CUAHSI Hydrologic Information System

Summary as of June 30, 2004by David R. Maidment

CUAHSI Hydrologic Information System Participants

Core Team: D. Maidment, J. Helly, P. Kumar, M. Piasecki, R. Hooper, J. Duncan

Collaborators: V. Lakshmi, X. Liang, Y. Liang, U. Lall, L. Poff, K. Reckhow, D.

Tarboton, I. Zaslavsky, C. Zheng

Hydrologic Information System Data Organization

Hydrologic Digital Library(Digital files of hydrologic information in any form,

indexed by a metadata catalog)

Flux Assessment System

Process model domainsTime series GIS data

Space-time grids Statistics

Hydrologic Data Model Application Systems

CUAHSI HIS is meant to facilitate:

• Data Acquisition– quicker, easier, usable formats

• Data Archiving– experimental and regional data for HO’s

• Data Assembly– bringing the data together, data model

• Data Analysis– visualization, statistics, hypothesis testing.

CUAHSI Hydrologic Information Systems

• Work of the five project partners– CUAHSI– San Diego Supercomputer Center– University of Texas– University of Illinois– Drexel University

• Involving the collaborators……Ken Reckhow, Yao Liang

Drexel University

• Michael Piasecki is PI, assisted by Luis Bermudez

• Goal is to study metadata languages and standards to find what is most suitable for hydrology

• Concept hierarchies stored in “ontologies” described in OWL (Ontology Web Language)

Content

• Selection of the “base” metadata specification

• Expression of the selection using ontologies

• Profiles

• Tools to extend metadata specifications to allow

creation of profiles

• Sources for hydrologic vocabulary

Selection of base metadata specification

Specification Level of

Conceptualization Scope

ISO:19115:2003

UML: easily transportable to an

ontology

Global

FGDC-STD-001-1998Not presented in a conceptual way

(text and DTD)US

EML 2.0.0 XML schema Community

Selection of base metadata specification

ISO:19115:2003

FGDC-STD-001-1998

Mapping will be available

EML 2.0.0

They use ideas in ISO and FGDC ( do not really use their elements ); however they present detail elements to describe format and security constraints

ISO Metadata formalized in OntologiesISO 19115:2003 (Geographic Metadata)

http://loki.cae.drexel.edu/~wbs/ontology/2004/04/iso-metadata

ISO 19108 (Temporal Schema)

http://loki.cae.drexel.edu/~wbs/ontology/2004/05/iso-19108

ISO 19107 (Spatial Schema)

ISO 19110(Methodology for feature cataloguing)

In progress

FGDC Metadata formalized in Ontology

Why ? We can express the mappings in machine readable format

How? Java program is coded to convert FGDC XML Schemas to OWL

FGDC XML schemas available at:http://www.fgdc.gov/metadata/metaxml.html

Extraction of classes and properties and cardinalities

Conversion of datatypes and codelist to be done

CUAHSI – Profile V.1.0

1) Extend ISO

2) Set as core (Metadata elements selected to be used by CUAHSI)

3) Set some mandatory

4) Create domain list to fit needs

Express in machine readable format OWL/XML

fully interoperable

with original ISO

CUAHSI – Profile V.1.0

ISO 19115

ISO 19108 ISO 19107

ISO 19110

CUAHSI Profile

1) Extend ISO

CUAHSI – Profile V.1.0

2) Set as core

<owl:AnnotationProperty rdf:ID="core">

Using: “flag” to mark the core elements

core = true

iso:MD_Metadata+ metadataConstraints[0..n] : MD_Constraints …

cuahsi:MD_Metadata+ metadataConstraints[1..n] : MD_Constraints …

3) Set as Mandatory- Security and legal Constraints

- Data quality Lineage (including process steps)

CUAHSI – Profile V.1.0

4) New code lists

MD Classification Code for security Constraints

- World

- Group

- Owner

CUAHSI – Profile V.1.0

Profiles and subprofiles

CUAHSI Profile V.1.0

Features-Profile TimeSeries-Profile

… ……

In progress

Identifying characteristics of elements

What can be created by the user? E.g. abstract.

What can be created by the metadata software. E.g. metadata version, date of creation.

What can automatically be created by the tools creating the data :E.g. lineage.

What can be extracted from files which format is known: E.g. HDF or shape files.

In progress

Also will be expressed in OWL/XML using an annotation property

User profiles

To facilitate creation of metadata by reusing resources

E.g. Citation Responsible Party

Vocabulary in metadata instancesStudied the files located at: http://www.env.duke.edu/cares

Created an ontology with features, attributes and keywords of the ~62 files to depict the heterogeneity problems

- Some have FGDC metadata, others do not

- Semantic Heterogeneity is found in feature and attributes

How to deal with this problem?

In automatic data creation the feature name and attributes could be set a priori (or mapped ) from a hydrologic ontology that supplies the terms.

In manual creation of metadata we could map the semantics when uploading files:

Similar to Lin, K. and B. Ludäscher work at SDSC mapping geological maps

Users map their semantics to a hydrologic ontology.

A system should assist making good guesses from previous mappings and ontology inference :

Purpose to have a usable ontology

Ontologies constructionCreation of a top hydrologic ontology that is mapped with Wordnet ( the ontology with more usage as of today)

http://loki.cae.drexel.edu/~how/upper/upper.html

Creation of hydrologic units ontology Extracting hydrologic terms to define feature and attributes :

- ARC HYDRO in progress

- UNESCO Thesaurus

- GCMD

- SWEET

- GETTY

What is next?Build Metadata descriptions for Neuse_files (initially 2)

Core set for anydata set in CUAHSI

automatically set

auto user profile

user “by hand” want this to be very small

Data set 1 Data set 2

Data set specific elementsand attributes

=> all in MIF format for HydroViewer

CUAHSI Hydrologic Information Systems

• Work of the five project partners– CUAHSI– San Diego Supercomputer Center– University of Texas– University of Illinois– Drexel University

• Involving the collaborators……

New Concept of PublicationNew WayOld Way

HydroViewer GUI

NeuseRiverWatershedCollection

HydroViewer Demoby John Helly

SDSC Multiview Map Viewer

http://geo.sdsc.edu/website/SIO_Expl/viewer.htm

Wireless telecommunicationof water resources data

Can we use thesedata as a prototype forthe CUAHSI observatory?

CUAHSI Hydrologic Information Systems

• Work of the five project partners– CUAHSI– San Diego Supercomputer Center– University of Texas– University of Illinois– Drexel University

• Involving the collaborators……

University of Texas

• David Maidment is PI, assisted by Jon Goodall, Gil Strassberg, Venkatesh Merwade

• Hydrologic data model development– atmospheric water, surface water, subsurface

water– interoperable analysis environment

Information Sources

Analysis and Visualization

Hydrologic Information Data Model

CUAHSI Hydrologic Information System

GIS

Experiments

Simulation

Monitoring

Climate models

2. Integrate data into a coherent structure

3. Do science

1. Assemble data from many sources

Hypothesis testing

Data Assimilation

Remote sensing

Statistics

Created first for the Neuse basin and then for each of the following CUAHSI Observatory Planning basins

Digital Watershed:An implementation of the CUAHSI Hydrologic Information Data Model for a particular region

http://neuse.crwr.utexas.edu/

Neuse Basin: Coastal aquifer system

* From USGS, Water Resources Data Report of North Carolina for WY 2002

Section line

Beaufort Aquifer

A 3-D Volume Model of the Beaufort Aquifer

Beaufort confining layer

Beaufort aquifer

Built by Gil Strassberg from borehole information collected by the Neuse basin case study

team

RUC20 – Output SamplesPrecipitable water in the atmosphere

Cross-section of relative humidity

Images created from Unidata’s Integrated Data Viewer (IDV)

Wind vectors and wind speed (shading)

Surface Water Information

ArcIMS Web Server displaying data compiled in Neuse HO Planning Study

Neuse basin data in Multiview

http://geo.sdsc.edu/website/SIO_Expl/viewer.htm

Data ModelHydroObject

Continuous Discrete Coupler

HydroVolume

HydroArea

HydroLine

HydroPoint

Raster

HydroElement

TIN

HydroScalar

HydroVector

Ontology

Discrete

Discrete

Continuous

Coupler

Coupling table 

FromID ToID Feature

1 2 4

2 3 5

 

Where …HydroID of canal feature = 2

HydroID of upstream canal feature = 1HydroID of downstream canal feature = 3HydroID of upstream control structure = 4

HydroID of downstream control structure = 5

Mass balance

University of Illinois

• Praveen Kumar is PI, assisted by Benjamin Ruddell

• Developing “Modelshed” which is an generalized hydrologic modeling and data analysis environment built on top of Arc Hydro

• Focused on applications integrating hydrology and climate modeling

Flow

Time

Time Series

Hydrography

Hydro Network

Channel System

Drainage System

Arc Hydro Components

What is a Modelshed?• A volumetric spatial

model unit, registered in three dimensions by a GIS, with which time-varying data, model fluxes, spatial relationships and descriptive metadata are associated

CUAHSI Hydrologic Information Systems

• Work of the five project partners– CUAHSI– San Diego Supercomputer Center– University of Texas– University of Illinois– Drexel University

• Involving the collaborators……Ken Reckhow, Yao Liang

Involving the Collaborators…..

• We have a good start

• How do we involve the collaborators in a productive way?

• How should we interact with the Hydrologic Observatory proposers (meeting at Utah State on August 24-25)?

• Possible CUAHSI “all hands” meeting at SDSC on August 12-13