  In many research areas, scientific progress is accelerated by
multidisciplinary access to image data and their interdisciplinary annotation.
However, keeping track of these annotations to ensure a high-quality
multi-purpose data set is a challenging and labour intensive task. We developed
the open-source online platform EXACT (EXpert Algorithm Collaboration Tool)
that enables the collaborative interdisciplinary analysis of images from
different domains online and offline. EXACT supports multi-gigapixel medical
whole slide images as well as image series with thousands of images. The
software utilises a flexible plugin system that can be adapted to diverse
applications such as counting mitotic figures with a screening mode, finding
false annotations on a novel validation view, or using the latest deep learning
image analysis technologies. This is combined with a version control system
which makes it possible to keep track of changes in the data sets and, for
example, to link the results of deep learning experiments to specific data set
versions. EXACT is freely available and has already been successfully applied
to a broad range of annotation tasks, including highly diverse applications
like deep learning supported cytology scoring, interdisciplinary multi-centre
whole slide image tumour annotation, and highly specialised whale sound
spectroscopy clustering.
