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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

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Metadata-driven data fusion

(semantic service chaining), trust

Semantic agent-based integration

Semantic agent-based

searches

Geospatial reasoning, OWL-

Time

Cap

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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

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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