Version DOI GitHub repo size License

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

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

Robert Schumann – Liederkreis (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.

Robert Schumann’s op. 39 Liederkreis is one of two works bearing that same title, both of which Schumann wrote during his 1840 “Liederjahr” (Year of Song); incidentally, 1840 was the same year of Schumann’s marriage to Clara Wieck. Other vocal works from Schumann’s “Liederjahr” include the famous Dichterliebe and Frauenliebe und Leben. Incidentally, these works are Schumann’s first published works not for solo piano, his only known chamber work prior to 1840 being the posthumously published C minor Piano Quartet of 1829. It was, in fact, Clara who encouraged Robert to branch out beyond solo-piano genres, and the height of emotion showcased in these 1840 songs speaks to a primed sensitivity already latent in Robert’s practice.

Op. 39, the “Eichendorff Liederkreis,” sets excerpts from Joseph von Eichendorff’s collection Intermezzo. Unlike most other song cycles in Schumann’s oeuvre, these poems do not directly convey a narrative, instead portraying a series of landscapes and nature images shot through with intense and abrupt emotional outbursts. Schumann’s piano writing is tightly conjoined with melodic figuration, showcasing a logical early extension of his solo-piano technique in a vocal context. Our annotations reveal the harmonic framework that supports the rich polyphonic details present in this voice-and-piano texture.

Getting the data#

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 song, In der Fremde, has the following files:

  • MS3/op39n01.mscx: Uncompressed MuseScore 3.6.2 file including the music and annotation labels.

  • notes/op39n01.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/op39n01.measures.tsv: A table with relevant information about the measures in the score.

  • chords/op39n01.chords.tsv: A table containing layer-wise unique onset positions with the musical markup (such as dynamics, articulation, lyrics, figured bass, etc.).

  • harmonies/op39n01.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/op39n01.harmonies.tsv")
notes = ms3.load_tsv("notes/op39n01.notes.tsv")

Version history#

See the GitHub releases.

Questions, Suggestions, Corrections, Bug Reports#

Please create an issue and/or feel free to fork and submit pull requests.

Cite as#

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

op39n01

28

47

2.1.0

Uli Kneisel

Adrian Nagel

op39n02

30

66

2.1.0

Uli Kneisel

Adrian Nagel

op39n03

72

106

2.1.0

Uli Kneisel

Adrian Nagel

op39n04

39

53

2.1.0

Uli Kneisel

Adrian Nagel

op39n05

68

83

2.1.0

Uli Kneisel

Adrian Nagel

op39n06

30

68

2.1.0

Uli Kneisel

Adrian Nagel

op39n07

39

66

2.1.0

Uli Kneisel

Adrian Nagel

op39n08

39

88

2.1.0

Uli Kneisel

Adrian Nagel

op39n09

28

86

2.1.0

Uli Kneisel

Adrian Nagel

op39n10

41

108

2.1.0

Uli Kneisel

Adrian Nagel

op39n11

50

67

2.1.0

Uli Kneisel

Adrian Nagel

op39n12

31

54

2.1.0

Uli Kneisel

Adrian Nagel

Overview table automatically updated using ms3.

Further information: