This article describes Daphne, a virtual assistant for designing Earth observation distributed spacecraft missions. It is, to the best of our knowledge, the first virtual assistant for such application. The article provides a thorough description of Daphne, including its question answering system and the main features we have implemented to help system engineers design distributed spacecraft missions. In addition, the article describes a study performed at NASA's Jet Propulsion Laboratory (JPL) to assess the usefulness of Daphne in this use case. The study was conducted with N = 9 subjects from JPL, who were asked to work on a mission design task with two versions of Daphne, one that was fully featured implementing the cognitive assistance functions, and one that only had the features one would find in a traditional design space exploration tool. After the task, they filled out a standard user experience survey, completed a test to assess how much they learned about the task, and were asked a number of questions in a semi-structured exit interview. Results of the study suggest that Daphne can help improve performance during system design tasks compared to traditional tools, while keeping the system usable. However, the study also raises some concerns with respect to a potential reduction in human learning due to the use of the cognitive assistant. The article ends with a list of suggestions for future development of virtual assistants for space mission design. Index Terms-Distributed spacecraft missions, earth observation, machine learning, mixed initiative, virtual assistant. I. INTRODUCTION M OTIVATED by the challenges of system architecture in general and architecting distributed satellite missions (DSM) in particular, and inspired by the success of commercial virtual assistants (VA), such as Siri, Google Assistant, Alexa, or Mycroft, we have developed Daphne, the first VA-to the best of our knowledge-to support the high-level design of DSM. This article describes how Daphne can be used to design DSM and includes a quantitative validation study performed at NASA JPL where the test subjects had expertise in mission design. The contribution of this article is two fold. First, we introduce Daphne as a complete, open-source package for DSM tradespace analysis that includes the standard VA functionality, such as Manuscript
