DOI10.5281/zenodo.13221002Zenodo13221002MaRDI QIDQ6701068
Dataset published at Zenodo repository.
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The Garzoni dataset comprises apprenticeship contracts registered in Venice from the 16th to the 18th century, sourced from the records of the Accordi dei Garzoni, held at the Venetian State Archives. The contracts were manually annotated and curated via a dedicated web application, considering a wide range of contractual information,also including social and geographical relations. This rich and extensive dataset of over 54,000 annotated apprenticeship contracts can support the study of apprenticeship, work and society in early modern Venice.This release contains the following Garzoni data, in JSON and XLSX formats: contracts person mentions person_relationships persons profession_categories professions locations Please note that location normalization is incomplete. For more information about data model visit https://garzoni.dhlab.epfl.ch.If you use this data, please cite the work listed below. Maud Ehrmann, Orlin Topalov, and Frdric Kaplan, "From Archival Sources to Structured Historical Information: Annotating and Exploring the Accordi Dei Garzoni," in Apprenticeship, Work, Society in Early Modern Venice, ed. Anna Bellavitis and Valentina Sapienza (London: Routledge, 2023), 304, https://doi.org/10.4324/9781003197195-6. @incollection{ehrmann_archival_2023, title = {From {Archival Sources} to {Structured Historical Information}: {Annotating} and {Exploring} the "{Accordi} Dei {Garzoni}"}, booktitle = {Apprenticeship, {Work}, {Society} in {Early Modern Venice}}, author = {Ehrmann, Maud and Topalov, Orlin and Kaplan, Frederic}, editor = {Bellavitis, Anna and Sapienza, Valentina}, year = {2023}, pages = {304}, publisher = {Routledge}, address = {London}, url = {https://infoscience.epfl.ch/handle/20.500.14299/195087}, isbn = {978-1-00-319719-5}} Bellavitis, A., Sapienza, V. (Eds.). (2023). Apprenticeship, Work, Society in Early Modern Venice (1st ed.). Routledge. https://doi.org/10.4324/9781003197195
This page was built for dataset: Garzoni Dataset
