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/ABC and the corresponding
documentation page https://dcmlab.github.io/ABC
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:
Neuwirth, M., Harasim, D., Moss, F. C., & Rohrmeier, M. (2018). The Annotated Beethoven Corpus (ABC): A Dataset of Harmonic Analyses of All Beethoven String Quartets. Frontiers in Digital Humanities, 5(July), 1–5. https://doi.org/10.3389/fdigh.2018.00016
The ABC forms part of the larger Distant Listening Corpus which constitutes a data infrastructure the data report of which has implications for the present corpus, too:
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
The Annotated Beethoven Corpus (ABC) (A corpus of annotated scores)#
The ABC dataset consists of expert harmonic analyses of all Beethoven string quartets (opp. 18, 59, 74, 95, 127, 130, 131, 132, 135, composed between 1800 and 1826), encoded in a human- and machine-readable format (MuseScore format). Using a modified Roman Numeral notation (the DCML harmony annotation standard), the dataset includes the common music-theoretical set of harmonic features such as key, chordal root, chord inversion, chord extensions, suspensions, and others.
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, andharmonies) and a JSON descriptor:clone the repo:
git clone https://github.com/DCMLab/ABC.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 movement of the first quartet, op. 18/1, has the following files:
MS3/n01op18-1_01.mscx: Uncompressed MuseScore 3.6.2 file including the music and annotation labels.notes/n01op18-1_01.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/n01op18-1_01.measures.tsv: A table with relevant information about the measures in the score.chords/n01op18-1_01.chords.tsv: A table containing layer-wise unique onset positions with the musical markup (such as dynamics, articulation, lyrics, figured bass, etc.).harmonies/n01op18-1_01.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/n01op18-1_01.harmonies.tsv")
notes = ms3.load_tsv("notes/n01op18-1_01.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.
Publications#
The accompanying Data Report has been published in Neuwirth, M., Harasim, D., Moss, F. & Rohrmeier M. (2018).
An evaluation of the dataset can be found in this Moss, F., Neuwirth M., Harasim, D. & Rohrmeier, M. (2019).
The latest version of the annotation standard has been described in Hentschel, J., Neuwirth, M. & Rohrmeier, M. (2021)
Cite as#
Neuwirth, M., Harasim, D., Moss, F. C., & Rohrmeier, M. (2018). The Annotated Beethoven Corpus (ABC): A Dataset of Harmonic Analyses of All Beethoven String Quartets. Frontiers in Digital Humanities, 5(July), 1–5. https://doi.org/10.3389/fdigh.2018.00016
License#
Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License (CC BY-NC-SA 4.0).
Remarks#
Hybrid version of annotations
v1.0 of this dataset used version 1.0.0 of the DCML harmony annotation standard,
with the version number attributed only in hindsight. Some of the labels that were corrected in the meantime, however,
use features available only in later versions, such as recursive reference to a secondary (‘tertiary’) key as in V7/V/V.
However, changes have been applied conservatively in order to keep the data as homogeneous as possible.
Possible annotation errors
While the annotation process (as detailed in the Data Report) was conducted very carefully, and all annotated symbols have been automatically checked for syntactic correctness, the authors cannot entirely rule out the possibility of typograpical errors or misinterpretations (e.g., due to ambiguities in the score or underspecification in the musical texture). After all, music analysis is not a deterministic process but involves interpretation. If you encounter anything that seems not right to you, please create an issue here.
Missing bars
The original XML file for Op. 132 No. 15, mov. 5 from Project Gutenberg did not contain measures 194-241. We added them manually.
File naming convention#
n(?P<quartet>\d{2}) # quartet number, e.g. n01
op(?P<op>\d{2,3}) # opus number, e.g. op18
