TrainDL (Teacher training for Data Literacy & Computer Science competences) shall conduct activities in Austria, Germany, and Lithuania, focusing on the transferability of digital education competences. The consortium aims to specifically identify how data literacy and competences on artificial intelligence (AI) can become structurally implemented into the training of teachers, both in the course of their university education and for in-service teachers in STEAM in order to reduce the digital gap. Big Data processes and AI have already changed the economic, social, and political environment for people of all backgrounds. Holistic digital education therefore needs to be accessible to all European citizens. This can most effectively be achieved through the respective educational systems.Therefore, pre-service and in-service teachers and policy makers shall have the opportunity to co-create best practices on how these future skills can be anchored in the national systems and in European strategies. It shall be tested how modules and formats of data literacy, computer science (CS) and AI education can be adapted for teacher training so that differences in availability of computer science education can be balanced across European countries. The main target groups involved are pre-service and in-service teachers as well as policy makers in education (national and sub-national ministries, agencies, curriculum-setting bodies). Through a participatory approach rooted in systems thinking and action research, the hypothesis, the measures, and their transferability shall be tested and evaluated in three project cycles. This collaborative process shall produce a continuous exchange and a metric to evaluate the status quo of data literacy in computer science education, leading to a European teacher education monitor. Based on these findings, curriculum recommendations and a policy framework for data literacy and AI shall be introduced to the appropriate European stakeholders.