Carl Nielsen's works
The dataset contains indexes for the works of several Danish composers. The guide focuses on the index for Carl Nielsen's works and analysis of these with R.
Photo: Georg Lindström
The material behind the dataset
The index identifies and describes the individual works, reproduces them as sheet music and links a wide range of information to them. This may include, for example, when they were composed, a link to their treatment in the printed edition, the Carl Nielsen Edition in 32 volumes, the history of their creation, the sources of the information, for example sheet music manuscripts, letters, and so forth.
See the Carl Nielsen index: Catalogue of Carl Nielsen's Works.
About the dataset
The dataset is an extract of the raw data underlying the digital access solution. The solution uses the XML format MEI, which is specially designed to annotate musical works, as well as extensive supplementary data associated with the works themselves. The MEI standard is developed and maintained by the Music Encoding Initiative.
The dataset only includes metadata and not the actual scores for the musical works. The dataset is prepared for analysis, and the guide therefore focuses primarily on showing how to analyze the data, for example where Carl Nielsen's works are listed, which authors he composed music for, and more.
The dataset is free of copyright.
The creation of the dataset
This dataset is based on a comprehensive thematic-bibliographic index of Carl Nielsen's works in 32 volumes. The index was prepared by the Danish Center for Music Publishing, a former unit of Royal Danish Library, which also has the vast majority of the source material in its collections. The digital edition builds on and supplements the printed edition and is available in the Catalogue of Carl Nielsen's Works, CNW. It is a practical-scientific index with works as well as many sources, information on creation, first performances, and more.
Find datasets and guidance material
- View notes and read more about the index and the work behind it in the access solution DCM.
- Download the dataset from the library's open access archive, LOAR.
- Find tutorials and code examples in R on Github