  Autonomous unmanned aerial vehicles are complex systems of hardware,
software, and human input. Understanding this complexity is key to their
development and operation. Information visualizations already exist for
exploring flight logs but comprehensive analyses currently require several
disparate and custom tools. This design study helps address the pain points
faced by autonomous unmanned aerial vehicle developers and operators. We
contribute: a spiral development process model for grounded evaluation
visualization development focused on progressively broadening target user
involvement and refining user goals; a demonstration of the model as part of
developing a deployed and adopted visualization system; a data and task
abstraction for developers and operators performing post-flight analysis of
autonomous unmanned aerial vehicle logs; the design and implementation of DATA
COMETS, an open-source and web-based interactive visualization tool for
post-flight log analysis incorporating temporal, geospatial, and multivariate
data; and the results of a summative evaluation of the visualization system and
our abstractions based on in-the-wild usage. A free copy of this paper and
source code are available at osf.io/h4p7g
