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Autonomous unmanned aerial vehicles are complex systems of hardware,software, and human input. Understanding this complexity is key to theirdevelopment and operation. Information visualizations already exist forexploring flight logs but comprehensive analyses currently require severaldisparate and custom tools. This design study helps address the pain pointsfaced by autonomous unmanned aerial vehicle developers and operators. Wecontribute: a spiral development process model for grounded evaluationvisualization development focused on progressively broadening target userinvolvement and refining user goals; a demonstration of the model as part ofdeveloping a deployed and adopted visualization system; a data and taskabstraction for developers and operators performing post-flight analysis ofautonomous unmanned aerial vehicle logs; the design and implementation of DATACOMETS, an open-source and web-based interactive visualization tool forpost-flight log analysis incorporating temporal, geospatial, and multivariatedata; and the results of a summative evaluation of the visualization system andour abstractions based on in-the-wild usage. A free copy of this paper andsource code are available at osf.io/h4p7g

Data Comets: Designing a Visualization Tool for Analyzing Autonomous Aerial Vehicle Logs with Grounded Evaluation