🤖 AI Summary
This study addresses the lack of a systematic research framework in ubiquitous analytics, which hinders effective responses to the risks of design ossification arising from the convergence of spatial computing and generative AI. To bridge this gap, the work proposes the first structured research framework encompassing seven core dimensions: cognition, context, interaction, platform, visualization, collaboration, and evaluation. It maps the scholarly lineage of the field and articulates 42 cross-dimensional future challenges. By integrating spatial operating systems (e.g., visionOS, Horizon OS, Android XR), wearable devices, agentic AI, and open web standards, the paper establishes foundational theoretical principles and a comprehensive research roadmap, offering systematic guidance for open, empirically driven human-AI collaborative data analysis.
📝 Abstract
Spatial computing, generative AI, and open web standards are converging. Three spatial operating systems -- Android XR, Meta Horizon OS, and Apple visionOS -- now ship with platform-level scene understanding. Wearable displays span the range from full headsets to slim smartglasses. Agentic AI operates on the same spatial substrates as the human user. This convergence enables new opportunities for \textit{ubiquitous analytics} (UA): the use of many, physically distributed, networked devices to support data sensemaking anytime and anywhere. But proprietary platforms are settling design conventions that will calcify without evidence-based alternatives. UA has now matured to the point where its intellectual history can be read as a structured genealogy of foundations, contributions, and lineages. We trace this genealogy and organize it into clusters spanning cognition, context, interaction, platforms, visualization, collaboration, and evaluation. Finally, we cross these clusters with each other, yielding a total of 42 future research challenges.