2. (Geo) Informatics across Disciplines!

3. Why Geo-Spatial Computing? Societal: Google Earth, Google Maps, Navigation, location-based service Global Challenges facing humanity – many are geo-spatial! Future of Computer Science (CS) is to address societal challenges! Intellectual Challenges CS assumptions, opporunities for new research Ex. Shortest path problem – What algorithms are common today? Are these correct if edge travel-times is not fixed (e.g. rush-hour, non-rush-hour)? Is Dynamic Programming correct for spatio-temporal problems? Ex. Classical Data Mining, e.g. Decision trees, Association Rules, Regression, … Are these effective for spatial data? ACM SIGSPATIAL Special interest group started in 2008 to bring computer scientists together Annual Conference: ACM GIS Journals GeoInformatica: An Intl. Jr. on Advances in Computer Science for GIS

4. Shashi Shekhar Mcknight Distinguished University Professor URLs : www.cs.umn.edu/ ~shekhar Area: Spatial Databases, Spatial Data Mining, Geographic Info. Systems Teaching: Fall 2010: Csci 5980: Computational Geo-Informatics (link)link Spring 2010: Csci 5708: Database Systems 2010-2011: Csci 8715: Spatial Databases Books, Surveys, etc.: Developing a book on spatial and spatio-temporal data mining Textbook, Encyclopedia, …

5. Research Group: Spatial Database, Data Mining, GIS URLs : www.spatial.cs.umn.edu Weekly Meetings: www.spatial.cs.umn.edu/schedule.html Current Projects: NSF: CRI:IAD Infrastructure for Research in Spatio-Temporal and Context-Aware Systems … NSF: III-CXT: Spatio-temporal Graph Databases for Transportation Science NSF: IGERT: Non-equilibrium Dynamics Across Space and Time NSF: Expedition: Understanding Climate Change: A Data Driven Approach USDOD: Spatio-Temporal Pattern Mining for Multi-Juris. Multi-Temporal Activity Datasets USDOD: Dynamic Purpose-Aware Graph Models for Composite Networks USDOD: Cascase Models for Multi-Scale Spatio-temporal Pattern Discovery Current Ph.D. Students: Pradeep Mohan Mike Evans Dev Oliver Xun Zhou KwangSoo Yang Abdussalam Bannur Viswanath Gunturi Zhe Xiang

6. Spatial Databases: Representative Projects only in old plan Only in new plan In both plans Evacutation Route Planning Parallelize Range Queries Storing graphs in disk blocksShortest Paths

7. Spatial Data Mining : Representative Projects Nest locationsDistance to open water Vegetation durability Water depth Location prediction: nesting sitesSpatial outliers: sensor (#9) on I-35Co-location PatternsTele connections

8. Spatio-Temporal (ST) Questions How do we conceptualize spatio-temporal (ST) worlds? How do we measure ST concepts, recognize them in (remotely) sensed information or in the field, and identify their accuracy and quality? How do we represent ST concepts with incomplete/ uncertain information, with alternative data models, and possibly with multiple representations for the same data, in digital environments? How do we store, access, and transform ST concepts, facilitating data sharing, data transfer, and data archiving, while ensuring minimum information loss? How do we explain ST phenomena through the application of appropriate methods of forward or inverse models of physical and human processes? How do we visualize ST concepts on a variety of media such as maps on electronic displays or animated displays ? How do we use ST concepts to think about spatio-temporal phenomena, and to seek explanations for spatio-temporal patterns and phenomena? Source: Adaptation from NCGIA proposal to NSF by Goodchild et al.