SpaceTime: SpatioTemporal Data Exploration

There has been a meteoric rise in the use of spatiotemporal data in a variety of fields of science and engineering. The newfound ability to deploy sensor-rich vehicles, IoT devices, smart dust, and mobile phones at scale have empowered science and industry to collect unprecedented amounts of location-and-time-based data. Further, the computational ability to process and act on such scales of data has also seen massive improvements in the recent past. The combination of these trends has led to simultaneous technological revolutions in multiple areas of inquiry, such as smart city analytics, mobility data products, autonomous transport, insurance and safety, and precision agriculture. Project SpaceTime is a multi-institution, crosscutting, and interdisciplinary effort investigating the spatiotemporal data analysis and exploration challenges in these areas.


  • Behrooz Omidvar-Tehrani, Arnab Nandi, Seth Young, Nicholas Meyer, Dalton Flanagan: DV8: Interactive Analysis of Aviation Data, ICDE Demo, 2017
  • Sobhan Moosavi, Rajiv Ramnath, Arnab Nandi: Discovery of Driving Patterns by Trajectory Segmentation, ACM SIGSPATIAL PhD Symposium, 2016
  • Sobhan Moosavi, Behrooz Omidvar-Tehrani, R. Bruce Craig (Nationwide Insurance), Arnab Nandi, Rajiv Ramnath: Characterizing Driving Context from Driver Behavior, [preprint]
  • Mohamed Sarwat, Arnab Nandi: On designing a GeoViz-aware database system - Challenges and Opportunities, International Symposium on Spatio-Temporal Data (SSTD) 2017
  • Kayhan Moharerri, Dan Arters, Trey Hakanson, Andre Carrel, Arnab Nandi: Crossroads: A mobility analytics platform for car sharing providers and fleet managers, in preparation