An analysis and storage system for music research datasets

We present a workflow processing and data storage system that has been developed to store the computational analysis of large databases of music-related documents. Documents can consist of any music-related data, for example, audio files or symbolic scores. The system can be used to run feature extraction algorithms to compute new data based on these input documents. The feature extraction process can be distributed over many networked computers to reduce calculation time. Researchers can develop and run their own algorithms on a collection of music-related documents using any programming system without needing system administrator knowledge or direct access to the files, using a web based interface. Computed features are stored in the system along with a reference to the version of the code that was used to compute it. Audio files and computed features can be accessed over the internet. This system has been developed as a supporting part of the CompMusic project, allowing collaborating researchers to develop new feature extraction algorithms and share them with other researchers. It has been released under an open-source licence.