1. Developing Ontologies (and more)
Peter Fox (NCAR)
ESIP Winter Meeting (TIWG)
January 9, 2008, Washington, D.C.

2. Ontology Spectrum Thesauri “narrower term” relation Frames
Selected
Logical
Constraints
(disjointness,
inverse, …)
Frames
(properties)
Formal
is-a
Catalog/ ID
Informal
is-a
Formal
instance
General
Logical
constraints
Terms/
glossary
Value Restrs.
Originally from AAAI Ontologies Panel by Gruninger, Lehmann, McGuinness, Uschold, Welty;
– updated by McGuinness.
Description in:

3. Ontology - declarative knowledge
The triple: {subject-predicate-object}
interferometer is-a optical instrument
Fabry-Perot is-a interferometer
Optical instrument has focal length
Optical instrument is-a instrument
Instrument has instrument operating mode
Data archive has measured parameter
SO2 concentration is-a concentration
Concentration is-a parameter

4. Semantic Web Layers

5. Terminology
Ontology (n.d.). The Free On-line Dictionary of Computing.
An explicit
formal specification of how to represent the objects, concepts
and other entities that are assumed to exist in some area of
interest and the relationships that hold among them.
Semantic Web
An extension of the current web in which information is given well-defined meaning, better enabling computers and people to work in cooperation,
Primer:
Languages
OWL 1.0 (Lite, DL, Full) - Web Ontology Language (W3C)
RDF - Resource Description Framework (W3C)
OWL-S/SWSL - Web Services (W3C)
WSMO/WSML - Web Services (EC/W3C)
SWRL - Semantic Web Rule Language, RIF- Rules Interchange Format
Editors: Protégé, SWOOP, CoE, VOM, Medius, SWeDE, …
Languages:
OWL
RDF
OWL-S
SWSL
WSMO/WSML
Many other MLs exist, e.g. ESML, GML, but these are not ….
Reasoners -
OWL - Web Ontology Language (W3C)
RDF - Resource Description Framework (W3C)
OWL-S/SWSL - Web Services (W3C)
WSMO/WSML - Web Services (EC/W3C)
SWRL - Semantic Web Rule Language
PML - Proof Markup Language
ODM/MOF - Ontology Definition Metamodel/Meta Object Facility (OMG)
Editors: Protégé, SWOOP, Medius, SWeDE
Reasoners
Pellet, Racer, Medius KBS, FACT++, fuzzyDL, KAON2, MSPASS, QuOnto
Query Languages
SPARQL, XQUERY, SeRQL, OWL-QL, RDFQuery
Other Tools for Semantic Web
Search: SWOOGLE swoogle.umbc.edu
Collaboration:
Other: Jena, SeSAME/SAIL, Mulgara, Eclipse, KOWARI
Semantic wiki: OntoWiki, SemanticMediaWiki
SWEET sweet.jpl.nasa.gov
VSTO vsto.hao.ucar.edu,
MMI
GeoSciML

6. OWL and RDF OWL RDF Services Rules Lite DL Full OWL-S SWSL WSML
SAWSDL - (WSDL-S)
Rules
SWRL

7. Developing Ontologies
Approach:
Bottom-up
Top-down (upper-level or foundational)
Mid-level (use case)
Using tools
Coding and testing
Iterating
Maintaining and evolving (curation, preservation)

8. GRDDL - bottom up
GRDDL - Gleaning Resource Descriptions from Dialects of Languages
Pretty much = “XML/XHTML (for e.g.) into RDF via XSLT”
Good support, e.g. Jena
Handles microformats
Active community
How to categorize, use, re-use (parts of)?

9. Collecting RDFa extends XHTML by: ATOM (used with RSS)
extending the link and meta to include child elements
add metadata to any elements (a bit like the class in micro-formats, but via dedicated properties)
It is very similar to micro-formats, but with more rigor:
it is a general framework (instead of an “agreement” on the meaning of, say, a class attribute value)
terminologies can be mixed more easily
ATOM (used with RSS)
GRDDL = Gleaning Resource Descriptions from Dialects of Languages

10. Foundational Ontologies
CONTENTS
General concepts and relations that apply in all domains
physical object, process, event,…, inheres, participates,…
Rigorously defined
formal logic, philosophical principles, highly structured
Examples
DOLCE, BFO, GFO, SUMO, CYC, (Sowa)
Courtesy: Boyan Brodaric

11. Foundational ontology
Foundational Ontologies
PURPOSE: help integrate domain ontologies
“…and then there was one…”
Foundational ontology
Geophysics ontology
Marine ontology
Water ontology
Planetary ontology
Geology ontology
Struc ontology
Rock ontology
Courtesy: Boyan Brodaric

