A Services Oriented Architecture for Water Resources Data

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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. Collaborators. San Diego Supercomputer Center Ilya Zaslavsky , David Valentine, Tom Whitenack Utah State University - PowerPoint PPT Presentation

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A Services Oriented Architecture for Water Resources Data

David R. Maidment and Timothy L. WhiteakerCenter for Research in Water Resources

University of Texas at Austin

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

A Services Oriented Architecture for Water Resources Data

• WATERS Network Information System• Observations data model• Data Services

A Services Oriented Architecture for Water Resources Data

• WATERS Network Information System• Hydrologic Information Server• Data Services

Waters Network Testbed Sites

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

Florida – Santa Fe Watershed

Nitrate Nitrogen (mg/L)

Millpond Spring

PI: Wendy Graham, ….; DM: Kathleen McKee, Mark Newman

North Carolina – Albemarle Pamlico Sound

Salinity

Mod Monand Ferry Monnetworks

PI: Hans Paerl; DM: Rodney Guajardo

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

Baltimore — Gwynns Falls Watershed15-min Precipitation at Carroll Park

PI: Claire Welty, …..; DM: Mike McGuire

Susquehanna – Upper Juniata BasinNet Radiation (W/m2)

Oct 05 May 06

PI: Chris Duffy, Pat Reed; DM: Bora Beran, Yoori Choi

Iowa – Clear Creek Watershed

Uses streaming data loader

Precipitation

PI: Craig Just, Marian Muste, Anton Kruger; DM: Marian Muste, Dong Su Kim, Nick Arnold

Minnesota – Minnehaha Creek

Nitrate Nitrogen (mg/L)

PI: Miki Hondzo, Bill Arnold, …. DM: Jim Kang, Sung-Chul Kim

Montana – Crown of the ContinentSnow Depth (m)

Sperry glacier on iceweather station

2007: July August0

4

PI: Johnnie Moore, … DM: Toby Meirbachtol, Aaron Deskins

Utah – Little Bear River and Mud Lake

Turbidity

David Stevens, Jeff Horsburgh, David Tarboton, Nancy Mesner, Kim Schreuders

Sierra Nevada – San Joaquin RiverTransect of measurements across

the river

PI: Roger Bales, Tom Harmon DM: Xiande Meng

Corpus Christi Bay - Hypoxia

DO (mg/L)

PI: Barbara Minsker, Paul Montagna, Jim Bonner, Ben Hodges; DM: Kevin Nelson

A Services Oriented Architecture for Water Resources Data

• WATERS Network Information System• Observations data model• Data Services

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

Hydrologic Information Server Deployment

National Hydrologic Information ServerSan Diego Supercomputer Centermetadata for national datasets:

NWIS, Storet, Snotel WATERS testbed server

Point Observations Information ModelData 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

CUAHSI Observations Data Modelhttp://www.cuahsi.org/his/odm.html

Loading Data into ODM

MyDB

ODDataLoader

Database

New Methods for Data Loading

DataTurbine

SQL/Server Integration Services

Streaming Data Loader

A Services Oriented Architecture for Water Resources Data

• Waters Network Information System• Observations Data Model• Data Services

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

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.

(from Wikipedia)

Defined by the World Wide Web Consortium (W3C)

Web Pages and Web Serviceshttp://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)

Locations

Variable Codes

Date Ranges

WaterML and WaterOneFlow

GetSiteInfoGetVariableInfoGetValues

WaterOneFlowWeb Service

Client

STORET

NAMNWIS

DataRepositories

Data

DataData

EXTRACTTRANSFORMLOAD

WaterML

WaterML is an XML language for communicating water dataWaterOneFlow is a set of web services based on WaterML

WaterOneFlow• Set of query functions • Returns data in WaterML

Ilya Zaslavsky and David Valentine, SDSC

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

• Search multiple heterogeneous data sources simultaneously regardless of semantic or structural differences between them

Objective

NWIS

NARR

NAWQANAM-12

request

request

request

request

request

requestrequest

request

request

return

return

return

return

return

returnreturn

return

return

What we are doing now …..

Michael PiaseckiDrexel University

Semantic MediatorWhat we would like to do …..

NWIS

NAWQA

NARR

generic request

GetValues

GetValues

GetValues

GetValues

GetValues

GetValuesGetValues

GetValues

GetValues HODM

Michael PiaseckiDrexel University

Hydroseekhttp://www.hydroseek.org

Supports search by location and type of data across multiple observation networks including NWIS and Storet

Bora Beran, Drexel

HydroTaggerOntology: A hierarchy of concepts

Each Variable in your data is connected to a corresponding Concept

HIS to Google Earthdeveloped 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

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 a web services architecture so that they function as a connected whole.

For more information: http://www.cuahsi.org/his.html

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!