The ongoing digitization of processes in all domains of everyday life driven by IT systems shows great potential for process automation, analysis, and optimization. In the last decade process mining has advanced to an important and mature discipline of computer science research and has been widely adopted in industry. More recently,—acknowledging the huge potential of digital trace data to study processes—process science has been introduced as an interdisciplinary field studying how processes unfold over time. This paper discusses the potential that arises when using digital trace data not only in the context of highly automated processes but also to investigate human-centered (work) processes and elaborates on associated challenges. Examples range from the semi-automated storage and production processes in a smart factory to healthcare processes to process analysts performing process mining tasks and software engineers reading software artifacts like source code and process models.