How Do Observational Astronomers Learn to Inspect Imaging Data

Abstract

Astronomy is entering an unprecedented era of data collection. Upcoming large surveys will gather more data than ever before, generated at rates requiring real-time decision making. Looking ahead, it is inevitable that astronomers will need to rely more heavily on automated processes. Indeed, some instances have already arisen wherein the majority of the inspection process is automated. Visual discovery, performed traditionally by humans, is one key area where automation is now being integrated rapidly. Visual discovery comprises two aspects: (1) visual inspection, the skill associated with examining an image to identify areas or objects of interest; and (2) visual interpretation, the knowledge associated with the classification of the objects or features. Both skills and knowledge are vital for humans to perform visual discovery, however, there appears to have been limited investigation into how the skill of visual inspection in astronomy is acquired. We report on a survey of 70 professional observational astronomers, at various career stages and from different geographical regions. We found that between 63% and 73% of the astronomers surveyed had received formal and$/$or informal training in visual inspection of images, although formal training (21%) was less common than informal training (60%). Surprisingly, out of the 37% who did not recall having received training in visual inspection, 29% (20 astronomers) indicated that they provided training to others. This suggests the emergence of `expertise without precedent' where a first expert in the field provides a new way of achieving a task. These results, paired with a set of three pilot interviews, present a touchstone against which the training of future observational astronomers can be compared.