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CUAHSI Hydrologic Information System an introduction

CUAHSI Hydrologic Information System an introduction. Ilya Zaslavsky Director, Spatial Information Systems Lab San Diego Supercomputer Center University of California San Diego. Presentation at DID Data Management, Kuala Lumpur, Malaysia, July 24, 2009. San Diego Supercomputer Center.

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CUAHSI Hydrologic Information System an introduction

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  1. CUAHSI Hydrologic Information Systeman introduction Ilya Zaslavsky Director, Spatial Information Systems Lab San Diego Supercomputer Center University of California San Diego Presentation at DID Data Management, Kuala Lumpur, Malaysia, July 24, 2009

  2. San Diego Supercomputer Center SDSC building on UCSD campus Founded in 1985, as one of the five original supercomputer centers, funded by the National Science Foundation 400 employees Advanced research in high-performance computing and networking R&D and cyberinfrastructureprojects: in neuroscience, geology, astronomy, environmental sciences, molecular biology, hydrology

  3. Consortium of Universities for the Advancement of Hydrologic Science, Inc. 120+ US Universities An organization representing more than one hundred United States universities, receives support from the National Science Foundation to develop infrastructure and services for the advancement of hydrologic science and education in the U.S. http://www.cuahsi.org/

  4. What is CUAHSI HIS? CUAHSI HIS: NSF support through 2012 (GEO) Partners: Academic: 11 NSF hydrologic observatories, CEO:P projects, LTER… Government: USGS, EPA, NCDC, NWS, state and local Commercial: Microsoft, ESRI, Kisters International: Australia, UK Standardization: OGC, WMO (Hydrology Domain WG, CHy); adopted by USGS, NCDC An online distributed system to support the sharing of hydrologic data from multiple repositories and databases via standard water data service protocols; software for data publication, discovery, access and integration.

  5. Map for the US Build a common window on water data using web services Observation Stations Ameriflux Towers (NASA & DOE) NOAA Automated Surface Observing System USGS National Water Information System NOAA Climate Reference Network

  6. Water Data Water quantity and quality Soil water Rainfall & Snow Modeling Meteorology Remote sensing

  7. Sources of Observations Data

  8. Point Water Observations Time Series A point location in space A series of values in time

  9. Getting Water Data (the old way) Different Query Pages Different Query Responses

  10. Web Pages and Web Services http://www.safl.umn.edu/ Uses Hypertext Markup Language (HTML) Uses WaterML (a Markup Language for water data)

  11. HTML as a Web Language Text and Pictures in Web Browser HyperText Markup Language <title>Texas Water Development Board</title> <!DOCTYPE HTML PUBLIC "-//W3C//DTD HTML 4.01 Transitional//EN"> <html> <head> <meta name = "Robots" content = "index,follow"> <meta name = "Priority" content = "home,twdb,homepage"> <meta name = "Author" content = "Texas Water Development Board, Agency Number 580"> <meta name = "Title" content = "Texas Water Development Board"> <meta name = "Description" content = "Texas Water Development Board Home Page"> <meta name = "Keywords" content = "water,drought,rain,conservation,groundwater,surfacewater,lake,reservoir,hydrology,geology,desalination,TWDB,loans,grants,wastewater,sewage,Clean Water,DrinkingWater,State Revolving Fund,planning,State Water Plan,GIS,Geographic Information Systems,Mapping,data">

  12. WaterML as a Web Language Discharge of the San Marcos River at Luling, June 28 - July 18, 2002 Streamflow data in WaterML language

  13. Point Observations Information Model Utah State Univ Data Source WaterOneFlow Service Little Bear River Network GetSites Little Bear River at Mendon Rd Sites GetSiteInfo GetVariableInfo Dissolved Oxygen Variables GetValues 9.78 mg/L, 1 October 2007, 5PM Values {Value, Time, Metadata} • A data source operates an observation network • A network is a set of observation sites • A site is a point location where one or more variables are measured • A variable is a property describing the flow or quality of water • A value is an observation of a variable at a particular time • Metadata provide additional information about the value

