Nowadays, people are often listening to music through online services at home, at work or even when on the road, thus media service providers are living their golden age. The databases containing the available songs are enormous, however, most users only listen to their own preferred playlists. If they would have the option to browse from a list containing similar artists, they might find new, unfamiliar songs to their collection. This kind of relationship visualization is still in its infancy, as most of the time the next song or video in the playlist has a direct reference to the currently playing media.
In my thesis I got to know various music databases, especially their interfaces and the data that can be accessed through them. I also researched multiple clients and server side technologies, and then based on these experiences I designed a web application in which I put special emphasis on the user experience expectations for web pages, such as responsive design or loading time. I created a server-client web application which can be used to search for an artist, an album, a song or a label. In addition to various data and statistics (e.g. number of unique play, popularity, best-known albums, etc.), users can listen to the sample of the songs. The relationship of artists with similar music style are displayed in an easy to understand, flexible graph.
I tested the created website by response time and scalability, and based on these experiences, I also implemented a caching feature that provides acceptable search times even with larger visitor numbers.
In the course of my thesis I was able to gain insight into various web technologies, client-side visualization and interfaces provided by music databases.