  Object Cluster Hierarchies is a new variant of Hierarchical Cluster Analysis
that gains interest in the field of Machine Learning. Being still at an early
stage of development, the lack of tools for systematic analysis of Object
Cluster Hierarchies inhibits its further improvement. In this paper we address
this issue by proposing a generator of synthetic hierarchical data that can be
used for benchmarking Object Cluster Hierarchy methods. The article presents a
thorough empirical and theoretical analysis of the generator and provides
guidance on how to control its parameters. Conducted experiments show the
usefulness of the data generator that is capable of producing a wide range of
differently structured data. Further, benchmarking datasets that mirror the
most common types of hierarchies are generated and made available to the
public, together with the developed generator
(http://kio.pwr.edu.pl/?page\_id=396).
