Texting Scarlatti: composition, reception, performance

Domenico Scarlatti (b. Naples 1685; d. Madrid 1757) was one of the leading figures of eighteenth-century music. He revolutionised keyboard playing, became a central point of reference for generations of keyboard composers, and remains extremely popular with performers and audiences alike. He spent most of his working life teaching the same royal pupil in the courts of Portugal and Spain; yet, somehow, his music escaped the confines of the royal music room and went viral across Europe.

The ‘Texting Scarlatti’ project aims to chart the spread of Scarlatti’s music by establishing the stemma of all ±3200 surviving eighteenth-century manuscript and printed copies of his keyboard sonatas, and by mapping the major routes of circulation and their implied chronologies. This involves detailed bar-by-bar, note-by-note collation of all extant witnesses, a process that cannot be automated and requires careful attention to detail and skilled judgement. Every note of music encodes many different kinds of information; a full collation of all 3,200 witnesses will generate about 20 million data points and each collation will need to be done at least twice.

To piece together this jigsaw the project uses a combination of traditional textual criticism, large-scale computerised data management, and a collaborative approach: a core team of five specialists working with a group of up to 50 volunteer ‘citizen scientists’ from around the world. This group -the ‘Argos’ group- gives the core team an extra 100 hands for the textual heavy lifting, and an extra 100 eyes for collation, data entry and double-checking. Most of the volunteers are professional performers and teachers and are well placed to act as ambassadors for the project.

Research England’s participatory research funding enabled the team to run a pilot project during 2022 and to secure the grant from the Leverhulme Trust to complete the work. During the pilot they tested systems and processes, coding, data entry and data management. The team have developed a bespoke data management and analysis tool which could be used for similar large-scale textual analysis in both words and music.