Database Dramaturgy

“Theater as a Field of Cultural Production” picked up on some fruitful strains introduced by the Harrisons. Can we select our audiences, or does the location of theater determine our audience for us? Are some audiences more important or influential than others?This led to a natural discussion of the day's topic: data and databases. In any database construction, questions of hierarchy and relation inevitably arise. While our reading by Daniel Rosenberg drew an interesting distinction between data (from datum, “to give,” and so taken for granted), fact (from facere, “to do”, past actions that now exist as ontological truth), and evidence (from videre, “to see,” and thus an epistemological method), we argued that the distinctions are not as fixed. Data can become facts and facts can become data. As scholars, it is up to us to determine the moment of proof. We worried about the dangers of taking data as facts—what if everybody is wrong? We also discussed the possibilities and impossibilities of treating some of our scholarly evidence as data. How do we represent anecdotal or “human data,” like audience reaction? How do we account for non-text-based data and the ephemeral practices of performance, which can be difficult to hold in history? We talked a great deal about Google’s Ngram Viewer as a rough tool to prompt greater thought, rather than as data to be taken as proof. And we confronted the reality that even though popular culture may be enthralled with the idea of “big data,” we theater scholars are only working with “itsy bitsy data.”

Evidence for the triumph of performance, or bad data?
Evidence for the triumph of performance, or bad data?

Even so, itsy bitsy databases can take scholars many years to construct. We looked at The London Stage 1800-1900 and The Adelphi Theatre Project databases, which were built in 10 and 30 years, respectively. Participants discussed their own experiences building or using databases, from the Database of Early English Playbooks to the Internet Broadway Database. We highlighted the importance of constructing relational databases, where we consider location as a function of both place AND time. For some of us, venue is more important than the work being performed (say, the event of going to an early Loew’s cinema), while others would want to track the number of revivals of a specific work over time, or the pattern with which a specific work toured a regional or international circuit. We must be careful, in performing our “database dramaturgy,” to think about these relational questions from the beginning. Relational questions also take practical significance: how do we, as theater scholars, relate to those inside and outside our discipline to move database research forward? How do we institutionalize computational-skills acquisition and professional incentives for collaborative database projects?

See also: Matthew Franks