Database Studies

Database studies in music research, also known as corpus-based musicology, have their roots in the advent of digital encoding of music during the 1970s and are closely influenced by corpus-based work undertaken in linguistics. In music research, database studies are an example of a data-rich approach advocated by empirical musicology.

The central idea of database studies is that the research question is formulated in such a way that the answers can be obtained by analyzing large quantities of materials coded in a systematic way into a database. Databases usually consist of music coded in a particular way and the relevant metadata but can also consist of musical behavior or historical information about the sources.

The central benefits of database studies are transparency, impartiality, and generalizibility in comparison to the conventional music scholarship that usually operates using a few handpicked case examples. In database studies, transparency is achieved in the way databases are structured and through unambiguous definition of the fields and objects of databases. This allows the analyst to accurately define the objects of music that can be subjected to analysis. In principle, anyone can replicate the results of a database study using an identical set of retrieval commands and the database. In comparison with traditional music analysis, which values intuition, stylistic knowledge, and possibly subtle judgments about the aesthetic value of the analysis content, database studies can be considered to be more impartial in the analysis process. This is not to say that intuition and stylistic knowledge are not important in database studies but these need to be explicitly coded in the queries made for the database. Generalizibility of database studies refers to the possibility of identifying common factors in the music of a given collection due to the possibility of processing much larger samples of music than is possible in a conventional analysis.