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Spatial Data Management Lab


The Spatial Data Management Lab is directed by Chang-Tien Lu in the Department of Computer Science. Here, Lu and his team explore the emerging requirements for storing, analyzing, exchanging, and disseminating spatial and spatio-temporal data in many geospatial applications, ranging from general management such as indexing structure, query processing, and concurrency control, to more specific applications that deal with data analysis and knowledge discovery tasks like transportation visualization, watershed monitoring, disease outbreak analysis, geospatial web service, and web usage mining.  

Their goal is to develop new ways of managing and exchanging spatial and temporal data; perform spatial-temporal data visualization and analysis; and discover underlying knowledge from various and distributed data sources.

Research at the Spatial Data Management Lab has not only resulted in high quality research papers and demos, but also helped professionals in many fields — including transportation managers and watershed engineers — to respond more efficiently and make more effective decisions.


Following are some of the labs projects and partners:

  • Intelligent Threat Detection in Geospatial Contexts -- Army Corps of Engineers

  • Advanced Analytics for High-Performance Metro Security Monitoring -- WMATA

  • Early Detection of Proliferation Activities Using Open Source Indicators -- Dept. of Energy

  • Technology Monitoring and Forecasting for JIDO -- Department of Defense, 

  • Cost-Effective Semi-Automated Identification, Classification, and Coding of Significant Societal Events -- IARPA

  • Forecasting Transformative Technologies using Big Data -- Department of Defense

  • Advanced Analytics for Trustworthy Storytelling -- Army Research Office

  • Cyber and Advanced Data Analytics and Processing -- Northrop Grumman

  • SAFE: SIGINT-based Anticipation of Future Events -- IARPA 

  • Pythia: Anticipatory Intelligence from Open Source Indicators -- US Government 

  • Automated Sense-making for Massive Spatio-Temporal Attributed Data -- Army Research Office

  • Advanced Analytics for ITS -- District Department of Transportation

  • ITS Technical Support for System Integration: Tunnel-Operation Dynamic Messages, Mobile CCTV, Traffic Data Analysis and Visualization -- District Department of Transportation

  • Game-Aided Pedagogy to Improve Students' Learning Outcomes and Engagement in Transportation Engineering -- National Science Foundation

  • EMBERS: Early Model Based Event Recognition using Surrogates -- Intelligence Advanced Research Projects Activity (IARPA)

Graduate Student Research

The Spatial Data Management Lab provides invaluable research opportunities for master’s degree and Ph.D. students in the computer science program. In addition, frequent lab-sponsored seminars promote multidisciplinary participation and discussion, providing different perspectives to finding solutions. Many graduates who have worked in the lab have gone on to research and development positions at prestigious institutes and professor appointments at colleges and universities across the country.

For more information contact: 

Chang -Tien Lu