Purpose: Rare diseases often face challenges related to delayed diagnosis, with many patients receiving incorrect or no diagnosis. The lack of available treatments, coupled with a scarcity of experts and reliable data, complicates clinical care and research. Current coding systems, such as ICD-10, can only accurately describe a small amount of these diseases. There is a need for improved semantic standards to better represent rare diseases for documentation and research. The study aims to compare and improve mappings of rare disease terminologies: We propose a process to harmonize and extend the mapping of ORPHAcodes to SNOMED, ICD-10 and to establish ORPHAcodes as a non-standard vocabulary within the community of Observational Health Data Sciences and Informatics (OHDSI). Methods: The process comprises eight steps, including data set harmonization, identifying overlaps and gaps, and mapping combination. Existing mappings from Orphadata and the German Federal Institute for Drugs and Medical Devices (BfArM) formed the foundation. Results: All mappings were harmonized and stored in a Transition Database. Through the process, the mappings of ORPHAcodes were extended: 83% of the 9,520 ORPHAcodes (n = 7,877) can now be mapped and 100% of the ORPHAcodes (n = 9,520) were prepared as a vocabulary for OHDSI. Conclusions: Automating the process by developing workflows and storage approaches facilitates quick and easy updates, significantly reducing the need for manual interventions. The process lays the groundwork for quality-assured terminology management, a critical component of international research.