  This article summarizes the BCN20000 dataset, composed of 19424 dermoscopic
images of skin lesions captured from 2010 to 2016 in the facilities of the
Hospital Cl\'inic in Barcelona. With this dataset, we aim to study the problem
of unconstrained classification of dermoscopic images of skin cancer, including
lesions found in hard-to-diagnose locations (nails and mucosa), large lesions
which do not fit in the aperture of the dermoscopy device, and hypo-pigmented
lesions. The BCN20000 will be provided to the participants of the ISIC
Challenge 2019, where they will be asked to train algorithms to classify
dermoscopic images of skin cancer automatically.
