DCMLab / dvorak_silhouettes

https://dcmlab.github.io/dvorak_silhouettes/
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Re-extracts all files using ms3 v2.2.1 #19

Closed johentsch closed 1 year ago

johentsch commented 1 year ago

Changes to the TSV facets

Updated filenames

The TSV files have been renamed and now come with a suffix specifying the data facet that they represent. The three facets are

so, for example, the file measures/op08n01.tsv has been renamed to measures/op08n01.measures.tsv.

Added resource descriptors

Each TSV file is now accompanied with a JSON resource descriptor following the frictionless specification for Tabular Data Resources. They can and have be used to validate the tabular data.

These files have the same names as the TSV files they describe but replacing the .tsv extension with .resource.json. For example, the file measures/op08n01.tsv has the corresponding descriptor measures/op08n01.resource.json.

These metadata files replace the previous csv-metadata.json files (which followed the CSVW standard) that had described the data inadequately.

Added column quarterbeats_all_endings

The quarterbeats column (also known as qstamp) that had already been available does not provide values for first or third endings, expressing the dimensions of a singular playthrough without taking into account any repeats. The newly added column quarterbeats_all_endings does not have any empty values, providing continuous positions as if each measure followed the previous one.

Renamed index column

The first column of metadata.tsv was renamed from fname to piece.

Changes to the reviewed folder

The _reviewed.mscx files compare the current set of annotation labels against those from the previous version (v2.1). They are identical, so no differences are displayed.

Wherever the MuseScore parser throws one or several warnings (e.g. because an annotation label does not match the score very well), these warnings appear in a .warnings file. For example, the warnings for op08n01 can be seen in reviewed/op08n01.warnings. One goal for future versions of this dataset would be to reduce the number of warnings to the point of addressing all of them.