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Hydrologic Ontologies Framework (HOW)
Michael Piasecki, Bora BeranDepartment of Civil, Architectural, and Environmental Engineering
Drexel University
Luis BermudezMonterrey Bay Aquarium Research Institute (MBARI)
3rd GEON Annual Meeting San Diego, CA
May 5-6, 2005
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Drexel University, College of Engineering
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Drexel University, College of Engineering
Consortium of Universities for the Advancement of the Hydrologic Sciences, Inc.
funded through EAR Hydrology Program (PD Doug James)
Hydrologic Information Systems (HIS) Group:Rick Hooper (President CUAHSI)David Maidment (UT Austin)John Helly (SDSC)Praveen Kumar (UIUC)Michael Piasecki (Drexel U.)
The objective of HIS is:
Background
• to develop a Hydrologic Information System prototypeCommunity Metadata ProfileDigital Library SystemDigital Watershed
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Drexel University, College of Engineering
Why Hydrologic Ontologies?
1. To resolve semantic heterogeneities between disparate metadatadescriptions, e.g. “Gauge Height = Stage = Stream Gauge”, by representing metadata profiles in the Web Ontology Language.
2. To create a Hydrologic Controlled Vocabulary for navigation and discovery of hydrologic data, e.g. a framework that aids discovery(on a more generalized level) and defines markup (on a finer or “leaf” level) to identify specific data sets within a Digital Library.
3. To develop a conceptual representation for the Hydrologic Domainwithin which data discovery and information extraction can be inferredfrom knowledge representations.
Lets focus on this ……………
ISO 19103 Units/Conversion
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Drexel University, College of Engineering
Ontology Examples
Status of work in CUAHSI
We currently have
ISO 19108 Temporal Objects
USGS Hydrologic Unit CodeISO 19115 Geospatial
Hydrologic ProcessesSedimentation
ARCHydro
What we need is
Many More
Many More
Many More
Many More
Upper Hydrologic Ontology
GEON
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Drexel University, College of Engineering
Example Use
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Drexel University, College of Engineering
GEON sponsored Mini Workshop
• San Diego Supercomputer Center January 27-28, 2005Many thanks to Chaitan Baru (agree to sponsor) and Margaret Banton for organizing.
• ParticipantsMichael Piasecki Drexel University (convener)David Maidment University of Texas, AustinThanos Papanicolaou University of IowaEdwin Welles NOAA, National Weather Service, OHDLuis Bermudez Monterrey Bay Aquarium Research Institute (MBARI)llya Zaslavsky SDSCKai Lin SDSCAshraf Memon SDSC
• Objective:Discuss concepts for Upper Hydrologic Ontology
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Drexel University, College of Engineering
A few rules:
1) There is no one correct way to model a domain— there are alwaysviable alternatives. The best solution almost always depends on theapplication that you have in mind and the extensions that you anticipate.
2) Ontology development is necessarily an iterative process.
3) Concepts in the ontology should be close to objects (physical or logical)and relationships in your domain of interest. These are most likely to benouns (objects) or verbs (relationships) in sentences that describe yourdomain.
Be cognizant of ……….
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Drexel University, College of Engineering
1st Alternative Hydrologic Ontologies
GeoVolume concept horizontal slices no vertical tracing
class:hydrology
subclass:precip
subclass:………
subclass:……..
subclass:atmos water
subclass:surface water
subclass:sub-surf. water
15 km
~2 m
-1 km
Pros: categorization along spatial separations, easy to followclosely linked to hierarchical structure of CVtraditional linkage to disciplines and sub-disciplines horizontal flow path is well representedmodel domains are typically aligned with horizontal layers
Cons:vertical flow (budget) not represented wellneed prior knowledge in which domain to search for dataprocesses are sub-items on low levels of ontology, this may not suit the general idea of moving from more general to more specific concepts
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Drexel University, College of Engineering
2st Alternative Hydrologic Ontologies
Measurement concept everything is a measure expand to include phenomena & features
Feature:Basin
Curve-#
SCS => derived
Phenomenon:Rainfall
Intensity
NEXRAD => derivedgauge => measured
Substance:Water
Temperatu
pH
Pros: a very general concept that potentially serves all purposescould be linked with other domainspossible use of only ONE upper ontology model
Cons:processes, data models are not easily mapped or foundno hierarchical navigationdifficult when trying to use for CV or keyword lists might be difficult for “new” knowledge discovery
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Drexel University, College of Engineering
3st Alternative Hydrologic Ontologies
“Interests” concept models (prediction, analysis) data models (obs, measurements) processes (phenomena) representations (maps, time series, …)
Feature
Waterbody
HydroIDHydroCodeFTypeNameAreaSqKmJunctionID
HydroPoint
HydroIDHydroCodeFTypeNameJunctionID
Watershed
HydroIDHydroCodeDrainIDAreaSqKmJunctionIDNextDownID
ComplexEdgeFeature
EdgeType
Flowline
Shoreline
HydroEdge
HydroIDHydroCodeReachCodeNameLengthKmLengthDownFlowDirFTypeEdgeTypeEnabled
SimpleJunctionFeature
1HydroJunction
HydroIDHydroCodeNextDownIDLengthDownDrainAreaFTypeEnabledAncillaryRole
*
1
*
HydroNetwork
*
HydroJunction
HydroIDHydroCodeNextDownIDLengthDownDrainAreaFTypeEnabledAncillaryRole
HydroJunction
HydroIDHydroCodeNextDownIDLengthDownDrainAreaFTypeEnabledAncillaryRole
Data Model ArcHydro
class:hydrology
subclass:Sediment
subclass:Heat Flux
subclass:Flooding
subclass:models
subclass:data
subclass:processes
dimension
Type
….
Pros: direct link to processes & data models of interestcan link data sets directly with processescan make use of many already existing conceptualizations models (statistical, deterministic etc) can be well mapped
Cons:not very good for hierarchical navigationthere is no general -> specific transitiondifficult when trying to use for CV or keyword lists might be difficult for “new” knowledge discovery
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Drexel University, College of Engineering
Outcomes Hydrologic Ontologies
• Development of a Higher level Hydrologic ontology based on the afore mentioned concepts. The group felt no clear affinity for one or the other concepts. As a result, two or three top ontologies may need to be developed and placed next to each other. Depending on the taskat hand a user may use either one of them to address the objective.
• Development of lower ontologies that can be merged with the top ontology. a) development of ontologies from database schema (like ARCHydro and the NWIS data base) via XML schema libraries b) development of a processes (or phenomena) ontology c) development of modeling ontology d) inclusion of task specific (service) ontologies, e.g. units, temporal
• Development of a well defined Hydrologic Controlled Vocabulary that can be used to query the hydrologic realm. One suggestion made was to use common queries as a starting point to identify important aspects in the taxonomy of the CV.
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Drexel University, College of Engineering
HYDROOGLE
Application Hydrologic Ontologies
Upper Ontology:Measurements
Lower Ontology:HUC system
coupled with
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Drexel University, College of Engineering
Thank you
Questions?
http://loki.cae.drexel.edu:8080/web/how/me/metadatacuahsi.html
Additional Information
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Drexel University, College of Engineering
Pros: a very general concept that potentially serves all purposescould be linked with other domainspossible use of only ONE upper ontology model
Cons:processes, data models are not easily mapped or foundno hierarchical navigationdifficult when trying to use for CV or keyword lists might be difficult for “new” knowledge discovery