The German Commons - 154 Billion Tokens of Openly Licensed Text for
  German Language Models
Authors: name: Lukas Gienapp, name: Christopher Schröder, name: Stefan Schweter, name: Christopher Akiki, name: Ferdinand Schlatt, name: Arden Zimmermann, name: Phillipe Genêt, name: Martin Potthast
Organization: CORAL NLP Research

Large language model development relies on large-scale training corpora, yet
most contain data of unclear licensing status, limiting the development of
truly open models. This problem is exacerbated for non-English languages, where
openly licensed text remains critically scarce. We introduce the German
Commons, the largest collection of openly licensed German text to date. It
compiles data from 41 sources across seven domains, encompassing legal,
scientific, cultural, political, news, economic, and web text. Through
systematic sourcing from established data providers with verifiable licensing,
it yields 154.56 billion tokens of high-quality text for language model
training. Our processing pipeline implements comprehensive quality filtering,
deduplication, and text formatting fixes, ensuring consistent quality across
heterogeneous text sources. All domain subsets feature licenses of at least
CC-BY-SA 4.0 or equivalent, ensuring legal compliance for model training and
redistribution. The German Commons therefore addresses the critical gap in
openly licensed German pretraining data, and enables the development of truly
open German language models. We also release code for corpus construction and
data filtering tailored to German language text, rendering the German Commons
fully reproducible and extensible.