1. A Services Oriented Architecture for Water Resources Data David R. Maidment and Timothy L. Whiteaker Center for Research in Water Resources University of Texas at Austin Waters Network Meeting Baltimore, Oct 22, 2007

2. Collaborators San Diego Supercomputer Center –Ilya Zaslavsky, David Valentine, Tom Whitenack Utah State University –David Tarboton, Jeff Horsburgh, Kim Schreuders Drexel University –Michael Piasecki, Bora Beran, Yoori Choi University of South Carolina –Jon Goodall

3. A Services Oriented Architecture for Water Resources Data WATERS Network Information System Observations data model Data Services

4. A Services Oriented Architecture for Water Resources Data WATERS Network Information System Hydrologic Information Server Data Services

5. Waters Network Testbed Sites

6. Waters Observation Networks 16 observation networks (some testbeds have more than one network) Provides data from 1246 sites Of these, 167 sites are operated by WATERS investigators

7. Florida – Santa Fe Watershed Nitrate Nitrogen (mg/L) Millpond Spring PI: Wendy Graham, ….; DM: Kathleen McKee, Mark Newman

8. North Carolina – Albemarle Pamlico Sound Salinity Mod Mon and Ferry Mon networks PI: Hans Paerl; DM: Rodney Guajardo

9. Chesapeake Information Management System (Johns Hopkins, Drexel, Penn State Universities) http://www.hydroseek.org PI: Michael Piasecki, Bill Ball, Kevin Dressler, Chris Duffy, Pat Reed; DM: Bora Beran, Yoori Choi

10. Baltimore — Gwynns Falls Watershed 15-min Precipitation at Carroll Park PI: Claire Welty, …..; DM: Mike McGuire

11. Susquehanna – Upper Juniata Basin Net Radiation (W/m 2 ) Oct 05 May 06 PI: Chris Duffy, Pat Reed; DM: Bora Beran, Yoori Choi

12. Iowa – Clear Creek Watershed Uses streaming data loader Precipitation PI: Craig Just, Marian Muste, Anton Kruger; DM: Marian Muste, Dong Su Kim, Nick Arnold

13. Minnesota – Minnehaha Creek Nitrate Nitrogen (mg/L) PI: Miki Hondzo, Bill Arnold, …. DM: Jim Kang, Sung-Chul Kim

14. Montana – Crown of the Continent Snow Depth (m) Sperry glacier on ice weather station 2007: July August 0 4 PI: Johnnie Moore, … DM: Toby Meirbachtol, Aaron Deskins

15. Utah – Little Bear River and Mud Lake Turbidity David Stevens, Jeff Horsburgh, David Tarboton, Nancy Mesner, Kim Schreuders

16. Sierra Nevada – San Joaquin River Transect of measurements across the river PI: Roger Bales, Tom Harmon DM: Xiande Meng

17. Corpus Christi Bay - Hypoxia DO (mg/L) PI: Barbara Minsker, Paul Montagna, Jim Bonner, Ben Hodges; DM: Kevin Nelson

18. A Services Oriented Architecture for Water Resources Data WATERS Network Information System Observations data model Data Services

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

20. Hydrologic Information Server Deployment National Hydrologic Information Server San Diego Supercomputer Center metadata for national datasets: NWIS, Storet, Snotel WATERS testbed server HydroSeek Server Drexel University metadata for WATERS network datasets:

21. 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

22. CUAHSI Observations Data Model http://www.cuahsi.org/his/odm.html

23. Loading Data into ODM MyDB ODDataLoader Database

24. New Methods for Data Loading DataTurbine SQL/Server Integration Services Streaming Data Loader

25. How to Get an HIS Server Options: –Virtual Server: If you don’t have a server available, a virtual server can be allocated for you at SDSC –SDSC Staff sets up your server for you: Ship your server to SDSC and they will install HIS then ship it back to you. Provide remote desktop access to SDSC staff and they install and configure your server remotely. –Do it yourself: Download the components and data and configure your server on your own. Documentation and downloads available here: http://river.sdsc.edu/wiki/http://river.sdsc.edu/wiki/ You must provide software licenses for: –MSDN Academic Alliance ~ $700/yr –ArcGIS Server and Desktop (institutional site license) Contact Tom Whitenack at SDSC: whitenac@sdsc.eduwhitenac@sdsc.edu

27. A Services Oriented Architecture for Water Resources Data Waters Network Information System Observations Data Model Data Services

28. 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.

29. 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' or spelled out, 'W- S-D-L') 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)

30. Web Pages and Web Services http://www.safl.umn.edu/ http://his.safl.umn.edu/SAFLMC/cuahsi_1_0.asmx? Uses Hypertext Markup Language (HTML) Uses WaterML (an eXtended Markup Language for water data)

31. 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

32. WaterOneFlow Set of query functions Returns data in WaterML Ilya Zaslavsky and David Valentine, SDSC

33. 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

34. 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

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

36. 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

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

38. HIS to Google Earth developed by Peter Fitch, CSIRO, Australia http://www.watersnet.org/wtbs/ODMKMLGatway.html A web application housed in Canberra, Australia, that operates over the WATERS Network data services

39. NCSA – CyberIntegrator Data Sets Tools Workflow Contextual information about a specific data set, tool or step. Web Services: Barbara Minsker, Peter Bajcsy and Luigi Marini, UIUC

41. Conclusion: Web services work! The CUAHSI Hydrologic Information System (HIS) is a geographically distributed network of hydrologic data sources and functions that are integrated using web services oriented architecture so that they function as a connected whole. For more information: http://www.cuahsi.org/his.htmlhttp://www.cuahsi.org/his.html

42. Conclusions Hydrologic Information Server is functioning at all testbed sites Data are published in a consistent format (WaterML) and are thematically synthesized in Hydroseek with water agency data Applications and analyses can operate seamlessly over the Waters Network data services A lot more to be done – GIS, weather and climate, remote sensing, simulation modeling, interpretive analysis, ….. Digital Watershed development!