speeding up ontology creation of scientific terms

Speeding up ontology creation of scientific terms.

Luis Bermudez , John Graybeal,Montery Bay Aquarium Research Institute

http://marinemetadata.org

December 7, 2005

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etadata Interoperability Initiative

Why are ontologies importantAt AGU we

have 31 abstracts and 2 entire sessions related to ontologies

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Problem: Semantic Interoperability

SSDS

AOSN

get me Data for Variable ocean_temperature (C)

get me Data for Parameter temperature_1(deg C)

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Need for controlled vocabulary

A set of restricted words, used by an information community when describing resources or discovering data. The controlled vocabulary prevents misspellings and avoids the use of arbitrary, duplicative, or confusing words that cause inconsistencies when cataloging data.

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Controlled Vocabularies: Discovery of Data

GCMD HTMLhttp://gcmd.gsfc.nasa.gov/Resources/valids

BODC Discovery

Comma Separated Value

http://wwwtest.bodc.ac.uk/data/ codes_and_formats/parameter_codes/bodc_para_dict.html

AGU Index Terms HTMLhttp://www.agu.org/pubs/ gaplist.html

MEL HTMLhttps://mel.dmso.mil/docs/metadata_guide/section_6.htm

NOAA CoRIS Thesauri PDF

http://www.coris.noaa.gov/backmatter/keywords/discovery_ thesaurus.pdf

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Controlled Vocabularies: Usage (tag the data collected)

BODC

Comma Separated Value

http://wwwtest.bodc.ac.uk/data/ codes_and_formats/parameter_codes/bodc_para_dict.html

U.S. JGOFS Dictionary of parameters HTML

http://usjgofs.whoi.edu/datasys/ param_master.html

IOC GF3 parameter codes HTML

http://ioc.unesco.org/oceanteacher/ resourcekit/M3/Formats/Integrated/GF3/GF3.htm

SEACOOS

Comma Separated value

http://twiki.sura.org/twiki/pub/Main/DataStandards/seacoos_draft_data_ dictionary_v2.0.csv

CF XMLhttp://www.cgd.ucar.edu/cms/eaton/cf-metadata/standard_name.xml

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Problem: Semantic Interoperability

semantics semantics

Standard vocabularies

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Harmonization

DTDDTD

Comma Comma Separated Separated

ValuesValues

HTMLHTML

Tab Tab Separated Separated

ValuesValues

Relational Relational DatabaseDatabase

XML/XSDXML/XSD

RDFRDF

Web OntologyWeb Ontology Language (OWL)Language (OWL)

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Web Ontology Language: OWL

2003 World Wide Web Consortium recommendation to formally express ontologies.

Based on the Resource Description Framework (RDF).

Can be serialized in XML. Supporting tools: JENA, Protégé, SWOOP,

Sesame, Pangloss, Kuwari, VINE, Voc2OWL

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Fast introduction to OWL

RDF TriplesRDF ResourcesClasses - individuals - propertiesRDF Graph

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RDF: Triples, triples, triples

id description unitsocean_

temperatureOcean

Temperature C

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RDF: Resource

Resources

A resource is anything on the Web that has a unique identifier. Examples:

URI: urn:aosn.mbari.org.recordVariable.id:1900 URL: http://mmi.org/2005/08/gcmd-keyw#Chlorophyll URL: ftp://mmi.org/data-example

Literal

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Parameters

id description units

Temperature_1water temperature from unit 00471 deg C


Looks like a class

Looks like individuals of (members of) the class Parameter

Classes Individuals Properties

Property (Attributes)

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How are ontologies created?

Conceptual direction strategy:

Up - down

Bottom - up

Automation approach:

Manual

Automatic

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Up - down approach

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Bottom - up approach

Body of Water Class

RiverLake

Has water

Is inland body

Has a relative defined channel

Lake RiverExample:1. Properties of real

world objects are identified.

2. Similarities are identified.

3. Concepts are created

4. and are expressed as a class.

5. Classes are related.

Subclass

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id description unitsTemperature deg C

temperature

Temperature inside the OASIS can, in degrees C

Temperature

temperature measured inside the MMC controller

Temperature CelsiusTemperature degrees CTemperature water temperature deg C



Bottom - up approach

id description unitsocean_temperature Ocean Temperature Cocean_temperature_2 Ocean Temperature 2 C

ocean_temperature_allOcean TemperatureAll

C

ocean_temperature_qcflag

Ocean TemperatureQcflag

0=good,1=missing,2=marginal,3=bad

ocean_temperature_rawOcean TemperatureRaw

counts

sea_surface_temperatureSea SurfaceTemperature

C

ssds:Parameter

aosn:Variable

Example:1.Real word objects:

parameters in observatory systems.

