Panelist: Shashi Shekhar McKnight Distinguished Uninversity Professor University of Minnesota www.cs.umn.edu/~shekhar 4147 Cyber-Infrastructure (CI) Panel, AAG 2008 Outline What is Cyber Infrastructure (CI) ? How CI relates to your research/development ? Vision and plan you have on CI What role do you see for the new CI Specialty Group? Any other information you want to share with the audience
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Panelist: Shashi Shekhar
McKnight Distinguished Uninversity ProfessorUniversity of Minnesota
www.cs.umn.edu/~shekhar
4147 Cyber-Infrastructure (CI) Panel, AAG 2008
OutlineWhat is Cyber Infrastructure (CI) ?How CI relates to your research/development ?Vision and plan you have on CIWhat role do you see for the new CI Specialty Group? Any other information you want to share with the audience
What is Cyber Infra-structure (CI)?
“… new research environments that support advanced (spatial) data acquisition, data storage, (spatial) data management, (spatial) data integration, (spatial) data mining, (spatial) data visualization and other (spatial) computing and (spatial) information processing services over the Internet.”
“… technological solution to the problem of efficiently connecting data, computers, and people with the goal of enabling derivation of novel scientific theories and knowledge.”
Q? Is Geography enabling technology or domain science ?
NSF CI Vision 2007, NSF Blue Ribbon Committee 2003, …(a) HPC(b) Data, e.g. DataNet, InterOP( c) Virtual Organization, e.g. VOS(d) Learning Workforce Development
Related initiatives include CDI
2A. CI Research & Development : Spatial Databases
only in old plan
Only in new plan
In both plans
Evacutation Route Planning
Parallelize Range Queries
Storing graphs in disk blocksShortest Paths
2B. CI Research & Development : Spatial Data Mining
Nest locations Distance to open water
Vegetation durability Water depth
Location prediction: nesting sites Spatial outliers: sensor (#9) on I-35
Co-location Patterns Tele connections
3a. Vision and plan you have on CI
Advance Domain Science Computational methods = Third leg of modern science (w/ theory and experiments)
Bring to life theoretical models of phenomena too complex, costly, hazardous, vast or
small for experiments
Advance C.I. , e.g. Spatial Databases, Spatial Data Mining
Characterize computational structure
Pattern families, interest measures, computational cost, …
Representations, data-structures, algorithms, …
Example: Evacuation Route Planning Domain contribution: Walking > Driving for 1-mile radius areas
Computer Science: Scalable algorithm (i.e. CCRP)
Orders of magnitude faster than competition!
3b. Vision: Towards Spatio-temporal
• An Inconvenient Truth– Global datasets at many different timeslots– Wouldn’t it be a popular CI tool for scientists ?
• Teleconnection– Find (land location, ocean location) pairs with correlated climate changes
• Ex. El Nino affects climate at many land locations
Global Influence of El Nino during the Northern Hemisphere Winter(D: Dry, W: Warm, R: Rainfall)
Average Monthly Temperature
(Courtsey: NASA, Prof. V. Kumar)
4a. What role do you see for the new CI Specialty Group?
Build bridge between GIS and CI communitiesWhy challenges/opportunities does CI provide to Geography researchers ?Why challenges/opportunities does Geography provide to CI researchers ?
NSF Programs seeking input to shape CDI and other OCI programs
Computing Research Associates: RFP for grants to organize Visioning Workshops
Q? Should AAG/CI group engage in these initiatives ?- Geography as an enabling technology for other domains, e.g. Epidemiology- Unique CI needs, e.g. Spatio-temporal Google Earth
SDM: Opportunities for Computer Science
Nest locationsDistance to open water
Vegetation durability Water depth
Computational Challenges from Auto-correlation
Classical Linear Regression Low
Spatial Auto-Regression High
Name ModelClassification Accuracy
εx βy
εxβWyy ρ
framework spatialover matrix odneighborho -by- :
parameter n)correlatio-(auto regression-auto spatial the:
nnW
Computational Challenge: Computing determinant of a very large matrix in the Maximum Likelihood Function:
SSEnn
L 2
)ln(
2
)2ln(ln)ln(
2WI
1. Encyclopedia of GIS, Springer, 2008 - Provides a computational perspective - Many articles relate to C.I. topics - Many libraries have paper and electronic copies!
Any other information you want to share with the audience
2. GeoInformatica: An Intl. Journal on Advances in Computer Science for GIS- Articles on CI advances motivated by GIS are welcome!
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