Prof. Richard Freedman

Nationality: 
United States
Programme: 
SMART LOIRE VALLEY GENERAL PROGRAMME
Scientific Field: 
Period: 
January, 2019 to January, 2020

LE STUDIUM / Marie Skłodowska-Curie Research Fellowship

From

Department of Music, Haverford College - US

In residence at

CESR (Centre d’Etudes Supérieures de la Renaissance) / CNRS, University of Tours - FR

Host scientist

Prof. Philippe Vendrix

PROJECT

CRIM: the Renaissance Imitation Mass

Citations:  The Renaissance Imitation Mass (CRIM) is devoted to the digital representation and shared analysis of sixteenth-century Imitation Masses (Missae ad imitationem), the only musical genre (a corpus of about 500 works) to define itself by the process of transforming pre-existing music in order to create new works. The latest project in a series of long-standing collaborations between Richard Freedman (Haverford College, USA) and members of the Programme Ricercar (CESR, Université of Tours), and an extended team of musicologists and information technology specialists in the USA, Canada and Europe, CRIM will build upon recent developments in the digital domain for music scholarship, implementing a new kind of durable quotable text for music using open-source tools developed for use with the Music Encoding Initiative XML data standard.

The team of scholars and advanced students led by Freedman and his research partners at the Programme Ricercar are using these technologies to build an innovative database of music-analytic observations prepared according to a controlled vocabulary of types that describes the complex contrapuntal relationships found in our corpus. These observations, moreover, will be  bound together with commentaries and annotations prepared by individual researchers, which in turn will be made widely discoverable via Linked Open Data and Open Annotation ontologies.

We will also break much new ground by exploring data analytic and machine learning approaches to music, both by exploring patterns within our observed data and by modeling various algorithmic approaches to discovering similar patterns by automated means. CRIM will enhance musicological research through its novel digital editions and analytical annotation tools; through its improved understanding of citation and transformation processes of pre-existing materials in music, and through its novel meeting of specialists from musicology and information science.