  The diffusion of large databases collecting different kind of material
properties from high-throughput density functional theory calculations has
opened new paths in the study of materials science thanks to data mining and
machine learning techniques. Phonon calculations have already been employed
successfully to predict materials properties and interpret experimental data,
e.g. phase stability, ferroelectricity and Raman spectra, so their availability
for a large set of materials will further increase the analytical and
predictive power at hand. Moving to a larger scale with density functional
perturbation calculations, however, requires the presence of a robust framework
to handle this challenging task. In light of this, we automatized the phonon
calculation and applied the result to the analysis of the convergence trends
for several materials. This allowed to identify and tackle some common problems
emerging in this kind of simulations and to lay out the basis to obtain
reliable phonon band structures from high-throughput calculations, as well as
optimizing the approach to standard phonon simulations.
