Integrating Geographical Information Systems and Grid
Applications Marlon Pierce
([email protected])[email protected] Contributions: Ahmet
Sayar, Galip Aydin, Mehmet Aktas, Harshawardhan Gadgil, Zhigang Qi
Community Grids Lab Indiana University Project Funding: NASA AIST,
ACCESS Slide 2 QuakeSim Project Overview QuakeSim is a NASA funded
collaboration of geophysicists and computer scientists to build
cyber-infrastructure for geophysical research. CI research and
development includes Portlet-based portals AJAX enabled
Geographical Information System services Application services to
run codes. Slide 3 QuakeSim Project Development Overview
Portlet-based portal components allow different portlets to be
exchanged between projects. Form-based portlets --> Interactive
Maps These are clients to Web services Share with collaborators of
REASoN portal. Sensor Grid: Topic based publish-subscribe systems
support operations on streaming data. Web services allow
request/response style access to data and codes. GIS services (WMS,
WFS) Execution grid services for running codes: RDAHMM, ST_Filter
Use application specific WSDL on top of generic code management
services. GPS daily archive Web Services provided by Scripps. Slide
4 Slide 5 Sensor Grid Overview Slide 6 SensorGrid architecture
supports access to both archived (databases), and real-time
geospatial data through universal GIS standards and Web Service
interfaces. The architecture provides tools for coupling geospatial
data with scientific data assimilation, analysis and visualization
codes, such as: Pattern Informatics Virtual California IEISS RDAHMM
Slide 7 Real-Time Services for GPS Observations Real-time data
processing is supported by employing filters around
publish/subscribe messaging system. The filters are small
applications extended from a generic Filter class to inherit
publish and subscribe capabilities. Input SignalOutput Signal
Filter Slide 8 Filter Chains Slide 9 NaradaBrokering Topics Slide
10 Real-Time positions on Google maps Slide 11 Real-Time Station
Position Changes Slide 12 RDAHMM + Real-Time GPS Integration Slide
13 Federating Map Servers Zao Liu, Marlon Pierce, Geoffrey Fox
Community Grids Laboratory Indiana University Slide 14 Integrating
Map Servers Geographical Information Systems combine online dynamic
maps and databases. Many GIS software packages exist GIS servers
around state of Indiana ESRI ArcIMS and ArcMap Server (Marion,
Vanderburgh, Hancock, Kosciusco, Huntington, Tippecanoe) Autodesk
MapGuide (Hamilton, Hendricks, Monroe, Wayne) WTH Mapserver Web
Mapping Application (Fulton, Cass, Daviess, City of Huntingburg)
based on several Open Source projects (Minnesota Map Server)
Challenge: make 17 different county map servers from different
companies work together. 92 counties in Indiana, so potentially 92
different map servers. Slide 15 Considerations We assume
heterogeneity in GIS map and feature servers. GIS services are
organized bottom-up rather than top-down. Local city governments,
92 different county governments, multiple Indiana state agencies,
inter-state (Ohio, Kentucky) consideration, federal government data
providers (Hazus). Must find a way to federate existing services.
We must reconcile ESRI, Autodesk, OGC, Google Map, and other
technical approaches. Must try to take advantage of Google, ESRI,
etc rather than compete. We must have good performance and
interactivity. Servers must respond quickly--launching queries to
20 different map servers is very inefficient. Clients should have
simplicity and interactivity of Google Maps and similar AJAX style
applications. Slide 16 Caching and Tiling Maps Federation through
caching: WMS and WFS resources are queried and results are stored
on the cache servers. WMS images are stored as tiles. These can be
assembled into new images on demand (c. f. Google Maps).
Projections and styling can be reconciled. We can store multiple
layers this way. We build adapters that can work with ESRI and OGC
products; tailor to specific counties. Serving images as tiles
Client programs obtain images directly from our tile server. That
is, dont go back to the original WMS for every request. Similar
approaches can be used to mediate WFS requests. This works with
Google Map-based clients. The tile server can re-cache and tile on
demand if tile sections are missing. Slide 17 Map Server Example
Marion and Hancock county parcel plots and IDs are overlaid on IU
aerial photographic images that are accessed by this mashup using
Google Map APIs. We cache and tile all the images from several
different map servers. (Marion and Hancock actually use different
commercial software.)
