  High-quality, usable, and effective software is essential for supporting
astronomers in the discovery-focused tasks of data analysis and visualisation.
As the volume, and perhaps more crucially, the velocity of astronomical data
grows, the role of the astronomer is changing. There is now an increased
reliance on automated and autonomous discovery and decision-making workflows
rather than visual inspection. We assert the need for an improved understanding
of how astronomers (humans) currently make visual discoveries from data. This
insight is a critical element for the future design, development and effective
use of cyber-human discovery systems, where astronomers work in close
collaboration with automated systems to gain understanding from continuous,
real-time data streams. We discuss how relevant human performance data could be
gathered, specifically targeting the domains of expertise and skill at visual
discovery, and the identification and management of cognitive factors. By
looking to other disciplines where human performance is assessed and measured,
we propose four early-stage applications that would: (1) allow astronomers to
evaluate, and potentially improve, their own visual discovery skills; (2)
support just-in-time coaching; (3) enable talent identification; and (4) result
in user interfaces that automatically respond to skill level and cognitive
state. Throughout, we advocate for the importance of user studies and the
incorporation of participatory design and co-design practices into the
planning, implementation and evaluation of alternative user interfaces and
visual discovery environments.
