Methodology

Tile 2 Methodology

M1 – User Manual, part one

Our project dataset consists of around 2,617 collations: note-by-note comparisons of all extant eighteenth-century witnesses of Domenico Scarlatti’s keyboard sonatas with a designated baseline text which we call the control.

M2 – User Manual, part two (Header)

This section explains the spreadsheet Header fields used to record witness metadata, notation, ornamentation, and other textual features, clarifying how these details were documented across the project.

M3 – User Manual, part three (Bars)

This section explains how variants were recorded in the Bars section through a consistent, machine-readable notation system that captures note-by-note differences between each witness and the control.

M5 – Compilation phase

This section outlines how the project identified, acquired, indexed, and processed surviving Scarlatti witnesses using catalogues, CSV metadata files, and the Copycutter script to organise collections into individual sonata files.

M6 – Collation and validation phases

The 2,617 collations were completed in phases by team members and freelance research assistants using bespoke tools and workflows, then carefully validated to ensure accuracy and consistency.

M7 – Analysis, part one

This section explains how computational tools and a variant dictionary were used to validate, categorise, and convert the project’s large dataset of Scarlatti variants for further analysis and phylogenetic research.

M8 – Analysis, part two

This section explains how users can analyse the Texting Scarlatti dataset either through a beginner-friendly Google Colab tutorial series or by using the project’s GitHub scripts and data directly.

Contribute to the discussion

We welcome contributions to the discussion, which will be moderated but not edited. We ask that contributions focus on the work of this project and use our conventions (K and KS numbers, sigla, author date references). Any bibliographical items not found in our References section will be added. Please send your contributions to research@gsmd.ac.uk in the first instance.