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Development of a Community Ontology for Earth System Science
Rob RaskinNASA/Jet Propulsion Laboratory
Pasadena, CA
March 20, 2008
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Data to Knowledge
Data Information Knowledge
Basic Elements Bytes Numbers Models FactsServices Save Visualize Infer Understand PredictStorage File Database GIS Ontology MindVolume High LowDensity Low High
Syntax Semantics
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What is Knowledge? Facts, relations, meanings, contexts,
common sense Information with context Shared understanding of meaning Suitable for reasoning/inference Dynamic, expandable
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Application:Intelligent Search for Data Consults knowledge base to find
alternative meanings Clustered by: synonyms, parent, children
Enables discovery of resources without exact keyword match
Semantic understanding is crucial Common search engines (Google) use these
capabilities only minimally, at present
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Application: Intelligent Search for Data (cont.) Noesis ontology-aided search tool
http://noesis.itsc.uah.edu Provides access to:
Data Journal articles Web pages Experts (people)
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Ontology
Method to store “facts” General definition: “all that is known” Computer science definition: Machine-readable definition
of terms and how they relate to one another As with a dictionary, terms are defined in terms of other terms
Provide shared understanding of concepts Support knowledge reuse Support machine-to-machine communications with
deeper semantics than controlled vocabulary
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Desirable Features of OWL
OWL accepted as a standard by W3C As a standard language, it is easy to extend
(specialize) concepts developed by others Synonym support (multiple terms with same
meaning) Label available to indicate preferred term for each
community Homonym support (multiple meanings of
same term) Separate namespaces (President:Bush vs Plant:Bush)
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Plate tectonics - before
Plate Tectonics Ontology
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Atmosphere Ontology…
Atmosphere Ontology
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Semantic Web for Earth and Environmental Terminology (SWEET)
Concept space written in OWL Initial focus to assist search for data resources
Funded by NASA Later focus to serve as community standard Enables scalable classification of Earth system science
concepts
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Non-LivingSubstances
LivingSubstances
PhysicalProcesses
Earth Realm
PhysicalProperties
Time
NaturalPhenomena
Human Activities
Integrative Ontologies
Space
Data
Faceted Ontologies
Units
Numerics
SWEET 1.0 Ontologies
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SWEET 2.0 Ontologies: Modular Design
Mathematics Units
Electric/Magnetism
TimeSpace
RadiationTransfer
GeophysFluid Dynam
HumanActivities
ClimateChange
Troposphere
Thermo
Land Surface
Waves
Heliosphere Cryosphere
Mechanics
BasicScience/Math
SupportingGeophysicalPhenomena
PlanetaryRealms
ApplicationsAir Pollution
WaterResources
Geosphere
Ecosphere
Biogeo-chemistry
PlanetaryStructures
import
OceanUpper
Atmosphere
Geo-magnetism
PlanetaryGravity
BiogeochemCycles
Energy etc.
Chemistry
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SWEET Numerical Ontologies
Intervals, numeric relations (<,>) Cartesian products Functions, derivatives Fuzzy concepts
“near” Spatial concepts
0-D, 1-D, 2-D, and 3-D objects Coordinate systems Above, inside, etc.
Temporal concepts Instant, durations, geological time scales
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SWEET Data Ontology Dataset characteristics
Format, data model, dimensions, … Provenance
Source, processing history, … Parameters
Scale factors, offsets, … Data services
Subsetting, reprojection, … Quality measures Special values
Missing, land, sea, ice, ...
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Expressing More Complex Relations in OWL Many relations are quadruples, not
triples (Temperature hasValue 30 C) (JohnSmith hasExpertise Geology Expert)
Nested Solution (Temperature hasValue (30 C)) (JohnSmith (hasGeology Expertise)
Expert)
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Best Practices Keep ontologies small, modular
Be careful that “Owl:Import” imports everything Use higher level ontologies where possible
Identify hierarchy of concept spaces Model schemas Try to keep dependencies unidirectional
Gain community buy-in Involve respected leaders
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PlanetOnt.org
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SWEET Future Community Plans
Gain further support from Earth system science community Workshop at Summer ’08 Meeting of eSIP
Federation Submit SWEET as community standard
to NASA Earth Science Standards and Processes Working Group
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Tec
hn
olo
gy
Geospatial semantic services
established
Geospatial semantic services proliferate
Scientific semantic assisted services
SWEET 3.0 with semantic callable
interfaces via standard programming languages
SWEET core 2.0 based on best practices decided from community
Scientific reasoning
Reasoners able to utilize
SWEET 4.0
Local processing + data exchange
Basic data tailoring services (data as
service), verification/ validation
Interoperable geospatial services
(analysis as service), explanation
Common vocabulary based
product search and access
Inte
rop
erab
le
Info
rmat
ion
In
fras
tru
ctu
re
Ass
iste
d
Dis
cove
ry &
M
edia
tio
n
Metadata-driven data fusion
(semantic service chaining), trust
Semantic agent-based integration
Semantic agent-based
searches
Geospatial reasoning, OWL-
Time
Cap
ab
ilit
yR
esu
lts
Improved Information
Sharing
Increased Collaboration & Interdisciplinary
Science
Acceleration of Knowledge Production
Revolutionizing how science is
done
RDF, OWL, OWL-S
Semantic Web Roadmap
Current Near Term Mid Term Long Term
Autonomous inference of
science results
Numerical reasoning
Semantic geospatial search & inference, access
SWEET core 1.0 based on GCMD/CF
Vo
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ryL
ang
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Rea
son
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Ou
tpu
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utc
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e
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Resources SWEET
http://sweet.jpl.nasa.gov Ontology development/sharing site
http://PlanetOnt.org Noesis (search tool)
http://noesis.itsc.uah.edu SESDI
http://sesdi.hao.ucar.edu
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