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This is a README file for a data repository originating from the DCML corpus initiative and serves as welcome page for both

the GitHub repo DCMLab/handel_keyboard and the corresponding
documentation page https://dcmlab.github.io/handel_keyboard

For information on how to obtain and use the dataset, please refer to this documentation page.

When you use (parts of) this dataset in your work, please read and cite the accompanying data report:

Hentschel, J., Rammos, Y., Neuwirth, M., & Rohrmeier, M. (2025). A corpus and a modular infrastructure for the empirical study of (an)notated music. Scientific Data, 12(1), 685. https://doi.org/10.1038/s41597-025-04976-z

Georg Friedrich Händel – Grobschmied Variations (The Harmonious Blacksmith), HWV 430 (A corpus of annotated scores)#

This corpus of annotated MuseScore files has been created within the DCML corpus initiative and employs the DCML harmony annotation standard. It represents the Air and Variations movement from Händel’s Suite no. 5 in E Major, HWV 430, published in 1720 and popularly called The Harmonious Blacksmith. The title (translated into German as Grobschmied) refers to the spurious 19th-century rumour that the repeated high B in the Air was inspired by the sound of a blacksmith’s anvil. In actuality the melody was likely based upon one from Händel’s 1704 opera Almira. Händel’s intricate soprano-bass counterpoint results in florid harmonic elaborations whose elaboration throughout the five Variations our annotations reflect.

Getting the data #

download repository as a ZIP file
download a Frictionless Datapackage that includes concatenations of the TSV files in the four folders (measures, notes, chords, and harmonies) and a JSON descriptor:
- handel_keyboard.zip
- handel_keyboard.datapackage.json
clone the repo: git clone https://github.com/DCMLab/handel_keyboard.git

Data Formats #

Each piece in this corpus is represented by five files with identical name prefixes, each in its own folder. For example, the first section, Aria has the following files:

MS3/hwv430d_Grobschmied_Aria.mscx: Uncompressed MuseScore 3.6.2 file including the music and annotation labels.
notes/hwv430d_Grobschmied_Aria.notes.tsv: A table of all note heads contained in the score and their relevant features (not each of them represents an onset, some are tied together)
measures/hwv430d_Grobschmied_Aria.measures.tsv: A table with relevant information about the measures in the score.
chords/hwv430d_Grobschmied_Aria.chords.tsv: A table containing layer-wise unique onset positions with the musical markup (such as dynamics, articulation, lyrics, figured bass, etc.).
harmonies/hwv430d_Grobschmied_Aria.harmonies.tsv: A table of the included harmony labels (including cadences and phrases) with their positions in the score.

Each TSV file comes with its own JSON descriptor that describes the meanings and datatypes of the columns (“fields”) it contains, follows the Frictionless specification, and can be used to validate and correctly load the described file.

Opening Scores #

After navigating to your local copy, you can open the scores in the folder MS3 with the free and open source score editor MuseScore. Please note that the scores have been edited, annotated and tested with MuseScore 3.6.2. MuseScore 4 has since been released which renders them correctly but cannot store them back in the same format.

Opening TSV files in a spreadsheet #

Tab-separated value (TSV) files are like Comma-separated value (CSV) files and can be opened with most modern text editors. However, for correctly displaying the columns, you might want to use a spreadsheet or an addon for your favourite text editor. When you use a spreadsheet such as Excel, it might annoy you by interpreting fractions as dates. This can be circumvented by using Data --> From Text/CSV or the free alternative LibreOffice Calc. Other than that, TSV data can be loaded with every modern programming language.

Loading TSV files in Python #

Since the TSV files contain null values, lists, fractions, and numbers that are to be treated as strings, you may want to use this code to load any TSV files related to this repository (provided you’re doing it in Python). After a quick pip install -U ms3 (requires Python 3.10 or later) you’ll be able to load any TSV like this:

import ms3

labels = ms3.load_tsv("harmonies/hwv430d_Grobschmied_Aria.harmonies.tsv")
notes = ms3.load_tsv("notes/hwv430d_Grobschmied_Aria.notes.tsv")

Hentschel, J., Rammos, Y., Neuwirth, M., & Rohrmeier, M. (2025). A corpus and a modular infrastructure for the empirical study of (an)notated music. Scientific Data, 12(1), 685. https://doi.org/10.1038/s41597-025-04976-z

License #

Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License (CC BY-NC-SA 4.0).

cc-by-nc-sa-image

Overview #

file_name	measures	labels	standard	annotators	reviewers
hwv430d_Grobschmied_Aria	9	51	2.3.0	Adrian Nagel (2.1.0), Davor Krkljus (2.3.0)	DK
hwv430d_Grobschmied_Var1	8	56	2.3.0	Adrian Nagel (2.1.0), Davor Krkljus (2.3.0)	DK
hwv430d_Grobschmied_Var2	8	58	2.3.0	Adrian Nagel (2.1.0), Davor Krkljus (2.3.0)	DK
hwv430d_Grobschmied_Var3	8	56	2.3.0	Adrian Nagel (2.1.0), Davor Krkljus (2.3.0)	DK
hwv430d_Grobschmied_Var4	8	68	2.3.0	Adrian Nagel (2.1.0), Davor Krkljus (2.3.0)	DK
hwv430d_Grobschmied_Var5	12	61	2.3.0	Adrian Nagel (2.1.0), Davor Krkljus (2.3.0)	DK

Overview table automatically updated using ms3.

Further information: