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High-quality, usable, and effective software is essential for supportingastronomers in the discovery-focused tasks of data analysis and visualisation.As the volume, and perhaps more crucially, the velocity of astronomical datagrows, the role of the astronomer is changing. There is now an increasedreliance on automated and autonomous discovery and decision-making workflowsrather than visual inspection. We assert the need for an improved understandingof how astronomers (humans) currently make visual discoveries from data. Thisinsight is a critical element for the future design, development and effectiveuse of cyber-human discovery systems, where astronomers work in closecollaboration with automated systems to gain understanding from continuous,real-time data streams. We discuss how relevant human performance data could begathered, specifically targeting the domains of expertise and skill at visualdiscovery, and the identification and management of cognitive factors. Bylooking to other disciplines where human performance is assessed and measured,we propose four early-stage applications that would: (1) allow astronomers toevaluate, and potentially improve, their own visual discovery skills; (2)support just-in-time coaching; (3) enable talent identification; and (4) resultin user interfaces that automatically respond to skill level and cognitivestate. Throughout, we advocate for the importance of user studies and theincorporation of participatory design and co-design practices into theplanning, implementation and evaluation of alternative user interfaces andvisual discovery environments.

Understanding the human in the design of cyber-human discovery systems for data-driven astronomy