In the public transportation system, punctuality benefits both bus operation and passengers’ travel experience. However, uncertainty exists due to complex traffic conditions and heterogeneous driving behaviors. To analyze bus operational uncertainty, transport planners and bus operators need a tool that supports multi-granular modeling, spatio-temporal representation, and interactive exploration. To meet the requirement, we present MetroBUX, a visual analytics system for$B$us operational$U$ncertainty e$X$ploration. MetroBUX aligns daily bus trips and models stop-level uncertainty of bus arrival time. It has a consolidated interface with three main views: Map View for presenting the spatial distribution of uncertainty, Temporal View for tracking the evolution of uncertainty, and Trip View for inspecting uncertainty propagation. Specifically, MetroBUX enables integrated spatio-temporal analysis by connecting topological uncertainty distribution at different periods in a nested tracking graph. Furthermore, it supports interactive and hierarchical exploration, including region-, route-, trip-, and stop-level analysis. Case studies on real-world bus operational data and domain experts’ feedback demonstrate the efficiency of MetroBUX.

Multiple-view (MV) visualizations have become ubiquitous for visual communication and exploratory data visualization. However, most existing MV visualizations are designed for the desktop, which can be unsuitable for the continuously evolving displays of varying screen sizes. In this article, we present a two-stage adaptation framework that supports the automated retargeting and semi-automated tailoring of a desktop MV visualization for rendering on devices with displays of varying sizes. First, we cast layout retargeting as an optimization problem and propose a simulated annealing technique that can automatically preserve the layout of multiple views. Second, we enable fine-tuning for the visual appearance of each view, using a rule-based auto configuration method complemented with an interactive interface for chart-oriented encoding adjustment. To demonstrate the feasibility and expressivity of our proposed approach, we present a gallery of MV visualizations that have been adapted from the desktop to small displays. We also report the result of a user study comparing visualizations generated using our approach with those by existing methods. The outcome indicates that the participants generally prefer visualizations generated using our approach and find them to be easier to use.