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Collected metadata for masses in the early Cappella Sistina choirbooks

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NIAID Data Ecosystem2026-03-13 收录
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https://zenodo.org/record/6006653
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资源简介:
This dataset contains a collection of metadata about the early Cappella Sistina choirbooks, once belonging to the Papal Chapel. It presents the mass compositions contained in the manuscript sources V-CVbav MS 14, 23, 35, 41, 49, 51, 63, 197, 64 and concordant sources of these. The data has been collected in the year 2015 and hasn't been double-checked by any other person. Even though the data was collected as conscientiously as possible, it is sometimes incomplete and errors are also possible. The data as well as the data structure has been collected mostly in German. References for this metadata collection can be found under ./references. This data has been used already in: Plaksin, Anna Viktoria Katrin: "Modelle zur computergestützten Analyse von Überlieferungen der Mensuralmusik. Emprische Textforschung im Kontext phylogenetischer Verfahren.", Münster, 2021 (Schriften zur Musikwissenschaft aus Münster 27), online: urn:nbn🇩🇪hbz:6-59029717067, DOI: 10.26083/tuprints-00017211 The repo for this dataset can be found here: https://github.com/annplaksin/earlyCappSistMasses This release contains the slightly updated version that has been used in 10.26083/tuprints-00017211: SQL dump has been changed from MySQL to SQLite dialect Views have been updated PKs have been updated to ensure database-wide uniqueness (in a very basic way). Contents The SQLite database set is found under ./sql. It contains not only the tables but various views for a better overview. For opening and viewing the sql data, tools like e.g. the DB Browser for SQLite can be used. The ./csv folder contains csv exports of the tables and views. In ./networkData contains the relations of works and sources as bipartite network in .csv format. The edges are available as edge list or as adjacency matrix. The node list contains very basic information necessary for identification. Please note, this is the raw exported data for analysis.
创建时间:
2022-02-09
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