Title: Sports stars: analyzing the performance of astronomers at visualization-based discovery,
Abstract: In this data-rich era of astronomy, there is a growing reliance on automated
techniques to discover new knowledge. The role of the astronomer may change
from being a discoverer to being a confirmer. But what do astronomers actually
look at when they distinguish between "sources" and "noise?" What are the
differences between novice and expert astronomers when it comes to visual-based
discovery? Can we identify elite talent or coach astronomers to maximize their
potential for discovery? By looking to the field of sports performance
analysis, we consider an established, domain-wide approach, where the expertise
of the viewer (i.e. a member of the coaching team) plays a crucial role in
identifying and determining the subtle features of gameplay that provide a
winning advantage. As an initial case study, we investigate whether the
SportsCode performance analysis software can be used to understand and document
how an experienced HI astronomer makes discoveries in spectral data cubes. We
find that the process of timeline-based coding can be applied to spectral cube
data by mapping spectral channels to frames within a movie. SportsCode provides
a range of easy to use methods for annotation, including feature-based codes
and labels, text annotations associated with codes, and image-based drawing.
The outputs, including instance movies that are uniquely associated with coded
events, provide the basis for a training program or team-based analysis that
could be used in unison with discipline specific analysis software. In this
coordinated approach to visualization and analysis, SportsCode can act as a
visual notebook, recording the insight and decisions in partnership with
established analysis methods. Alternatively, in situ annotation and coding of
features would be a valuable addition to existing and future visualisation and
analysis packages.