Biomedical research, provision of healthcare, medical diagnosis, prognosis, and treatment increasingly rely on the processing of huge amounts of data and use of digital technologies. Emerging fields include Artificial Intelligence or Machine Learning to support medical diagnosis, electronic health records to improve the accessibility of patient data and connect health practice and research, as well as mobile health technologies. The increasing availability of digital data and technologies has both conceptual and practical implications for the way people are seen and treated within healthcare. The idea of data justice describes the development of a fundamental standard, of what is owed to individuals with regard to their health data. Theories of data justice give rise to at least three dimensions of ethical inquiry: questions of visibility and adequate representation in data, questions regarding the ability to engage (and disengage) with technology and to have proportionate access to the benefits and questions regarding the ability to address discrimination and materialised biases. The Master Class “Data Justice in Healthcare” aims to promote the exchange of ideas about the emergence, the ethical significance as well as possible individual and systemic solution strategies for a just handling of data within healthcare. We are inviting contributions that address questions of data justice, including but not limited to one of the following subtopics.