1. GeoSpatial and GeoTemporal Informatics for dynamic and complex systems May Yuan

3. What is solved Integration of spatial and temporal data –Location and snapshot –Dimensional, typological, and typological issues Empirical and computational solutions –Spatiotemporal statistics / time geography –Spatial data mining –Machine learning and artificial intelligence –Cellular automata –Agent-based modeling –Evolutionary algorithms

4. What is almost solved? Refined observation networks and data assimilation –Smart sensor networks –Adaptive sensor networks –Data-model assimilation Refined statistical and modeling approach to account for geographic dynamics and complexity –Data stream mining –Intelligent agents –Geographically aware agents –Adaptive agents

5. What has failed? Include surprised failures Fail is a strong word. Perhaps, appears limited Space-time composite model Intelligent highways Integration of sensor networks across scales (local, regional, and global) to automatically relate phenomena and processes across scales Communication among heterogeneous networks –Climate –Ecology –hydrology

6. What is missing (discuss areas not currently on the radar) From space-time observations to spatiotemporal processes Informatics framework to automate recognition of events and processes Analysis of events and processes –Weather (obs > events > systems > severity) –Population (obs > migration > gentrification) state process spatiotemporal data event measured by sensors trigger drive

7. What next? Include both high risk and needed topics P2P sensor networks Informatics Theory of Geographic Dynamics and Complexity Ontology Representation: flows, vector fields Analytical and computational approaches that address multi-scalar relationships among observations, geographic dynamics, and geographic systems Modeling approaches to address interactions among dynamics of different kinds across scales and domains –Climate and ecology –Politics and sociology –Climate and society –New levels of knowledge representation –Aggregates, agglomerates, and narratives

8. By telling and listening to stories, we communicate, learn, and make sense of the world by ordering events and assimilating them to find meanings and implications (Mateas and Sengers 2003). Narrative GIS that can tell stories Visual means to tell stories Narratives and sensing making