(?:-(?P<no>\d))? # (optional) number within the opus, e.g. -1
_(?P<mvt>\d{2}) # movement number, e.g. _01
Overview#
file_name |
measures |
labels |
standard |
annotators |
reviewers |
|---|---|---|---|---|---|
n01op18-1_01 |
313 |
405 |
1.0.0 |
Markus Neuwirth |
|
n01op18-1_02 |
110 |
263 |
1.0.0 |
Markus Neuwirth |
|
n01op18-1_03 |
145 |
203 |
1.0.0 |
Markus Neuwirth |
|
n01op18-1_04 |
381 |
598 |
1.0.0 |
Markus Neuwirth |
|
n02op18-2_01 |
249 |
486 |
1.0.0 |
Markus Neuwirth |
|
n02op18-2_02 |
86 |
177 |
1.0.0 |
Markus Neuwirth |
|
n02op18-2_03 |
87 |
138 |
1.0.0 |
Markus Neuwirth |
|
n02op18-2_04 |
412 |
468 |
1.0.0 |
Markus Neuwirth |
|
n03op18-3_01 |
269 |
383 |
1.0.0 |
Markus Neuwirth |
|
n03op18-3_02 |
151 |
394 |
1.0.0 |
Markus Neuwirth |
|
n03op18-3_03 |
168 |
278 |
1.0.0 |
Markus Neuwirth |
|
n03op18-3_04 |
364 |
569 |
1.0.0 |
Markus Neuwirth |
|
n04op18-4_01 |
219 |
554 |
1.0.0 |
Markus Neuwirth |
|
n04op18-4_02 |
261 |
369 |
1.0.0 |
Markus Neuwirth |
|
n04op18-4_03 |
98 |
145 |
1.0.0 |
Markus Neuwirth |
|
n04op18-4_04 |
217 |
386 |
1.0.0 |
Markus Neuwirth |
|
n05op18-5_01 |
225 |
430 |
1.0.0 |
Markus Neuwirth |
|
n05op18-5_02 |
105 |
168 |
1.0.0 |
Markus Neuwirth |
|
n05op18-5_03 |
139 |
247 |
1.0.0 |
Markus Neuwirth |
|
n05op18-5_04 |
300 |
567 |
1.0.0 |
Markus Neuwirth |
|
n06op18-6_01 |
264 |
374 |
1.0.0 |
Markus Neuwirth |
|
n06op18-6_02 |
79 |
265 |
1.0.0 |
Markus Neuwirth |
|
n06op18-6_03 |
68 |
168 |
1.0.0 |
Markus Neuwirth |
|
n06op18-6_04 |
296 |
465 |
1.0.0 |
Markus Neuwirth |
|
n07op59-1_01 |
400 |
482 |
1.0.0 |
Markus Neuwirth |
|
n07op59-1_02 |
476 |
635 |
1.0.0 |
Markus Neuwirth |
|
n07op59-1_03 |
132 |
374 |
1.0.0 |
Markus Neuwirth |
|
n07op59-1_04 |
327 |
604 |
1.0.0 |
Markus Neuwirth |
|
n08op59-2_01 |
255 |
445 |
1.0.0 |
Markus Neuwirth |
|
n08op59-2_02 |
157 |
326 |
1.0.0 |
Markus Neuwirth |
|
n08op59-2_03 |
134 |
262 |
1.0.0 |
Markus Neuwirth |
|
n08op59-2_04 |
409 |
567 |
1.0.0 |
Markus Neuwirth |
|
n09op59-3_01 |
269 |
516 |
1.0.0 |
Markus Neuwirth |
|
n09op59-3_02 |
207 |
481 |
1.0.0 |
Markus Neuwirth |
|
n09op59-3_03 |
96 |
177 |
1.0.0 |
Markus Neuwirth |
|
n09op59-3_04 |
428 |
699 |
1.0.0 |
Markus Neuwirth |
|
n10op74_01 |
262 |
446 |
1.0.0 |
Markus Neuwirth |
|
n10op74_02 |
169 |
304 |
1.0.0 |
Markus Neuwirth |
|
n10op74_03 |
467 |
447 |
1.0.0 |
Markus Neuwirth |
|
n10op74_04 |
195 |
322 |
1.0.0 |
Markus Neuwirth |
|
n11op95_01 |
151 |
245 |
1.0.0 |
Markus Neuwirth |
|
n11op95_02 |
192 |
353 |
1.0.0 |
Markus Neuwirth |
|
n11op95_03 |
207 |
364 |
1.0.0 |
Markus Neuwirth |
|
n11op95_04 |
175 |
326 |
1.0.0 |
Markus Neuwirth |
|
n12op127_01 |
282 |
558 |
1.0.0 |
Markus Neuwirth |
|
n12op127_02 |
126 |
542 |
1.0.0 |
Markus Neuwirth |
|
n12op127_03 |
289 |
428 |
1.0.0 |
Markus Neuwirth |
|
n12op127_04 |
299 |
689 |
1.0.0 |
Markus Neuwirth |
|
n13op130_01 |
236 |
723 |
1.0.0 |
Markus Neuwirth |
|
n13op130_02 |
107 |
181 |
1.0.0 |
Markus Neuwirth |
|
n13op130_03 |
89 |
450 |
1.0.0 |
Markus Neuwirth |
|
n13op130_04 |
150 |
295 |
1.0.0 |
Markus Neuwirth |
|
n13op130_05 |
66 |
189 |
1.0.0 |
Markus Neuwirth |
|
n13op130_06 |
493 |
626 |
1.0.0 |
Markus Neuwirth |
|
n14op131_01 |
120 |
334 |
1.0.0 |
Markus Neuwirth |
|
n14op131_02 |
197 |
354 |
1.0.0 |
Markus Neuwirth |
|
n14op131_03 |
10 |
30 |
1.0.0 |
Markus Neuwirth |
|
n14op131_04 |
276 |
659 |
1.0.0 |
Markus Neuwirth |
|
n14op131_05 |
499 |
599 |
1.0.0 |
Markus Neuwirth |
|
n14op131_06 |
27 |
68 |
1.0.0 |
Markus Neuwirth |
|
n14op131_07 |
387 |
522 |
1.0.0 |
Markus Neuwirth |
|
n15op132_01 |
264 |
622 |
1.0.0 |
Markus Neuwirth |
|
n15op132_02 |
238 |
479 |
1.0.0 |
Markus Neuwirth |
|
n15op132_03 |
211 |
506 |
1.0.0 |
Markus Neuwirth |
|
n15op132_04 |
46 |
113 |
1.0.0 |
Markus Neuwirth |
|
n15op132_05 |
404 |
732 |
1.0.0 |
Markus Neuwirth |
JH (1.0.0) |
n16op135_01 |
193 |
398 |
1.0.0 |
Markus Neuwirth |
|
n16op135_02 |
272 |
376 |
1.0.0 |
Markus Neuwirth |
|
n16op135_03 |
54 |
178 |
1.0.0 |
Markus Neuwirth |
|
n16op135_04 |
282 |
563 |
1.0.0 |
Markus Neuwirth |
Overview table automatically updated using ms3.
Further information: