1. CUAHSI HIS Data Services Project David R. Maidment Director, Center for Research in Water Resources University of Texas at Austin (HIS Project Leader)

2. CUAHSI HIS Development 2000 2008 2004 2002 2006 HIS Committee formed Snowbird meeting & HIS White Paper HIS Pilot Project NSF Proposal Development HIS Development Project CUAHSI Regional Meetings http://www.cuahsi.org/publications/cuahsi_tech_rpt_2.pdf

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 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. Definition The CUAHSI Hydrologic Information System (HIS) is a geographically distributed network of data sources and functions that are integrated using web services oriented architecture so that they operate as a connected whole.

5. Services Oriented Architecture Service-oriented Architecture (SOA) is an architectural design pattern that concerns itself with defining loosely-coupled relationships between producers and consumers. A major focus of Web services is to make functional building blocks accessible over standard Internet protocols that are independent from platforms and programming languages. The Web Services Description Language (WSDL, pronounced 'wiz-dəl') is an XML-based language that provides a model for describing Web services.XMLWeb services (from Wikipedia) Defined by the World Wide Web Consortium (W3C)

6. Locations Variable Codes Date Ranges WaterML and WaterOneFlow GetSiteInfo GetVariableInfo GetValues WaterOneFlow Web Service Client STORET NAM NWIS Data Repositories Data EXTRACT TRANSFORM LOAD WaterML WaterML is an XML language for communicating water data WaterOneFlow is a set of web services based on WaterML

7. WaterOneFlow Return data in WaterML Set of query functions http://river.sdsc.edu/wateroneflow/ Open Geospatial Consortium, Inc. (2007), CUAHSI WaterML, OGC Discussion Paper, OGC 07-041r1, Version 0.3.0, Zaslavsky, I., D. Valentine, and T. Whiteaker Editors, http://www.opengeospatial.org/standards/dp,http://www.opengeospatial.org/standards/dp

8. We are at a tipping point …. Web pages Web services ComputerPerson Computer Internet Computer People interact with a remote information server Networks of information servers provide services to one another

9. Information communication Water web pages Water web services HyperText Markup Language (HTML) Water Markup Language (WaterML)

10. Point Observations Information Model Data Source Network Sites Variables Values {Value, Time, Qualifier, Offset} Utah State Univ Little Bear River Little Bear River at Mendon Rd Dissolved Oxygen 9.78 mg/L, 1 October 2007, 6PM 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 A qualifier is a symbol that provides additional information about the value An offset allows specification of measurements at various depths in water http://www.cuahsi.org/his/webservices.html GetSites GetSiteInfo GetVariables GetVariableInfo GetValues

11. CUAHSI Observations Data Model http://www.cuahsi.org/his/odm.html David Tarboton and Jeff Horsburgh, Utah State University

12. 11 WATERS Network test bed projects 17 ODM databases (some test beds have more than one ODM) Data from 1643 sites, of these, 167 sites are operated by WATERS 28 million data values describing 202 variables National Hydrologic Information Server San Diego Supercomputer Center WATERS Network Information System

13. 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

14. Observations Catalog Specifies what variables are measured at each site, over what time interval, and how many observations of each variable are available

15. Data Heterogeneity Syntactic mediation – Heterogeneity of format – Use WaterML to get data into the same format Semantic mediation – Heterogeneity of meaning – Each water data source uses its own vocabulary – Match these up with a common controlled vocabulary – Make standard scientific data queries and have these automatically translated into specific queries on each data source

16. Search multiple heterogeneous data sources simultaneously regardless of semantic or structural differences between them Objective NWIS NARR NAWQA NAM-12 request request return return What we are doing now ….. Michael Piasecki Drexel University

17. Semantic Mediator What we would like to do ….. NWIS NAWQA NARR generic request GetValues GetValues HODM Michael Piasecki Drexel University

18. Hydroseek http://www.hydroseek.org http://www.hydroseek.org Supports search by location and type of data across multiple observation networks including NWIS and Storet Bora Beran, Drexel

19. HydroTagger Ontology: A hierarchy of concepts Each Variable in your data is connected to a corresponding Concept

20. Critical Zone Observatories (Slide from Suzanne Anderson, Univ. of Colorado)

21. Digital Watersheds A digital watershed is a structured collection of digital representations of inter-related hydrologic objects and measurements that facilitates integrated modeling and analysis.

22. 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 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

23. How has CUAHSI Helped? A management structure for the academic hydrologic science community to work together Formed the original HIS Committee – got the effort started A mechanism by which we can serve and support our hydrologic science colleagues