The Cantus Database and Cantus Index Network

Author:

Lacoste Debra1

Affiliation:

1. Project Manager and Principal Researcher, University of Waterloo and CANTUS project

Abstract

Abstract Perhaps the oldest and certainly the most enduring of online, medieval chant databases, the Cantus Database for Latin Ecclesiastical Chant and its sister site Cantus Index: Catalogue of Chant Texts and Melodies have experienced stimulating growth over many years. Developments in software and web technologies, coupled with institutional and government support, have enabled multiple rejuvenations for the Cantus Database, now in its fourth decade. Although the original manuscript inventories continue to be the foundation of the Cantus Database and the principal focus of many online searches, its expanded contents and the interactive nature of the website allow for a variety of uses as well as the collection of new data from worldwide contributors. Through sample textual and melodic searches, description of the resources in the database, and demonstration of the infrastructure that ensures compatibility and interoperability with other chant research websites, the place and impact of the Cantus Database and Cantus Index in fields related to medieval musicology and digital humanities are explored in this chapter. The well-known “Cantus” websites, traversing into public musicology and engaging academic crowdsourcing, continue to supply scholars with both raw data and comparative digital tools for chant research, all freely accessible online as the products of collaborative efforts.

Publisher

Oxford University Press

Reference68 articles.

1. Hildegard, Hermannus, and late chant style.;Journal of Music Theory,2008

2. Bain, J. (2017). Optical music recognition: Correcting machine reading outputs. Paper presented at the symposium Machine-Reading and Crowdsourcing Medieval Music Manuscripts. Eastman School of Music, Rochester, NY, October 26, 2017. Archival video of the livestream accessed August 28, 2020, https://www.esm.rochester.edu/machine-reading/

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