Transcript Slide 1
Some notes on CyberGIS in hydrology
Ilya Zaslavsky Spatial Information Systems Lab San Diego Supercomputer Center UCSD TeraGrid CyberGIS Workshop, February 2-3, 2010
What is the CUAHSI HIS?
UT-Austin, SDSC/UCSD, Utah State U, Idaho State U, Drexel U, U of So. Carolina PI: D. R. Maidment (UT-Austin)
CUAHSI HIS
: NSF support through 2012 (GEO) An online distributed system to support the sharing of hydrologic data repositories and databases via standard water data service from multiple protocols; software for data publication, discovery, access and integration .
Partners: Academic
: 11 NSF hydrologic observatories, CEO:P projects, LTER, CZO…
Government
: USGS, EPA, NCDC, NWS, state and local
Commercial
: Microsoft, ESRI, Kisters
International
: Australia, UK
Standardization
: OGC, WMO (Hydrology Domain WG); adopted by USGS, NCDC, Army Corps of Eng
Hydrologic Information System Service Oriented Architecture
Global search (Hydroseek)
Deployment to test beds
Customizable web interface (DASH) Other popular online clients Data publishing HIS Central Registry & Harvester
HTML - XML Water Data Web Services, WaterML Test bed HIS Servers WSDL and ODM registration Ontology tagging (Hydrotagger) ODM DataLoader Streaming Data Loading ODMTools Server config tools HIS Lite Servers Central HIS servers External data providers
Desktop clients
ArcGIS Matlab IDL, R Excel Programming (C#, VB..) MapWindow Modeling (OpenMI)
CUAHSI Water Data Services
47 services 15,000 variables 1.8 million sites 9 million series 4.3 billion data values
Map Integrating NWIS, STORET, & Climatic Sites
The largest water data catalog in the world
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International Standardization of WaterML
OGC/WMO Hydrology Domain Working Group
http://external.opengis.org/twiki_public/bin/view/HydrologyDWG/WebHome Towards an agreed upon By organizing - feature model Expressed as
WaterML 2.0
- observations model - semantics - Interoperability Experiments and pilots, standard design activities, webinars…
First OGC/WMO HydroDWG workshop : at Ispra, Italy, March 15-18, 2010
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Why CyberGIS
Some critical CI issues we encountered – Efficient management of large volumes of distributed spatio-temporal data – Understanding and unifying data models across sub-domains of water – – Development of data exchange standards Community ontology management and curation When one writes a CyberGIScience proposal for hydrology… – Intellectual merit: reconciling different notions of space and time in a field that describes water dynamics – Broad impact: spatial data integration at a scale where critical mass is achieved fast, which makes it beneficial to broader multidisciplinary group of stakeholders, and thus sustainable – Transformative: large distributed data interfaced with models, and coupled with provenance management resulting in a different rate and quality of simulations, larger models, and better decision-making