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Building Ontologies from the Ground Up

When users set out to model their professional activity

Mark A. MusenProfessor of Medicine and Computer Science

Stanford University

v 1.00

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“An ontology is a specification of a conceptualization” (T. Gruber)

• A conceptualization is the way we think about a domain

• A specification provides a formal way of writing it down

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Supreme genus: SUBSTANCE

Subordinate genera: BODY SPIRIT

Differentiae: material immaterial

Differentiae: animate inanimate

Differentiae: sensitive insensitive

Subordinate genera: LIVING MINERAL

Proximate genera: ANIMAL PLANT

Species: HUMAN BEAST

Differentiae: rational irrational

Individuals: Socrates Plato Aristotle …

Porphyry’s depiction of Aristotle’s Categories

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Creating Ontologies in Machine-Processable Form

• Provides a mechanism for developers to codify salient distinctions about the world or some application area

• Provides a structure for knowledge bases that can enable– Information retrieval

– Information integration

– Automated translation

– Decision support

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The New Philosophers

• Categorizing “what exists” in machine-understandable form

• Providing a structure that enables– Developers to locate and update relevant

descriptions – Computers to infer relationships and properties

• Creating new abstractions to facilitate the creation of this structure

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Part of the CYC Upper Ontology

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There is a misconception …

• That people building ontologies are all well versed in metaphysics, computer science, knowledge representation, and the content domain

• That ontologies in the real world are as “clean” as SUMO, DOLCE, and other upper-level ontologies

• That most people who are creating ontologies understand all the ramifications of what they are doing!

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Lots of ontology builders are not very good philosophers

• Nearly always, ontologies are created to address pressing professional needs

• The people who have the most insight into professional knowledge may have little appreciation for metaphysics, principles of knowledge representation, or computational logic

• There simply aren’t enough good philosophers to go around

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Practical Problems

BioInformatics

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The pressing need to standardize the names of human genes

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But the human genome is only part of the problem …

• Scientist maintain huge databases of gene sequences and gene expression for a wide range of “model organisms” (e.g., mouse, rat, yeast, fruit fly, round worm, slime mold)

• Database entries are annotated with the entries such as the name of a gene, the function of the gene, and so on

• How do you ensure uniformity in the nature of these annotations?

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Gene Ontology Consortium

• Founded in 1998 as a collaboration among scientists responsible for developing different databases of genomic data for model organisms (fruit fly, yeast, mouse)

• Now, essentially all developers of all model-organism databases participate

• Goal: To produce a dynamic, controlled vocabulary that can be applied to all organism databases even as knowledge of gene and protein roles in cells is accumulating and changing

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Gene Ontology (GO)

• Comprises three independent “ontologies”

– molecular function of gene products

– cellular component of gene products

– biological process representing the gene product’s higher order role.

• Uses these terms as attributes of gene products in the collaborating databases (gene product associations)

• Allows queries across databases using GO terms, providing linkage of biological information across species

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GO = Three OntologiesGO = Three Ontologies

• Molecular Function – elemental activity or task

– example: DNA binding

• Cellular Component – location or complex

– example: cell nucleus

• Biological Process – goal or objective within cell

– example: secretion

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GO has been wildly successful!!

• Dozens of biologists around the world contribute to GO on a regular basis

• The ontology is updated every 30 minutes!

• It’s now impossible to work in most areas of computational biology without making use of GO terms

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But GO has real problems …

• Ontologies are represented in an idiosyncratic format that is not compatible with standard knowledge-representation systems

• The format is based on directed acyclic graphs of concepts, without the general ability to specify machine interpretable properties of concepts or definitions of concepts

• Because of the informal knowledge-representation system, lots of errors have crept into GO– Terms that are duplicated in different places– Terms with no superclasses– Uncertain relationships between terms

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Tension in the GO Community

• Biologists around the world with pressing needs to integrate research databases work together to add terms to GO nearly continuously– Using an impoverished, nonstandard knowledge-

representation system– Using no standards to assure uniform modeling

conventions from one part of GO to another

• Computer scientists bemoan all this ad-hoc-ery and condemn GO as a hack that will become increasingly unusable and unmaintainable

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The Capulets and MontaguesA plague on both your houses?

