An increasing number of researchers work in computational auditory scene analysis (CASA). However, a set of tasks, each with a well-defined evaluation framework and commonly used datasets do not yet exist. Thus, it is difficult for results and algorithms to be compared fairly, which hinders research on the field. In this paper we will introduce a newly-launched public evaluation challenge dealing with two closely related tasks of the field: acoustic scene classification and event detection. We give an overview of the tasks involved; describe the processes of creating the dataset; and define the evaluation metrics. Finally, illustrations on results for both tasks using baseline methods applied on this dataset are presented, accompanied by open-source code.