  14. Site Codes Variable Codes Date Ranges WaterML and WaterOneFlow DEC Data GetSites GetSiteInfo GetVariableInfo GetValues UVM Data USGS Data WaterML Data Repositories WaterOneFlow Web Service Client EXTRACT TRANSFORM LOAD WaterML is an XML language for communicating water data WaterOneFlow is a set of web services based on WaterML

  15. Set of query functions Returns data in WaterML Standard Water Data Services Next Step: OGC-WMO Hydrology Domain Working Group: WaterML 2.0 https://lists.opengeospatial.org/mailman/listinfo/hydro.dwg http://external.opengis.org/twiki_public/bin/view/HydrologyDWG/WebHome Contact: IlyaZaslavsky, co-chair NWIS Daily Values (discharge), NWIS Ground Water, NWIS Unit Values (real time), NWIS Instantaneous Irregular Data, EPA STORET, NCDC ASOS, DAYMET, MODIS, NAM12K, USGS SNOTEL, ODM (multiple sites)

  16. Hydrologic Information System Service Oriented Architecture Test bed HIS Servers HIS Lite Servers Central HIS servers External data providers Global search (Hydroseek) Deployment to test beds Customizable web interface (DASH) Other popular online clients HTML - XML Desktop clients Data publishing HIS CentralRegistry & Harvester Water Data Web Services, WaterML WSDL - SOAP Ontology ETL services Controlled vocabularies Metadatacatalogs ArcGIS WSDL and ODM registration Matlab IDL, R Ontology tagging (Hydrotagger) Excel ODM DataLoader Programming (C#, VB..) Streaming Data Loading MapWindow ODMTools HISDesktop Modeling (OpenMI) Server config tools

  17. Central HIS Data Services Catalog

  18. Semantic Tagging of Harvested Variables

  19. Hydroseekhttp://www.hydroseek.net Supports search by location and type of data across multiple observation networks including NWIS, Storet, and academic data

  20. Against the NIH Syndrome 2006: CUAHSI HIS web services are discussed on the BASINS mailing list as a new way to access hydrologic data. The list is mostly used by hydrologists and developers outside academia; NCDC develops ASOS web services following WaterML 2007: MOU with USGS; USGS is developing WaterML-compliant GetValues service; GLEON uses an early version of ODM to develop their own schema (VEGA); Phoenix LTER is developing ODM (in MySQL) and WaterML services (in Java); A Google Earth-based client for CUAHSI web services is developed at CSIRO, Australia; Deployment to 11 hydrologic observatory test beds, + CBEO (CEOP project) 2008-2009: KISTERS develops WaterML-compliant web services over their database; Workshops at state agencies MapWindow open source GIS develops WaterOneFlow parsers; Florida, Texas and Idaho use ODM and WaterOneFlow web services to provide access to state data repositories; New Jersey is considering the same; Another CEOP project, at UC-Davis, is implementing ODM (in Postgres) and web services (in Java); Stroud Water Research Center; WRON; CZO; … many that we don’t know… Now SBRP: data from UCSD, UA, more? Integration with streaming data middleware (Open Source Data Turbine)

  21. The International Workshop on Hydrologic Data Management and Modeling in South East AsiaJuly 20-24University of Malaya Learning how the system works Publishing hydrologic data Setting up a server for SEA Already published: sample data from JPS (Malaysia) and from Indonesia

  22. Data published as web service: http://svctag-2z3322s/jps/cuahsi_1_0.asmx These are results of GetValues for JPS:3116434, Streamflow data In HydroExcel

  23. Charts of the same data In HydroExcel

  24. Area of interest In HydroSeek

  25. Finding JPS stations In HydroSeek

  26. More information about JPS stations In HydroSeek, and data download

  27. JPS data downloaded from HydroSeek

  28. Zooming in on Indonesia

  29. Looking for COD measurements In HydroSeek

  30. Zooming in to stations

  31. Summary • CUAHSI HIS = Cyberinfrastructurefor managing and publishing observational data • Supports many types of point observational data • Overcomes syntactic and semantic heterogeneity using a standard data model and controlled vocabularies • Supports a national network of observatory test beds • Maintains national registry of services (1.75 million stations – the largest in the world) • WaterML is a standard language for consistently communicating water observations data from academic and government sources using web services; already adopted by several federal agencies. Joint WMO and OGC activity to enhance it. • The system is already deployed at multiple locations • It is free and open source

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