  Recording animal behaviour is an important step in evaluating the well-being
of animals and further understanding the natural world. Current methods for
documenting animal behaviour within a zoo setting, such as scan sampling,
require excessive human effort, are unfit for around-the-clock monitoring, and
may produce human-biased results. Several animal datasets already exist that
focus predominantly on wildlife interactions, with some extending to action or
behaviour recognition. However, there is limited data in a zoo setting or data
focusing on the group behaviours of social animals. We introduce a large
meerkat (Suricata Suricatta) behaviour recognition video dataset with diverse
annotated behaviours, including group social interactions, tracking of
individuals within the camera view, skewed class distribution, and varying
illumination conditions. This dataset includes videos from two positions within
the meerkat enclosure at the Wellington Zoo (Wellington, New Zealand), with
848,400 annotated frames across 20 videos and 15 unannotated videos.