Professor Carole GobleUniversity of Manchester, UK

Warning: This talk contains sweeping generalisations

A wonderful keynote talk from the recent meeting on Standards and Ontologies for Functional Genomics

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PrologueTwo households, both alike in dignity,In fair genomics, where we lay our scene,(One, comforted by its logic’s rigour,Claims ontology for the realm of pure,The other, with blessed scientist’s vigour,Acts hastily on models that endure),From ancient grudge break to new mutiny,When “being” drives a fly-man to blaspheme.From forth the fatal loins of these two foesResearchers to unlock the book of life;Whole misadventured piteous overthrowsCan with their work bury their clans’ strife.The fruitful passage of their GO-mark'd love,And the continuance of their studies sage,Which, united, yield ontologies undreamed-of,Is now the hours' traffic of our stage;The which if you with patient ears attend,What here shall miss, our toil shall strive to mend.

Based on an idea by Shakespeare

Carole Goble

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The Montagues

Computer Science, Knowledge engineering, AILogic and Languages

TheoryTop down, well-behaved neatness

Generic and lots of toysMethodologies & patterns

Tools and standardsTechnology pushAcademic pursuit

One, comforted by its logic’s rigour,

Claims ontology for the realm of pure

Carole Goble

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The Capulets

Life ScientistsPractice

Bottom up, real-worldSpecific and many of them

Methodologies, community practiceTools and standards

Application pullPractical pursuit – build ‘n’ use it

The other, with blessed scientist’s vigour,

Acts hastily on models that endure

Carole Goble

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The Philosophers

PhilosophersTheoryTruth

Generic – the one true ontology?Methodologies, patterns & foundational ontologies

Not really into tools No push or pull

Academic pursuit

One, comforted by its logic’s rigour,

Claims ontology for the realm of pure

Carole Goble

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Pragm

atists

Aesthetics

Philosophers

Life ScientistsCapulets

KRMontagues

A means to an endContent providers

Theo

retic

ians

The endMechanism providers

Endurants, Perdurants,Being, Substance, Event

Spi

ritua

l gui

des

Carole Goble

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The Princes of Genomics

Rebellious subjects, enemies to peace,Profaners of this neighbour-stained steel,--Will they not hear? What, ho! you men, you beasts,That quench the fire of your pernicious rageWith purple fountains issuing from your veins,On pain of torture, from those bloody handsThrow your mistemper'd weapons to the ground,And hear the sentence of your moved prince.Three civil brawls, bred of an airy word,By thee, old Capulet, and Montague,Have thrice disturb'd the quiet of our streets,And made genomics's ancient citizensCast by their grave beseeming ornaments,To wield old partisans, in hands as old,Canker'd with peace, to part your canker'd hate:

Carole Goble

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A tragedy?

As in Romeo and Juliette, the threats are political

and sociological

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Creating ontologies has become a widespread cottage industry

• Professional Societies– MGED: Microarray Gene Expression Data Society– HUPO: Human Protein Organization

• Government– NCI Thesaurus– NIST: Process Specification Language

• Open Biological Ontologies– GO– Three dozen (and growing) other ontologies– Mostly in DAG-Edit, some in Protégé format

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Government Continues to be a Major Driving Force

• Highly visible intramural initiatives to create public ontologies at many agencies, including NIST, NIH, VA, CDC

• Notable variation in these ontologies’– Scope

– Representational sophistication

– “Openness” of content

– Opportunities for peer review

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NCI Enterprise Vocabulary Services

1997: R. Klausner, Director NCI, wanted a “science management system”

• Know about everything funded by NCI

• Goals and results – “bench to bedside”