2.They all have similar properties (id, description and units).

3. Make them a resource: instance of a class Parameter

rdf:type

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Bottom - up approach (cont.)

ssds:Parameter

aosn:Variable

mmi:Parameter

sweet:Property

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Manual (Ontology editor)

List of more than 50 editors: http://www.xml.com/2002/11/06/Ontology_Editor_Survey.html

Protégé

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Automatic

Ontology in Ontology in OWLOWL

Software Program

transformationProperties file

id description unitsocean_temperature Ocean Temperature Cocean_temperature_2 Ocean Temperature 2 C

ocean_temperature_allOcean TemperatureAll

C

ocean_temperature_qcflag

Ocean TemperatureQcflag

0=good,1=missing,2=marginal,3=bad

ocean_temperature_rawOcean TemperatureRaw

counts

sea_surface_temperatureSea SurfaceTemperature

C

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Automatic

Advantages Fast Preserves a connection with the source

( back - compatibility ) Avoids typing and copy/paste errors

Disadvantage Only works with simple vocabularies

( Flat vocabularies, and some taxonomies)

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VOC2OWL

Tool created by MMIAllows to create automatic - bottom -up

ontologies from two basic structures of simple vocabularies: Flat vocabularies (e.g. phone directory) Hierarchical vocabularies (e.g.

taxonomies)JAVA - Eclipse standalone application

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Metadata

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Conversion Properties I/OFormat of the ASCII file to transform: tab or csv

Location of the ASCII file

Location where the ontology in OWL will be saved

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Ontology Conversion Properties

Namespace of the resources

Column from where the local names of the resources (individuals) will be created.

One class (at least) is always created.

More than one class can be created

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ResultParameters

id description units



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Ontology Conversion Properties

If treated as a hierarchy, there is no such primary class. All the lines in the ASCII file represent a hierarchy

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Example Hierarchy (GCMD)

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Has been tested !

About 50 vocabularies were converted to OWL for the MMI workshop “ Advancing Domain Vocabularies” (Aug, 2005)

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Why do we need all these ontologies ?

Workshop was about relating terms from one controlled vocabulary to another one.

Microsoft Excel was to hard to use for this purpose -:)

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Mapping results

Topic Direct

mappings Inferred mappings

Total mappings

Plant Pigments 405 1,022 1,427

PaCOOS 131 375 506

Waves 93 181 274

Currents 90 153 243

CTD 81 432 513

Habitats 23 37 60

Total 823 2,200 3,023

47 participants and 12 hours of mapping time

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VINE : Vocabulary Integration Environment

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More…

• Advance the Marine Knowledge: 250,000 RDF triples (Ontologies + mappings)• They are available as:

• SOAP web services at: http://marinemetadata.org/webservices• Ontology files at: http://marinemetadata.org/ns

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Conclusions

• Solving semantic interoperability issues is fun.• We need to relate data producers vocabularies with standard vocabularies.• OWL is growing and growing in popularity more and more tools will be available.• VOC2OWL can help you !

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Our Guides

Roy Lowry, BODC Robert Arko, LDEO Julie Bosch, NOAA Ben Domenico, Unidata Karen Stocks, SDSC Steve Hankin, NOAA -

Ocean.US/DMAC

Mark Musen, Stanford Univ Michael Parke, Univ of Hawaii Lola Olsen, NASA Goddard Bob Weller, WHOI Dawn Wright, Oregon State

University

Steering Committee

Executive Committee

John Graybeal, MBARI. (PI) Philip Bogden, SURA/SCOOP

Stephen Miller, SIO. Francisco Chavez, MBARI.

Stephanie Watson, Texas A&M

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MMI:Your Handy Reference GuideMMI: http://marinemetadata.org

Voc2OWL: http://marinemetadata.org/voc2owl

Vine: http://marinemetadata.org/vine

Help Line: [email protected]

Ontologies: http://marinemetadata.org/ns

Term Search:

http://mmi.mbari.org:9600/mmi2/search.jsp

Tethys: http://marinemetadata.org/tethys

speeding up ontology creation of scientific terms

Documents

parameter temperature

water temperature

temperature cget

allocean temperature

deg ctemperature

deg cocean

voc2owlweb ontology

individuals of members