The paper deals with granularity of knowledge representation. The subject is studied on the basis of representation of music notation. Music notation is a language allowing for communication in music, one of the most sophisticated field of human activity, and has high level of complexity itself. On one hand, music notation symbols vary in size and have complex shapes; they often touch and overlap each other. On the other hand, music notation is a two dimensional language in which importance of geometrical and logical relations between its symbols may be compared to the importance of the symbols alone. Thus, computer representation of music is the first and perhaps one of the set of most important issues in music processing and music software specifically. Music knowledge, despite that is complicated and flexible, is highly structured and seems to fit perfectly paradigm of granular knowledge structuring. Granularity of music data representation is especially emphasised.
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