Data quality assessment in digital score libraries

Sheet music scores have been the traditional way to preserve and disseminate western classical works for centuries. Nowadays, their content can be encoded in digital formats that yield a very detailed representation of expressed language notation. These constitute, therefore, an invaluable asset library services such as search, analysis, clustering, recommendations, synchronization with audio files. Digital scores, like any other published data, may suffer from quality problems. For instance, they contain incomplete or inaccurate elements. As “dirty” dataset irrelevant input some use cases, users need able estimate level data are about use. This article presents management framework score libraries (DSL) designed by GioQoso multi-disciplinary project. It relies on model identifies several information levels unfortunately blurred out encodings. then serves foundation organize categories issues occur score, leading model. The also positions each issue respect potential usage contexts, allowing attachment consistent set indicators together measure how given is fit specific usage. We finally report implementation these conceptual foundations online DSL.