- Thereby improve and speed translation of research

Approach:1. Create integrative terminology2. Evolve terminology scope from supporting grants

management to supporting science3. Build Web-accessible infrastructure – caCORE

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More than 37,000 concepts are represented with extremely detailed granularity in many areas

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Definitions may include considerable detail with respect to properties that establish relationships with other concepts

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NCI Thesaurus is in Active Usenciterms.nci.nih.gov

ncicb.nci.nih.gov/core/EVS (more info)

Website: 1500-4000 page hits daily, 14K unique visitors (2004)

• API: NCICB & external applications

• Fulfills NCI and collaborators’ needs for controlled vocabulary

• Public domain, open content license

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NCI Thesaurus Guidelines

• Develop content model (based on Ontylog

description logic from Apelon, Inc.)• Leverage existing sources as appropriate

– MeSH, VA NDF-RT, MedDRA …

• Develop unique content where needed– Cancer genes, gene products, cancer diagnoses, drugs,

chemotherapies, molecular abnormalities etc., and relationships among them

• Link to other standards using URLs where possible– OMIM, Swissprot, GO

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:

ProductionRelease

ExternalTesting

NCI ThesaurusTest DTSServers

NCI ThesaurusEditing Environment

NCI ThesaurusWorkflow

Conflict Detectionand Resolution

Work ListGeneration

Classification

HxValidation

Hx

Baseline

Schema

Schema

Schema

Individual Editors’ TDE Workflow Client Editing Application DB Schema - Current NCI Baseline - Local History

Lead Editor TDE Work Manager Client Editing Application Conflict Detection/Resolution DB Schema - Master NCI Baseline - Master History

ChangeSet

WorkAssignment

CandidateRelease

Hx

NCI ThesaurusProduction

DTS Servers

Hx

Release

NCI uses an Elaborate Process for Editing and Maintenance

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The NCI Thesaurus is not without its problems

• Upper level concepts are sometimes used inconsistently or not at all

• Textual definitions of concepts may not always reflect the meaning implied by the concepts’ position in the ontology

• Reliance on a proprietary knowledge-representation system – Prevents the ability to disseminate the ontology freely– Adds an unfortunate degree of uncertainty to the

semantics

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Throughout this cottage industry

• Lots of ontology development, principally by content experts with little training in conceptual modeling

• Use of development tools and ontology-definition languages that may be– Extremely limited in their expressiveness– Useless for detecting potential errors and guiding

correction– Nonadherent to recognized standards– Proprietary and expensive

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But the world is beginning to change!

• The Montagues do want to get the modeling right!

• The Capulets do want to see their work used by others!

• Useful, open tools and standards are now available that make it hard to justify closed, proprietary approaches

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Some signs the world is changing …

• Developers of several overlapping and incompatible ontologies of anatomy suddenly are trying to understand why their models do not agree

• Philosopher Barry Smith suddenly is camping out at biomedical informatics meetings to get the attention of ontology developers

• NCI is piloting the use of OWL and Protégé to encode and manage the NCI thesaurus

• MGED and several other biomedical ontologies are being authored in OWL and Protégé from the beginning

• Downloads of the Protégé system continue to escalate

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Total Protege RegistrationsThrough 10/13/04

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10000110001200013000140001500016000170001800019000200002100022000

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Protégé’s main features

• Simplified editing of ontologies and knowledge bases• Open-source distribution to encourage development by a

world-wide community of users• A plug-in architecture that enables developers to add new

features easily• Support for a wide range of representation formats

– CLIPS/COOL– XML Schema– UML– RDF– OWL

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Protégé is ecumenical in its support for formal languages

• Open Knowledge Base Connectivity Protocol– CLIPS/COOL– UML– XML Schema– RDF and RDFS– Topic Maps

• Ontology Web Language (OWL)

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Protégé remains successful because of its user community

• There are now 89 plug-ins available for use with Protégé• Collaboration with our users enables rapid debugging and

code fixes• Some development, such as the creation of extensions to

our basic OWL capabilities, has been a major collaborative experience

• Annual users groups meetings provide great opportunities for developers to share strategies, principles, and war stories

