Understanding and translating humorous wordplay often requires recognition of implicit cultural references, knowledge of word formation processes, and discernment of double meanings – issues which pose challenges for humans and computers alike. This paper introduces the CLEF 2023 JOKER track, which takes an interdisciplinary approach to the creation of reusable test collections, evaluation metrics, and methods for the automatic processing of wordplay. We describe the track’s interconnected shared tasks for the detection, location, interpretation, and translation of puns. We also describe associated data sets and evaluation methodologies, and invite contributions making further use of our data.