This project is funded under the AHRC Big-Data initiative, and aims to make use of the large quantity of information available in on-line scans of music scores to improve the accuracy of Optical Music Recognition, which is the process by which the musical information in a score is extracted from the image of that score, analogous to Optical Character Recognition for text. Multiple images of the score of a piece of music are often available, and to use more than one image increases the information available for the OMR task. This project will take two approaches to improving OMR through the use of multiple sources. The first, post-processing, approach will result in software to take the outputs of multiple runs of OMR software on different sources for the same piece of music, and combine these outputs into a single, more accurate, representation of the piece. The second approach will use multiple information within the OMR software (adapting existing open-source software) to improve the accuracy of recognition.