Scientists have access to a variety of tools and services for managing research data openly. These promote collaboration and improve data analysis efficiency. However, scientists often struggle to select the right services and encounter challenges in using them due to a lack of expertise. Research data is often stored in non-standardized data formats from diverse outputs of scientific instruments. Establishing a standard file format for data exchange across various software and disciplines, was a key focus of our project. The developed pipelines were based on expertise within the ETH domain in Open Research Data activities, tailored for the atmospheric science community. Our solution is further aligned with guidelines from the environmental modeling community, atmospheric observatory community, and large-scale facilities like the SLS. Engaging PhD students and PostDocs was essential in understanding their data management needs and identifying common data treatment strategies. This close collaboration early-on significantly increased the acceptance of the developed tools and ensured hands-on training and tutoring by our data manager to educate them. As a result, we now have a suite of Python and Matlab code that allows us to import and export data and meta-data from commonly used data analysis programs – such as IgorPro, Matlab, and Jupyter notebooks – at any stage of the research process into a commented, open, and complete file.