Hydrologic Ontologies Framework (HOW)

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Hydrologic Ontologies Framework (HOW)
Michael Piasecki, Bora Beran Department of Civil,
Architectural, and Environmental
Engineering Drexel University Luis
Bermudez Monterrey Bay Aquarium Research
Institute (MBARI) 3rd GEON Annual Meeting San
Diego, CA May 5-6, 2005
Drexel University, College of Engineering
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Background
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

• to develop a Hydrologic Information System
  prototype Community Metadata Profile Digital
  Library System Digital Watershed

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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.

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Domain and Scope of Hydrologic Ontologies
Basic questions What is the domain that
the ontology will cover? For what we are going
to use the ontology? For what types of
questions the information in the ontology should
provide answers? Who will use and maintain the
ontology?

• Competency questions (litmus test)
• What streams belong to Hydrologic Unit
  XYX?
• What is the net volume flux in watershed A for
  month Y?
• What was the accumulated rainfall in region Y
  because of storm X?
• What is the discharge time-history at point X as
  a result of storm Y passing through?
• ..
• many more

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Status of work in CUAHSI
We currently have
What we need is
Ontology Examples
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Example Use
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GEON sponsored Mini Workshop

• San Diego Supercomputer Center January 27-28,
  2005 Many thanks to Chaitan Baru (agree to
  sponsor) and Margaret Banton for organizing.
• Participants Michael Piasecki Drexel University
  (convener)
• David Maidment University of Texas, Austin
• Thanos Papanicolaou University of Iowa
• Edwin Welles NOAA, National Weather Service, OHD
• Luis Bermudez Monterrey Bay Aquarium Research
  Institute (MBARI)
• llya Zaslavsky SDSC
• Kai Lin SDSC
• Ashraf Memon SDSC
• Objective Discuss concepts for Upper
  Hydrologic Ontology

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Be cognizant of .
A few rules 1) There is no one correct way to
model a domain there are always viable
alternatives. The best solution almost always
depends on the application 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 be nouns (objects) or verbs
(relationships) in sentences that describe
your domain.
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1st Alternative Hydrologic Ontologies
GeoVolume concept horizontal slices no
vertical tracing
Pros categorization along spatial separations,
easy to follow closely linked to hierarchical
structure of CV traditional 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 well need 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
classhydrology
subclasssurface water
subclasssub-surf. water
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2st Alternative Hydrologic Ontologies
Measurement concept everything is a measure
expand to include phenomena features
FeatureBasin
Pros a very general concept that potentially
serves all purposes could be linked with other
domains possible use of only ONE upper ontology
model Cons processes, data models are not
easily mapped or found no hierarchical
navigation difficult when trying to use for CV or
keyword lists might be difficult for new
knowledge discovery
Curve-
SCS gt derived
PhenomenonRainfall
Intensity
NEXRAD gt derivedgauge gt measured
SubstanceWater
Temperatu
pH
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3st Alternative Hydrologic Ontologies
Interests concept models (prediction,
analysis) data models (obs, measurements)
processes (phenomena) representations
(maps, time series, )
classhydrology
Pros direct link to processes data models of
interest can link data sets directly with
processes can 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 -gt specific transitiondifficult when
trying to use for CV or keyword lists might be
difficult for new knowledge discovery
subclassdata
subclassprocesses
Data Model ArcHydro
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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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Application Hydrologic Ontologies
Upper Ontology Measurements
coupled with
Lower Ontology HUC system
HYDROOGLE
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Thank you Questions?
Additional Information
http//loki.cae.drexel.edu8080/web/how/me/metadat
acuahsi.html
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Pros a very general concept that potentially
serves all purposes could be linked with other
domains possible use of only ONE upper ontology
model Cons processes, data models are not
easily mapped or found no hierarchical
navigation difficult when trying to use for CV or
keyword lists might be difficult for new
knowledge discovery
Drexel University, College of Engineering