The Digital Production Lab in John C. Hodges Library at the University of Tennessee, like many university imaging studios, has long relied on a seasonal and temporary labor force drawn from our student body. Improving human-computer interaction in our production workflows should reduce training time and errors while increasing throughput and worker confidence. In this paper, we present our on-going efforts adapting Elgato's Stream Deck XL hardware to control a computer running Apple's macOS operating system and Phase One's Capture One Pro software using Python and AppleScript code. The paper outlines our custom code linking these parts together, describes how this relatively inexpensive input device streamlines our digitization process, and includes ideas for future application.
Don Williams, Peter D. Burns, "Refining the Theory-to-Practice Path for FADGI Still Imaging" in Proc. IS&T Archiving 2020, 2020, pp 39 - 42, https://doi.org/10.2352/issn.2168-3204.2020.1.0.39