1. Hydrologic Information System for the Nation I. Zaslavsky (SDSC) & The CUAHSI HIS Project his.cuahsi.org, hiscentral.cuahsi.org

2. Consortium of Universities for the Advancement of Hydrologic Science, Inc. 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/ 122 US Universities as of July 2008

3. Databases Analysis Models CUAHSI Hydrologic Information System Goal: Enhance hydrologic science by facilitating user access to more and better data for testing hypotheses and analyzing processes Advancement of water science is critically dependent on integration of water information –Querying nation’s repository of water data –Linking small integrated research sites (<100 km2) with global and continental models –Integrating data from multiple disciplines to understand controls on hydrologic cycle It is as important to represent hydrologic environments precisely with data as it is to represent hydrologic processes with equations Rainfall & Snow Water quantity and quality Remote sensing Meteorology Soil water

4. What is the CUAHSI HIS? An internet based system to support the sharing of hydrologic data comprising databases connected using the internet through web services as well as software for data discovery, access and publication.

5. Project co-PI in Phase 2 Collaborator in Phase I CUAHSI HIS Partner Institutions

6. HIS WATERS Testbed CUAHSI Hydrologic Information System (HIS) NSF has funded work at 11 testbed sites, each with its own science agenda. HIS supplies the common information system

7. Super computer Centers: NCSA, TACC Domain Sciences: Unidata, NCAR LTER, GEON Government: USGS, EPA, NCDC, USDA Industry: ESRI, Kisters, OpenMI HIS Team WATERS Testbed WATERS Network Information System CUAHSI HIS International Partners CSIRO Land and Water Resources Water Resources Observations Network (WRON) European Commission Water database design and model integration (HarmonIT and OpenMI)

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

9. Water Data Web Sites

10. NWISWeb site output # agency_cd Agency Code # site_no USGS station number # dv_dt date of daily mean streamflow # dv_va daily mean streamflow value, in cubic-feet per-second # dv_cd daily mean streamflow value qualification code # # Sites in this file include: # USGS 02087500 NEUSE RIVER NEAR CLAYTON, NC # agency_cdsite_nodv_dtdv_vadv_cd USGS020875002003-09-011190 USGS020875002003-09-02649 USGS020875002003-09-03525 USGS020875002003-09-04486 USGS020875002003-09-05733 USGS020875002003-09-06585 USGS020875002003-09-07485 USGS020875002003-09-08463 USGS020875002003-09-09673 USGS020875002003-09-10517 USGS020875002003-09-11454 Time series of streamflow at a gaging station USGS has committed to supporting CUAHSI’s GetValues function

11. Point Observations Information Model 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 An observation series is an array of observations at a given site, for a given variable, with start time and end time A value is an observation of a variable at a particular time A qualifier is a symbol that provides additional information about the value Data Source Network Sites Observation Series Values {Value, Time, Qualifier} USGS Streamflow gages Neuse River near Clayton, NC Discharge, stage, start, end (Daily or instantaneous) 206 cfs, 13 August 2006 Return network information, and variable information within the network Return site information, including a series catalog of variables measured at a site with their periods of record Return time series of values

12. http://his.cuahsi.org/odmdatabases.html CUAHSI Observations Data Model

13. WaterML design principles Driven largely by hydrologists; the goal is to capture semantics of hydrologic observations discovery and retrieval Relies to a large extent on the information model as in ODM (Observations Data Model), and terms are aligned as much as possible –Several community reviews since 2005 Driven by data served by USGS NWIS, EPA STORET, multiple individual PI-collected observations Is no more than an exchange schema for CUAHSI web services A fairly simple and rigid schema tuned to the current implementation; the least barrier for adoption by hydrologists Conformance with OGC specs not in the initial scope – but working with OGC on this (OGC Discussion Paper 07-041)

14. Water Data Services Set of query functions Returns data in WaterML 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)

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

16. Hydrologic Information Server Microsoft SQLServer Relational Database Observations Data & Catalogs Geospatial Data GetSites GetSiteInfo GetVariables GetVariableInfo GetValues DASH – data access system for hydrologyWaterOneFlow services ArcGIS Server

17. SQL Server ODMs and catalogs. All instances exposed as ODM (i.e. have standard ODM tables or views: Sites, Variables, SeriesCatalog, etc.) NWIS-IID NWIS-DV ASOS STORET TCEQ BearRiver... Spatial store Geodatabase or collection of shapefiles or both NWIS-IID points NWIS-DV points ASOS points STORET points TCEQ points BearRiver points... My new ODM My new points More databases More synced layers DASH Web Application Background layers (can be in the same or separate spatial store) WOF services Web services from a common template NWIS-IID WS NWIS-DV WS ASOS WS STORET WS TCEQ WS BearRiver WS... My new WS More WS from ODM-WS template USGS NCDC EPA TCEQ Web Configuration file Stores information about registered networks MXD Stores information about layers WSDLs, web service URLs Connection strings Layer info, symbology, etc. ODM DataLoader 2 6 5 3 1 4 WORKGROUP HIS SERVER ORGANIZATION STEPS FOR REGISTERING OBSERVATION DATA

18. Central HIS Data Services Catalog

19. 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 database schema (VEGA); ► Phoenix LTER is developing ODM (in MySQL) and WaterML web 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: ► KISTERS develops WaterML-compliant web services over their database, for a client; ► 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); ► More, which we don’t know about…

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

21. Semantic Tagging of Harvested Variables

22. CUAHSI HIS as a mediator across multiple agency and PI data –Maintains integrated metadata catalog and services registry –Keeps identifiers for sites, variables, etc. across observation networks –Manages and publishes controlled vocabularies, and provides vocabulary/ontology management and update tools –Provides common structural definitions for data interchange –Provides a sample protocol implementation –Governance framework: a consortium of universities, MOUs with federal agencies, collaboration with key commercial partners, NSF support for core development and test beds

23. HIS Scalability Adding… – …data types and datasets; processing models and services; servers; users and roles – – - shall not create unmanageable bottlenecks that require system re- engineering Designing for scalability: –Distilling a generic set of web service signatures; resolving semantic and structural heterogeneities –Using ODM as a common generic format for time series data, for ease of coding and uniform search interfaces –DASH GUI design to abstract specifics of disparate repositories –Leveraging common CI components developed in GEON –Working with agencies to remove web service bottlenecks

24. 11 WATERS Network test bed projects 16 ODM instances (some test beds have more than one ODM instance) Data from 1246 sites, of these, 167 sites are operated by WATERS investigators National Hydrologic Information Server San Diego Supercomputer Center HIS Deployment

25. Water Quality in Moreton Bay, Brisbane, Australia (Jane Hunter)

26. National Water Metadata Catalog Synthesis and communication of the nation’s water data http://his.cuahsi.org http://his.cuahsi.org HydroseekWaterML Government Water Data Academic Water Data

27. Accomplishments Generic method for 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 but can grow! WaterML is a common language for water observations data from academic and government sources Point Observations Data from Agencies and Academic Investigators can be consistently communicated using web services Point Observations Data can be archived in a relational database National Water Metadata Catalog is the most comprehensive index of the nation’s water observations presently existing

28. HIS Overview Report Summarizes the conceptual framework, methodology, and application tools for HIS version 1.1 Shows how to develop and publish a CUAHSI Water Data Service Available at: http://his.cuahsi.org/documents/HISOverview.pdf