This is the latest in a series of successful ARDUOUS (International Workshop on Annotation of Real World Data for Artificial Intelligence Systems; previously Annotation of useR Data for UbiquitOUs Systems) workshops. The field of Artificial Intelligence (AI) has seen a rapid development in the last years with a huge increase in the consumption of data and in the recognition of its influence on the developed AI systems. To address this shift from knowledge-based to data-driven AI systems development, the ARDUOUS workshop series explore various topics in data annotation for AI applications. Well-annotated data powers developments in many fields of AI such as training models in machine learning, computer vision, and natural language processing, learning representations in knowledge representation and reasoning or planning and search, and plays an important role in validating knowledge-based systems. Furthermore, ensuring the involvement of the relevant stakeholders increases the fairness, ethics and trust in the annotations and ultimately in the resulting AI systems.