How I built a melody map of Greater Tokyo: 2496 stations and recordings for only 200

The author shares their experience in creating a unique dataset containing train departure melodies for 2496 stations in Greater Tokyo. The project required integrating disparate sources, including wikis, audio archives, and open data. During the process, it became clear that even the simple task of matching station names was a complex analytical challenge due to inconsistencies in data formats. The article details the methodology for data collection, common errors during data cleaning, and the difficulties of verifying sources. The author emphasizes that the quality of final insights in big data projects depends less on algorithm complexity and more on the thoroughness of preparing and normalizing source information. This case study clearly demonstrates how routine data collection becomes the foundation for a high-quality digital product, even if recordings were ultimately obtained for only a small fraction of the stations.