This competition investigates the performance of large-scale retrieval of historical document fragments based on writer recognition. The analysis of historic fragments is a difficult challenge commonly solved by trained humanists. We focus on the task of automatic image retrieval to simulate common scenarios of humanities research, such as fragment or writer retrieval. Therefore, we created a large dataset consisting of more than 120000 fragments. The goal is then to find similar patches of the same page or manuscript. contains ~100 000 fragments using the Historical-IR19 as base dataset, they should all contain some text, however some fragments are quite small. Training-set: contains ~100 000 fragments using the Historical-IR19 as base dataset, they should all contain some text, however some fragments are quite small. Test-set: contains about 20 000 new fragments Naming-convention: WID_PID_FID.jpg , where WID=writer id, PID: page id, FID= fragment id For more information visit: https://lme.tf.fau.de/research/competitions/hisfragir20/