciences
(3) Institute of Bioorganic Chemistry of the Polish Academy of Sciences
Abstract
GLAM (Galleries, Libraries, Archives and Museums) institutions host rich content that is provided in the form of digital collections. Bibliographic databases are collections of references focused on a particular topic that can be used to apply Digital Humanities (DH) methods. Recent approaches such as Collections as Data and Labs promote the publication of digital collections supporting computational use.This work aims to provide a framework for publishing and reusing digital collections based on literary bibliographies published by GLAM institutions in order to make them suitable for computational use in the form of Collections as Data, in particular, in the context of the European Literary Bibliography. It also describes the infrastructure used and DH research scenarios to illustrate how the results can be reused for different goals. Digital curators and DH researchers interested in making their datasets available in the form of Collections as Data are the intended audience of this work.
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