12. Foundational ontology
Foundational Ontologies
PURPOSE: help organize domain ontologies
“…a place for everything, and everything in its place…”
Foundational ontology
shale
rock
formation
lithification
Courtesy: Boyan Brodaric

13. Problem scenario
Little work done on linking foundational ontologies with geoscience ontologies
Such linkage might benefit various scenarios requiring cross-disciplinary knowledge, e.g.:
water budgets: groundwater (geology) and surface water (hydro)
hazards risk: hazard potential (geology, geophysics) and items at threat (infrastructure, people, environment, economic)
health: toxic substances (geochemistry) and people, wildlife
many others…
Courtesy: Boyan Brodaric

14. DOLCE

15. DOLCE + SWEET Benefits Issues full coverage rich relations
home for orphans
single superclasses
DOLCE
= SWEET
< SWEET
Physical-body
BodyofGround, BodyofWater,…
Material-Artifact
Infrastructure, Dam, Product,…
Physical-Object
LivingThing, MarineAnimal
Amount-of-Matter
Substance
Activity
HumanActivity
Physical-Phenomenon
Phenomena
Process
State
StateOfMatter
Quality
Quantity, Moisture,…
Physical-Region
Basalt,…
Temporal-Region
Ordovician,…
Issues
individuals (e.g. Planet Earth)
roles (contaminant)
features (SeaFloor)
Courtesy: Boyan Brodaric

16. Conclusions Surprisingly good fit amongst ontologies
so far: no show-stopper conflicts, a few difficult conflicts
DOLCE richness benefits geoscience ontologies
good conceptual foundation helps clear some existing problems
Unresolved issues in modeling science entities
modeling classifications, interpretations, theories, models,…
Same procedure with GeoSciML
Courtesy: Boyan Brodaric

17. SUMO - Standard Upper Merged Ontology
Physical
Object
SelfConnectedObject
ContinuousObject
CorpuscularObject
Collection
Process
Abstract
SetClass
Relation
Proposition
Quantity
Number
PhysicalQuantity
Attribute

20. Using SNAP/ SPAN

21. GeoSciOnt?

23. Using SWEET Plug-in (import) domain detailed modules
Lots of classes, few relations (properties)

24. Mix-n-Match The IRI example: MMI Others
Collect a lot of different ontologies representing different terms, levels of concepts, etc. into a base form: RDF
See Benno’s talk in session 1b.
MMI
Others

25. Blumenthal NC basic attributes CF attributes IRIDL attributes/objects
CF data objects
CF Standard Names
(RDF object)
SWEET Ontologies
(OWL)
Location
CF Standard Names
As Terms
IRIDL Terms
SWEET as Terms
Search Terms
Gazetteer Terms
Blumenthal

26. IRI RDF Architecture Blumenthal MMI Data Servers Ontologies JPL
bibliography
Start Point
Standards
Organizations
RDF Crawler
Location
Canonicalizer
RDFS Semantics
Owl Semantics
SWRL Rules
SeRQL CONSTRUCT
Time
Canonicalizer
Sesame
Search Queries
Blumenthal
Search Interface

27. Mid-Level: Developing ontologies
Use cases and small team (7-8; 2-3 domain experts, 2 knowledge experts, 1 software engineer, 1 facilitator, 1 scribe)
Identify classes and properties (leverage controlled vocab.)
Start with narrower terms, generalize when needed or possible
Adopt a suitable conceptual decomposition (e.g. SWEET)
Import modules when concepts are orthogonal
Review, vet, publish
Only code them (in RDF or OWL) when needed (CMAP, …)
Ontologies: small and modular

28. Use Case example
Plot the neutral temperature from the Millstone-Hill Fabry Perot, operating in the vertical mode during January 2000 as a time series.
Objects:
Neutral temperature is a (temperature is a) parameter
Millstone Hill is a (ground-based observatory is a) observatory
Fabry-Perot is a interferometer is a optical instrument is a instrument
Vertical mode is a instrument operating mode
January 2000 is a date-time range
Time is a independent variable/ coordinate
Time series is a data plot is a data product

29. Class and property example
Parameter
Has coordinates (independent variables)
Observatory
Operates instruments
Instrument
Has operating mode
Instrument operating mode
Has measured parameters
Date-time interval
Data product

33. Higher level use case
Find data which represents the state of the neutral atmosphere above 100km, toward the arctic circle at any time of high geomagnetic activity