• Members of the international Protégé community are a huge support base for new users and for fledgling projects

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The NCI Thesaurus

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Moving from cottage industry to the industrial age

• There must be widely available tools that are open-source, that are easy to use, and that adhere to knowledge representation standards: Protégé certainly is a candidate

• There must be a large user user community of developers who use the tools and who can provide feedback to one another and to the core team of tool builders

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Moving from cottage industry to the industrial age II

• Government and professional societies must set expectations regarding the need for appropriate standards

• Government and professional societies must invest in educational programs to teach Montagues to identify with Capulets, and vice versa

• Demonstration projects must communicate to the potential developers of future ontologies the strengths and weaknesses of the guidelines, tools, and languages that facilitated the development work

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A thousand flowers are blooming from every corner of the landscape

• Ontologies are being developed by interested groups from every sector of academia, industry, and government

• Many of these ontologies have been proven to be extraordinarily useful to wide communities

• Many of these same ontologies have been shown to be structurally flawed and of uncertain semantics

• We finally are at the stage where we have tools and representation languages that can lift us out of the grass roots to create durable and maintainable ontologies with rich semantic content

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An infrastructure is now in place

• The need to build new ontologies in environmental health, phenotypic expression in model organisms, developmental biology, and many, many other domains is getting wide attention

• We finally have the tools and the languages to do things right

• Now all we need now is the will, the educational opportunities, and the community feedback to help developers at the grass roots to reemerge as philosophers and princes.

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Let’s have a happy ending.

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Editing OWL Ontologieswith Protégé

Holger KnublauchStanford University

July 06, 2004

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This Tutorial

• Introduction to OWL, the Semantic Web, and the Protégé OWL Plugin

• Theory + Walkthrough

• Also available: Tutorial by Matthew Horridge (http://www.co-ode.org)– Similar content but more details on logic– Other example scenario (Pizzas)

• ... Workshop (this afternoon)

• ... Talks (tomorrow morning)

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Overview

The Semantic Web and OWL

Basic OWL

Interactive: Classes, Properties

Advanced OWL

Interactive: Class Descriptions

Creating Semantic Web Contents

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The Semantic WebShared ontologies help to exchange data

and meaning between web-based services

(Image by Jim Hendler)

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Wine Example ScenarioTell me what wines I should buy to serve

with each course of the following menu.

Wine Agent

Grocery Agent

Books Agent

I recommend Chardonney or

DryRiesling

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Ontologies in the Semantic Web

• Provide shared data structures to exchange information between agents

• Can be explicitly used as annotations in web sites

• Can be used for knowledge-based services using other web resources

• Can help to structure knowledge to build domain models (for other purposes)

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OWL

• Web Ontology Language

• Official W3C Standard since Feb 2004

• Based on predecessors (DAML+OIL)

• A Web Language: Based on RDF(S)

• An Ontology Language: Based on logic

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OWL Ontologies

• What’s inside an OWL ontology– Classes + class-hierarchy– Properties (Slots) / values– Relations between classes

(inheritance, disjoints, equivalents)– Restrictions on properties (type, cardinality)– Characteristics of properties (transitive, …)– Annotations– Individuals

• Reasoning tasks: classification,consistency checking

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OWL Use Cases

• At least two different user groups– OWL used as data exchange language

(define interfaces of services and agents)– OWL used for terminologies or knowledge

models

• OWL DL is the subset of OWL (Full) that is optimized for reasoning and knowledge modeling

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Protégé OWL Plugin

• Extension of Protégé for handling OWL ontologies

• Project started in April 2003

• Features– Loading and saving OWL files & databases– Graphical editors for class expressions– Access to description logics reasoners– Powerful platform for hooking in custom-

tailored components

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Tutorial Scenario

• Semantic Web for Tourism/Traveling

• Goal: Find matching holiday destinations for a customer

I am looking for a comfortable destination

with beach access

Tourism Web

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Scenario Architecture

• A search problem: Match customer’s expectations with potential destinations

• Required: Web Service that exploits formal information about the available destinations– Accomodation (Hotels, B&B, Camping, ...)– Activities (Sightseeing, Sports, ...)

