Disdrometers are advanced instruments used to measure the size and velocity of raindrops, providing crucial insights into precipitation microphysics and aid in calibrating ground and spaceborne weather radars.DISDRODB is an open and collaborative project focused on creating a global and comprehensive database of disdrometer data and products. To achieve our ambitious goal within the context of the ORD project, we partially redesigned the software to transition DISDRODB to a decentralized data infrastructure. Additionally, we ensured the software reliability and facilitated future maintenance through rigorous testing. This comprehensive approach has strengthened the project's data management capabilities, fostering a dependable and efficient system that supports seamless collaboration and data integration across diverse research institutions. In DISDRODB, data contributors play a pivotal role by uploading raw data from their disdrometer stations to their preferred remote data repositories like Zenodo. Additionally, they include essential station information in the DISDRODB metadata repository, along with the URL where the raw data is stored. The DISDRODB metadata repository, located on GitHub, allows the community to track all available stations, their corresponding data repositories, and to collaborate to continuously improve station metadata using best open-source practices. This inclusive and participatory approach ensures the accuracy and reliability of the data, enhancing the overall quality of the database. The open-source python disdrodb package serves as the foundation, offering tools for interacting with the metadata archive and the remote data repositories. It enables disdrometer data retrieval from remote repositories, as well as standardization and homogenization of raw disdrometer data on the user-side. To expand the DISDRODB archive, data contributors simply need to specify the content of the raw data they wish to contribute using a reader template function provided by the disdrodb software. In conclusion, the streamlined process adopted by the DISDRODB infrastructure guarantees efficient incorporation and processing of new data. Additionally, the software modular configuration files enable seamless integration of data from future disdrometer technologies and sensors with custom specifications. The rigorous testing of DISDRODB infrastructure, coupled with its user-friendly contribution system, is expected to facilitate the mobilization of scientific data archives currently scattered across numerous institutions globally. This project represents a significant step towards enhancing data accessibility and collaboration within the scientific community.