introduction to cuahsi water web services and texas his david r. maidment the university of texas at...
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Introduction to CUAHSI Water Web Services and Texas HIS
David R. Maidment
The University of Texas at Austin
HIS Team and Collaborators
• University of Texas at Austin – David Maidment, Tim Whiteaker• San Diego Supercomputer Center – Ilya Zaslavsky, David
Valentine, Tom Whitenack• Utah State University – David Tarboton, Jeff Horsburgh, Kim
Schreuders, Justin Berger• Drexel University – Michael Piasecki, Yoori Choi• University of South Carolina – Jon Goodall, Tony Castronova• Idaho State University – Dan Ames, Ted Dunsford, Teva Veluppillai• CUAHSI Program Office – Rick Hooper, David Kirschtel, Conrad
Matiuk• WATERS Network – Testbed Data Managers• HIS Standing Committee • USGS – Bob Hirsch, David Briar, Scott McFarlane• NCDC – Rich Baldwin• ESRI – Dean Djokic, Christine Eggers, and many others
CUAHSI Water Web Services and Texas HIS
• CUAHSI Hydrologic Information System• CUAHSI Water Data Services• Texas Water Data Services
CUAHSI Water Web Services and Texas HIS
• CUAHSI Hydrologic Information System• CUAHSI Water Data Services• Texas Water Data Services
Consortium of Universities for the Advancement of Hydrologic Science, Inc (CUAHSI)
118 Universities in North America (and 3 in Europe)
NSF supports building a Hydrologic Information System (HIS)
Synthesis and communication of the nation’s water data http://his.cuahsi.org
Federal Water Data Academic Water DataState and Local Water Data
To make a complete picture of
water data, we need to be able to add
state and local data to
national and academic data
sources.
Regional Water Data Systems
RainfallWater quantity
Groundwater
Water Observations Data
Meteorology
Soil water
Water quality
Data are Published in Many Formats
A services oriented architecture is a ‐concept that applies to large, distributed
information systems that have many owners, are complex and heterogeneous, and have considerable legacies from the
way their various components have developed in the past (Josuttis, 2007).
Services-Oriented Architecture
We are at a tipping point…
•Web pages •Web services
Internet
People interact with a remote information server
People interact with a network ofInformation services
InternetInternet
WaterML
HTML as a Web Language
Text and Picturesin Web Browser
<head><meta http-equiv="content-type" content="text/html; charset=utf-8" /><title>Vermont EPSCoR</title><link rel="stylesheet" href="epscor.css" type="text/css" media="all" /><!-- <script type='text/javascript' language='javascript‘ src='Presets.inc.php'>--></head>
HyperText Markup Language
Point Water Observations Time Series
A point location in space A series of values in time
WaterML as a Web Language
Discharge of the San Marcos River at Luling, TX June 28 -
July 18, 2002
Streamflow data in WaterML language
CUAHSI Water Web Services and Texas HIS
• CUAHSI Hydrologic Information System• CUAHSI Water Data Services• Texas Water Data Services
Base StationComputer(s)
Telemetry Network
Sensors
Query, Visualize, and Edit data using ODM Tools
Excel, text
ODMDatabase
ODM Data
Loader
Streaming Data
Loader GetSitesGetSiteInfo
GetVariableInfoGetValues
WaterOneFlowWeb Service
WaterML
DiscoveryHydroSeek
AccessAnalysis
GISMatlabSplus
RIDL
JavaC++VB
HIS Desktop
Water Metadata Catalog
Harvester
Service Registry HydroTagger
HIS Central
CUAHSI Water Data Services System
USGS NWIS
EPA STORET
NCDC Others
Point Observations Information Model
Data Source
Network
Sites
Variables
Values
{Value, Time, Metadata}
Utah State Univ
Little Bear River
Little Bear River at Mendon Rd
Dissolved Oxygen
9.78 mg/L, 1 October 2007, 5PM
• 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 metadata quantity provides additional information about the value