34. Translating the Use-Case - non-monotonic?
GeoMagneticActivity has ProxyRepresentation
GeophysicalIndex is a ProxyRepresentation (in Realm of Neutral Atmosphere)
Kp is a GeophysicalIndex hasTemporalDomain: “daily”
hasHighThreshold: xsd_number = 8
Date/time when KP => 8
Specification needed for query to CEDARWEB
Instrument
Parameter(s)
Operating Mode
Observatory
Date/time
Return-type: data
Input
Physical properties: State of neutral atmosphere
Spatial:
Above 100km
Toward arctic circle (above 45N)
Conditions:
High geomagnetic activity
Action: Return Data

35. Translating the Use-Case - ctd.
NeutralAtmosphere is a subRealm of TerrestrialAtmosphere
hasPhysicalProperties: NeutralTemperature, Neutral Wind, etc.
hasSpatialDomain: [0,360],[0,180],[100,150]
hasTemporalDomain:
NeutralTemperature is a Temperature (which) is a Parameter
Translating the Use-Case - ctd.
Specification needed for query to CEDARWEB
Instrument
Parameter(s)
Operating Mode
Observatory
Date/time
Return-type: data
Input
Physical properties: State of neutral atmosphere
Spatial:
Above 100km
Toward arctic circle (above 45N)
Conditions:
High geomagnetic activity
Action: Return Data
FabryPerotInterferometer is a Interferometer, (which) is a Optical Instrument (which) is a Instrument
hasFilterCentralWavelength: Wavelength
hasLowerBoundFormationHeight: Height
ArcticCircle is a GeographicRegion
hasLatitudeBoundary:
hasLatitudeUpperBoundary:
GeoMagneticActivity has ProxyRepresentation
GeophysicalIndex is a ProxyRepresentation (in Realm of Neutral Atmosphere)
Kp is a GeophysicalIndex hasTemporalDomain: “daily”
hasHighThreshold: xsd_number = 8
Date/time when KP => 8

36. Tools - Using Protégé

37. Creating Ontologies - visual
UML - new release of ODM/MOF
Ontology Definition Metamodel/Meta Object Facility (OMG) for UML
Provides standardized notation
CMAP Ontology Editor (concept mapping tool from IHMC)
Drag/drop visual development of classes, subclass (is-a) and property relationship
Read and writes OWL
Formal convention (OWL/RDF tags, etc.)
White board, text file

38. Using CMAP/COE

40. Is OWL the only option? No…
SKOS - Simple Knowledge Organization Scheme
Annotations (RDFa)
Atom
Natural Language (read results from a web search and transform to a usable form)
CL (common logic)
Rabbit, e.g. ShellfishCourse is a Meal Course that (if has drink) always has drink Potable Liquid that has Full body and which either has Moderate or Strong flavour
PENG (processable English)

41. Is OWL the only option II? No…
Natural Language (NL)
Read results from a web search and transform to a usable form
Find/filter out inconsistencies, concepts/relations that cannot be represented
Popular options
CLCE (common logic controlled english)
Rabbit, e.g. ShellfishCourse is a Meal Course that (if has drink) always has drink Potable Liquid that has Full body and which either has Moderate or Strong flavour
PENG (processable English)
Really need PSCI - process-able science

42. Creating Ontologies - verbal
Translating use cases
E.g. Find data which represents the state of the neutral atmosphere above 100km, toward the arctic circle at any time of high geomagnetic activity
Can this be expressed as an ontology?
CLCE, Rabbit, PENG, Sydney syntax
Notice something about the next examples?

43. Sydney syntax If X has Y as a father then Y is the only father of X.
The class person is equivalent to male or female, and male and female are mutually exclusive.
equivalent to
The classes male and female are mutually exclusive. The class person is fully defined as anything that is a male or a female.

44. PENG - Processible English
If X is a research programmer then X is a programmer.
Bill Smith is a research programmer who works at the CLT.
Who is a programmer and works at the CLT?

45. CLCE - Common Logic Controlled English
CLCE: If a set x is the set of (a cat, a dog, and an elephant), then the cat is an element of x, the dog is an element of x, and the elephant is an element of x.
PC:~(∃x:Set)(∃x1:Cat)(∃x2:Dog)(∃x3:Elephant)(Set(x,x1,x2,x3) ∧ ~(x1∈x ∧ x2∈x ∧ x3∈x))

46. Use Case
Provide a decision support capability for an analyst to determine an individual’s susceptibility to avian flu without having to be precise in terminology (-nyms)

49. Using ThManager

50. Services Ontologies of services, provides:
What does the service provide for prospective clients? The answer to this question is given in the "profile," which is used to advertise the service. To capture this perspective, each instance of the class Service presents a ServiceProfile.
How is it used? The answer to this question is given in the "process model." This perspective is captured by the ServiceModel class. Instances of the class Service use the property describedBy to refer to the service's ServiceModel.
How does one interact with it? The answer to this question is given in the "grounding." A grounding provides the needed details about transport protocols. Instances of the class Service have a supports property referring to a ServiceGrounding.