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Tourism Semantic Web

• Open World:– New hotels are being added– New activities are offered

• Providers publish their services dynamically

• Standard format / grounding is needed → Tourism Ontology

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Tourism Semantic Web

OWLMetadata

(Individuals)

OWLMetadata

(Individuals)

OWLMetadata

(Individuals)

OWLMetadata

(Individuals)

Tourism Ontology

Web Services

Destination

AccomodationActivity

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OWL (in Protégé)

• Individuals (e.g., “FourSeasons”)

• Properties– ObjectProperties (references)– DatatypeProperties (simple values)

• Classes (e.g., “Hotel”)

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Individuals

• Represent objects in the domain

• Specific things

• Two names could represent the same “real-world” individual

SydneysOlympicBeachBondiBeach

Sydney

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ObjectProperties

• Link two individuals together

• Relationships (0..n, n..m)

Sydney

BondiBeachhasPart

FourSeasonshasAccomodation

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Inverse Properties

• Represent bidirectional relationships

• Adding a value to one property also adds a value to the inverse property

Sydney

BondiBeachhasPart

isPartOf

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Transitive Properties

• If A is related to B and B is related to C then A is also related to C

• Often used for part-of relationships

Sydney

BondiBeach

hasPart

NewSouthWales

hasPart

hasPart (derived)

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DatatypeProperties

• Link individuals to primitive values(integers, floats, strings, booleans etc)

• Often: AnnotationProperties without formal “meaning”

Sydney

hasSize = 4,500,000isCapital = truerdfs:comment = “Don’t miss the opera house”

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Classes

• Sets of individuals with common characteristics

• Individuals are instances of at least one class

City

Sydney

Beach

Cairns

BondiBeach

CurrawongBeach

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Range and Domain

• Property characteristics– Domain: “left side of relation” (Destination)– Range: “right side” (Accomodation)

Sydney

BestWestern

FourSeasonshasAccomodation

DestinationAccomodation

hasAccomodation

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Domains

• Individuals can only take values of properties that have matching domain– “Only Destinations can have

Accomodations”

• Domain can contain multiple classes

• Domain can be undefined:Property can be used everywhere

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Superclass Relationships

• Classes can be organized in a hierarchy

• Direct instances of subclass are also (indirect) instances of superclasses

Cairns

Sydney

Canberra

Coonabarabran

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Class Relationships

• Classes can overlap arbitrarily

City

Sydney

CairnsBondiBeach

RetireeDestination

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Class Disjointness• All classes could potentially overlap

• In many cases we want to make sure they don’t share instances

Sydney

UrbanArea RuralArea

SydneyWoomera

CapeYork

disjointWith

City Destination

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(Create a new OWL project)

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(Create simple classes)

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(Create class hierarchy and set disjoints)

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(Create Contact class with datatype properties)

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(Edit details of datatype properties)

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(Create an object property hasContact)

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(Create an object property with inverse)

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(Create the remaining classes and properties)

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Class Descriptions• Classes can be described by their

logical characteristics

• Descriptions are “anonymous classes”

Things with three star accomodation

Things with sightseeing opportunities

RetireeDestination

SydneySanJose

BlueMountains

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Class Descriptions

• Define the “meaning” of classes

• Anonymous class expressions are used– “All national parks have campgrounds.”– “A backpackers destination is a destination

that has budget accomodation and offers sports or adventure activities.”

• Expressions mostly restrict property values (OWL Restrictions)

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Class Descriptions: Why?

• Based on OWL’s Description Logic support

• Formalize intentions and modeling decisions (comparable to test cases)

• Make sure that individuals fulfill conditions

• Tool-supported reasoning

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Reasoning with Classes

• Tool support for three types of reasoning exists:– Consistency checking:

Can a class have any instances?

