  This paper presents thirteen datasets for binary, multiclass and multilabel
classification based on the European Court of Human Rights judgments since its
creation. The interest of such datasets is explained through the prism of the
researcher, the data scientist, the citizen and the legal practitioner.
Contrarily to many datasets, the creation process, from the collection of raw
data to the feature transformation, is provided under the form of a collection
of fully automated and open-source scripts. It ensures reproducibility and a
high level of confidence in the processed data, which is some of the most
important issues in data governance nowadays. A first experimental campaign is
performed to study some predictability properties and to establish baseline
results on popular machine learning algorithms. The results are consistently
good across the binary datasets with an accuracy comprised between 75.86% and
98.32% for an average accuracy of 96.45%.