51. Developing a service ontology
Use case: find and display in the same projection, sea surface temperature and land surface temperature from a global climate model.
Find and display in the same projection, sea surface temperature and land surface temperature from a global climate model.
Classes/ concepts:
Temperature
Surface (sea/ land)
Model
Climate
Global
Projection
Display …

52. Service ontology Climate model is a model Model has domain
Climate Model has component representation
Land surface is-a component representation
Ocean is-a component representation
Sea surface is part of ocean
Model has spatial representation (and temporal)
Spatial representation has dimensions
Latitude-longitude is a horizontal spatial representation
Displaced pole is a horizontal spatial representation
Ocean model has displaced pole representation
Land surface model has latitude-longitude representation
Lambert conformal is a geographic spatial representation
Reprojection is a transform between spatial representation ….

53. Service ontology
A sea surface model has grid representation displaced pole and land surface model has grid representation latitude-longitude and both must be transformed to Lambert conformal for display

54. Best practices
Ontologies/ vocabularies must be shared and reused - swoogle.umbc.edu,
Examine ‘core vocabularies’ to start with
SKOS Core: about knowledge systems
Dublin Core: about information resources, digital libraries, with extensions for rights, permissions, digital right management
FOAF: about people and their organizations
DOAP: on the descriptions of software projects
DOLCE seems the most promising to match science ontologies
Go “Lite” as much as possible, then DL and only if you have to Full - balancing expressibility vs. implementability
Minimal properties to start, add only when needed

55. Tutorial Summary
Many different options for ontology development and encoding
Tools are in reasonable shape, no killer-tool
Best practices DO exist
PLEASE DO NOT just start coding OWL!
Use case should drive the functional requirements of both your ontology and how you will ‘build’ one
PARTNER with someone already familiar

56. More information OWL-S - http://www.w3.org/Submission/OWL-S
SWSO/F/L - Semantic Web Services Ontology/Framework/Language -
WSMO/X/L - Web Services Modeling Ontology/Exection/Language
SAWSDL - (WSDL-S)

57. Other tools Reasoners Query Languages Other Tools for Semantic Web
Pellet, Racer, Medius KBS, FACT++, fuzzyDL, KAON2, MSPASS, QuOnto
Query Languages
SPARQL, XQUERY, SeRQL, OWL-QL, RDFQuery
Other Tools for Semantic Web
Search: SWOOGLE swoogle.umbc.edu
Collaboration:
Other: Jena, SeSAME/SAIL, Mulgara, Eclipse, KOWARI
Semantic wiki: OntoWiki, SemanticMediaWiki
Languages:
OWL
RDF
OWL-S
SWSL
WSMO/WSML
Many other MLs exist, e.g. ESML, GML, but these are not ….
Reasoners -
OWL - Web Ontology Language (W3C)
RDF - Resource Description Framework (W3C)
OWL-S/SWSL - Web Services (W3C)
WSMO/WSML - Web Services (EC/W3C)
SWRL - Semantic Web Rule Language
PML - Proof Markup Language
ODM/MOF - Ontology Definition Metamodel/Meta Object Facility (OMG)
Editors: Protégé, SWOOP, Medius, SWeDE
Reasoners
Pellet, Racer, Medius KBS, FACT++, fuzzyDL, KAON2, MSPASS, QuOnto
Query Languages
SPARQL, XQUERY, SeRQL, OWL-QL, RDFQuery
Other Tools for Semantic Web
Search: SWOOGLE swoogle.umbc.edu
Collaboration:
Other: Jena, SeSAME/SAIL, Mulgara, Eclipse, KOWARI
Semantic wiki: OntoWiki, SemanticMediaWiki
SWEET sweet.jpl.nasa.gov
VSTO vsto.hao.ucar.edu,
MMI
GeoSciML

58. Editors Protégé (http://protégé.stanford.edu)
SWOOP (
Altova SemanticWorks (
SWeDE ( goes with Eclipse
Medius
TopBraid Composer and other commercial tools
Visual Ontology Modeler (VOM) - Sandpiper
CMAP Ontology Editor (COE) (

59. What about Earth Science?
SWEET (Semantic Web for Earth and Environmental Terminology)
based on GCMD terms
modular using faceted and integrative concepts
VSTO (Virtual Solar-Terrestrial Observatory)
captures observational data (from instruments)
modular using domains
MMI
captures aspects of marine data, ocean observing systems
partly modular, mostly by developed project
GeoSciML
is a GML (Geography ML) application language for Geoscience
modular, in ‘packages’