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Visual analytics systems can greatly help in the analysis of urban data allowing domain experts from academia and city governments to better understand cities, and thus enable better operations, informed planning and policies. Effectively designing these systems is challenging and requires bringing together methods from different domains. In this paper, we discuss the challenges involved in designing a visual analytics system to interactively explore large spatio-temporal data sets and give an overview of our research that combines visualization and data management to tackle these challenges. [ABSTRACT FROM AUTHOR]

Major League Baseball (MLB) has a long history of providing detailed, high-quality data, leading to a tremendous surge in sports analytics research in recent years. In 2015, MLB.com released the StatCast spatiotemporal data-tracking system, which has been used in approximately 2,500 games since its inception to capture player and ball locations as well as semantically meaningful game events. This article presents a visualization and analytics infrastructure to help query and facilitate the analysis of this new tracking data. The goal is to go beyond descriptive statistics of individual plays, allowing analysts to study diverse collections of games and game events. The proposed system enables the exploration of the data using a simple querying interface and a set of flexible interactive visualization tools. [ABSTRACT FROM AUTHOR]