GetSites
GetSiteInfo
GetVariableInfo
GetValues
Information is transmitted through the internet in WaterML as web services
Data Values – indexed by “What-where-when”
Variables, V
Space, S
Time, T
s
t
Vi
vi (s,t)“Where”
“What”
“When”
Data Values Table
Data Series – Metadata description
Space
Variable, Vi
Site, Sj
End Date Time, t2
Begin Date Time, t1
Time
Variables
Count, C
There are C measurements of Variable Vi at Site Sj from time t1 to time t2
Series Catalog
Space
Variable, Vi
Site, Sj
End Date Time, t2
Begin Date Time, t1
Time
Variables
Count, C
Vi
Sj
t2
t1
C
http://his.cuahsi.org/odmdatabases.html
CUAHSI Observations Data Model
Values
Series
Spatial References TableSpatial ReferenceID SRSID SRSName
0 Unknown1 4267 NAD272 4269 NAD83
Sites TableSiteID SiteCode SiteName Latitude Longitude LatLongID
1 AcmeP1 Backyard Pond 34.565 -93.232 12 AcmePR2 Mill River gage Station 34.2 -93.4 1
Simplified ODM Structure
HIS Servers at Universities in the WATERS Network
HIS Central at San Diego Supercomputer
Center
CUAHSI Water Data Services
35 services15,000 variables1.75 million sites
8.33 million series342 million data
CUAHSI Water Web Services and Texas HIS
• CUAHSI Hydrologic Information System• CUAHSI Water Data Services• Texas Water Data Services
Texas Water Data
Services
10 services7,010 variables
15,870 sites645,566 series
23,272,357records
Ingest Data From Different Sources
Transform Data into Uniform Format
Load Newly Formatted Data into ODM Tables in MS SQL/Server
Wrap ODM with WaterML Web Services for Online Publication
TPWD Coastal
Fisheries Raw Data
TWDBCoastline
Raw Data
TIFPLower Sabine
Publishing an ODM Water Data Service
Data Upload
Observations Data Model (ODM)
WaterML
TPWD ODM
TWDB ODM
TIFP ODM
TCOONMETADATA
ODM
TCOONDataValues
WaterML
Metadata From:ODM Database in Austin
TCOON Web Site in Corpus Christi
TCOONWater Data
Service
Publishing a Hybrid Water Data Service TCOON Metadata are Transferred
from XML to the ODM
Web Services can both Query the ODM for Metadata and use a Web
Scraper for Data Values
Calling the WSDL Returns Metadata and Data Values as if from the same
Database
GetSitesGetSiteInfo
GetVariableInfo
Get Values from:
http://his.crwr.utexas.edu/tcoonts/tcoon.asmx?WSDL
Web Services in Space and Time
•Water Markup Language (WaterML) is a schema for encoding water observations time series data and metadata;
•Geographic Markup Language (GML) encodes spatial data about sets of geographic features;
•so that you can transmit water data in space and time
WFS and WaterML
Observations Data in Time in WaterML
Observations Metadata in Space in GML as a Web Feature Service
A Theme Layer
Synthesis over all data sources of observations of a particular variable
e.g. Salinity
Texas Salinity Theme
7900 series347,000 data
7900 seriesTPWD 3400TCEQ 3350TWDB 150
Copano and Aransas Bay Salinity
Number of Data
0 – 5050 – 150
150 – 400400 – 1000
1000 – 3000
Copano Bay
Aransas Bay
Texas Daily Streamflow Theme
USGS Data 1138 sites
(400 active)
Austin – Travis Lakes Streamflow
Years of Data
0 – 1010 – 2020 – 4040 – 60
60 – 110
Texas Water Temperature Theme
22,700 series966,000 data
Austin – Travis Lakes Water Temperature
Number of Data
0 – 5050 – 150
150 – 400400 – 1000
1000 – 5000
Texas Natural Resources Information System Data Viewer
Texas Natural Resources Information System Data Viewer – Observation Sites
Time Series
Conclusions
•We have built a successful and functioning services-oriented architecture for water observations data in the United States
•WaterML is critical as the common water data language
•A lot of water information is best accessed and indexed at the state and regional level
•CUAHSI HIS would like to work with academic partners to build state and regional HIS
HIS Website – his.cuahsi.org
Download tools, research publications, contribute to the
effort – it’s all here