Matt Testa and Andre Avorio, Building a Data Set of the Baltimore Symphony Orchestra’s Performance History

Since 2016, Matt Testa has been the archivist for the Arthur Friedheim Library at the Peabody Institute of the Johns Hopkins University, where he is responsible for special collections, institute records, digital preservation, and archival reference and instruction services. Previously, he held project archivist positions at the Music Division of the Library of Congress and at Special Collections in Performing Arts at the University of Maryland, College Park. Matt has an MA in musicology from McGill University and an MLS from the University of Maryland.

Event Timeslots (1)

Friday Program
-
This presentation will discuss a collaboration between the Baltimore Symphony Orchestra, the Peabody Institute's Arthur Friedheim Library, the Music Library Association's Atlantic Chapter, and the Open Music Library to create a publicly accessible data set of the BSO's performance history. This resource, now online but still in development, displays information about thousands of the orchestra’s public performances since 1967, including where and when the concerts took place, what pieces the orchestra played, and who performed as a conductor or soloist. Work on this project required a strategic approach to data normalization and many careful actions. Although project staff had access to an existing internal database of BSO performance data, refining more than 30,000 entries for consistency and usability proved to be challenging. Some fundamental questions had to be answered: What kinds of research questions would we want this data set to help answer? What fields would be most essential? What tools and techniques would be most efficient in standardizing a complex and messy data set? What could we learn from similar published data sets of other performing arts organizations? With an eye toward creating "good enough" data, we focused our attention on some of the most critical areas. This presentation will explore the materials, methods, and problems involved in the creation of this data set. It will also describe challenges for the next stages of the project and lessons learned that could be applied to similar projects.

Leave a Reply