Dunham's Data Series

Dunham’s Data: Digital Methods for Dance Historical Inquiry is a three-year initiative (2018-2021) funded by the United Kingdom Arts and Humanities Research Council and led by Kate Elswit (Royal Central School of Speech and Drama, University of London) and Harmony Bench (The Ohio State University). The project explores questions and problems that make the analysis and visualization of data meaningful for dance history through the case study of choreographer Katherine Dunham and is part of a larger suite of ongoing collaborations by Bench and Elswit, Movement on the Move.

Building on the analogue and early digital methodological precursors for tracking historical itineraries, the Dunham’s Data team manually compiled their data from many undigitized archival materials at Southern Illinois University at Carbondale, the Missouri Historical Society, and the Library of Congress, among other sources, documenting Dunham’s daily whereabouts, the works in her repertory, and the people she employed. The data was routinely cross-referenced and reconciled with the information obtained from Dunham’s personal and professional correspondence, contracts, and company documents including receipt books, payroll, costume lists, personal logs, programs, scrapbooks, lighting plots, and newspaper clippings. Additional supplemental data sources such as immigration records, local newspapers, and historical transportation maps and schedules were also used in constructing the datasets. 

At present, Dunham’s Data represents over 5000 days from 1947–60 that Dunham spent in approximately 190 unique cities, 189 performers who traveled with her, and 166 pieces of active repertory in various configurations during that time.

The first public-use dataset from Dunham’s Data is a manually curated Everyday Itinerary of Katherine Dunham’s touring and travel (98% of the days), with 134 trips to 83 cities across five continents (hotels and performance venues are included, whenever possible). In the second phase, Dunham’s Data will expand the Everyday Itinerary to 1947–60, which will be released as an update.

The Check-In dataset, the second dataset in the series, accounts for the comings and goings of Dunham’s dancers, drummers, and singers over time. The dataset discerns who among the nearly 200 performers were in the studio and theatre together over the fourteen years from 1947 to 1960.  As with the Everyday Itinerary, data on check-ins come from scattered sources. While the Check-In dataset is developed in tandem with information from the Everyday Itinerary dataset, and vice versa, due to information available, there is a greater level of ambiguity in the Check-In dataset and many dates are approximated in order to achieve chronology. By showing who shared time and space together, the Check-In dataset can be used to trace potential lines of transmission of embodied knowledge within and beyond the Dunham Company.

The Repertory dataset is the third dataset in the series. It concerns Dunham’s repertory, and catalogues the various titles and descriptions by which a piece might be known, the years in which it was performed, and all of the singers, dancers, and drummers who were listed as performing in it. The Repertory dataset documents other aspects of each work such as composers of the music, the varying numbers of performers, places of inspiration where available, and whether pieces were performed in concert venues, nightclubs, or both. It also tracks fluid relationships among nearly 300 numbers identified in Dunham’s repertory from the 1930s onwards by examining the various scales at which Dunham repurposed choreographic elements over time and for different performance venues, and therefore the alternative ways that works might connect individual performers.

The Check-In and Repertory datasets will be released through 2021.

In addition to Kate Elswit and Harmony Bench, the Dunham’s Data team includes digital humanities postdoctoral research assistant Antonio Jimenez Mavillard and dance history postdoctoral research assistants Takiyah Nur Amin and Tia-Monique Uzor.

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