Face-to-face interactions between representatives of the state and citizens are a key intercept in public service delivery, for instance when providing social benefits to vulnerable groups. Despite the relevance of these encounters for the individual, but also for society at large, there is a significant research gap in the systematic empirical study of the communication taking place. This is mainly due to the high institutional and data protection barriers for collecting data in a very sensitive and private setting in which citizens request support from the state. In this paper, we describe the procedure of compiling the first open access dataset of transcribed recordings of so-called Public Service Encounters in Germany, i.e., meetings between state officials and citizens in which there is direct communication in order to allocate state services. This dataset sets a new research directive in the social sciences, because it allows the community to open up the black box of direct state-citizen interaction. With data of this kind it becomes possible to directly and systematically investigate bias, bureaucratic discrimination and other power-driven dynamics in the actual communication and ideally propose guidelines as to alleviate these issues.