Archive of Danish Literature
The dataset is a subset of the texts in Archive of Danish Literature. The dataset is free of copyright and provides quick access to a well-structured text corpus for digital analysis.
Photo: Erik Henningsen
The material behind the dataset
Archive of Danish Literature (ADL) is a literary history collection with selected digitised works from older Danish literature, from the Middle Ages to the mid-20th century. ADL is the result of many years of collaboration between Royal Danish Library and The Danish Language and Literature Society. It is a resource for research, teaching, and broad dissemination of older Danish literature, and currently contains works by 78 authors. The texts are reproduced from standard printed editions. The texts are made available on a website, and for many of the works it is possible to both read the digitised and searchable text, and to view facsimiles (copies of the original printed edition).
About the dataset
The dataset is a subset of the texts in ADL. The dataset provides quick access to a well-structured text corpus for digital analysis.
The dataset consists of 156 works from 1851 to 1945. The authors are mainly prominent authors from the period, such as NFS Grundtvig, Edvard Brandes, and Herman Bang.
The dataset can be used to demonstrate various text mining techniques, such as collocations and to analyze keywords in modern Danish, literature and history. You can also create different subsets and examine the works of specific authors, possibly in comparison with other authors.
The dataset is free of copyright.
The creation of the dataset
The digitised text pages are OCR-processed and then semantically marked up in the TEI P5 format. ADL was first launched in 2001. The current version of the website is from 2020. The downloadable dataset was compiled in 2025 by Royal Danish Library, to provide easy access to analysis of the large text corpus with digital tools.
Find datasets and guidance material
- You can search and read the texts individually in tekster.kb.dk.
- Download the dataset from the library's open access archive, LOAR.
- Find Python tutorials and code examples on Github
- The material can also be accessed via Royal Danish Library's API.