The ORSMD project set out to make synthetic mobility data for Switzerland more open, accessible, and easier to use. Synthetic mobility data are artificial datasets that reproduce travel patterns without identifying real people. They are valuable for research, planning, and policy because they allow users to study how people move while protecting privacy. To achieve this, the project improved and redesigned the Swiss implementation eqasim a generic pipeline for generating synthetic individual persons and their movements over a single day. A major outcome was a full reworking of the data-generation pipeline so that it is more modular, flexible, and easier to maintain. The project also increased the use of open data sources, including SynPop 2022, and replaced older transport supply inputs with the more widely used GTFS standard. Where fully open data were not available, we developed anonymization methods to ensure that individuals from raw data cannot be identified. The project also made important progress in openness and usability. The codebase was migrated to GitHub under the new name eqasim-switzerland, improving its international visibility and future collaboration. In addition, prototype frontend and backend tools were developed so users can explore, visualize, filter, and compare the generated mobility data through web-based interfaces. Overall, the project has laid the foundation for a durable open research data framework that will support researchers today and, in the future, also help practitioners and policy-makers make betterinformed mobility decisions.