– Classification:Is A a subclass of B?

– Instance classification:Which classes does an individual belong to?

• For Protégé we recommend RACER(but other tools with DIG support work too)

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Restrictions (Overview)

• Define a condition for property values– allValuesFrom– someValuesFrom– hasValue– minCardinality– maxCardinality– cardinality

• An anonymous class consisting of all individuals that fulfill the condition

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Cardinality Restrictions• Meaning: The property must have at least/at

most/exactly x values• is the shortcut for and• Example: A FamilyDestination is a Destination

that has at least one Accomodation and at least 2 Activities

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allValuesFrom Restrictions

• Meaning: All values of the property must be of a certain type

• Warning: Also individuals with no values fulfill this condition (trivial satisfaction)

• Example: Hiking is a Sport that is only possible in NationalParks

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someValuesFrom Restrictions• Meaning: At least one value of the

property must be of a certain type

• Others may exist as well

• Example: A NationalPark is a RuralArea that has at least one Campground and offers at least one Hiking opportunity

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hasValue Restrictions• Meaning: At least one of the values of

the property is a certain value

• Similar to someValuesFrom but with Individuals and primitive values

• Example: A PartOfSydney is a Destination where one of the values of the isPartOf property is Sydney

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Enumerated Classes• Consist of exactly the listed individuals

OneStarRating

TwoStarRatingThreeStarRating

BudgetAccomodation

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Logical Class Definitions

• Define classes out of other classes– unionOf (or)– intersectionOf (and)– complementOf (not)

• Allow arbitrary nesting of class descriptions (A and (B or C) and not D)

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unionOf• The class of individuals that belong to

class A or class B (or both)

• Example: Adventure or Sports activities

Adventure Sports

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intersectionOf• The class of individuals that belong to

both class A and class B

• Example: A BudgetHotelDestination is a destination with accomodation that is a budget accomodation and a hotel

BudgetAccomodation

Hotel

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Implicit intersectionOf• When a class is defined by more than

one class description, then it consists of the intersection of the descriptions

• Example: A luxury hotel is a hotel that is also an accomodation with 3 stars

AccomodationWith3StarsHotel

LuxuryHotel

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complementOf• The class of all individuals that do not

belong to a certain class

• Example: A quiet destination is a destination that is not a family destination

DestinationFamilyDestination

QuietDestination (grayed)

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Class Conditions

• Necessary Conditions:(Primitive / partial classes)“If we know that something is a X,then it must fulfill the conditions...”

• Necessary & Sufficient Conditions:(Defined / complete classes)“If something fulfills the conditions...,then it is an X.”

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Class Conditions (2)

QuietDestination

NationalPark

(not everything that fulfills theseconditions is a NationalPark)

(everything that fulfills theseconditions is a QuietDestination)

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ClassificationNationalPark

BackpackersDestination

• A RuralArea is a Destination

• A Campground is BudgetAccomodation

• Hiking is a Sport• Therefore:

Every NationalPark is a Backpackers-Destiantion

(Other BackpackerDestinations)

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Classification (2)

• Input: Asserted class definitions

• Output: Inferred subclass relationships

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(Create an enumerated class out of individuals)

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(Create a hasValue restriction)

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(Create a hasValue restriction)

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(Create a defined class)

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(Classify Campground)

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(Add restrictions to City and Capital)

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(Create defined class BackpackersDestination)

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(Create defined class FamilyDestination)

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(Create defined class QuietDestination)

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(Create defined class RetireeDestination)

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(Classification)

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(Consistency Checking)

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Visualization with OWLViz

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OWL Wizards

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Putting it All Together

• Ontology has been developed

• Published on a dedicated web address

• Ontology provides standard terminology

• Other ontologies can extend it

• Users can instantiate the ontology to provide instances– specific hotels– specific activities

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Ontology Import

• Adds all classes, properties and individuals from an external OWL ontology into your project

• Allows to create individuals, subclasses, or to further restrict imported classes

• Can be used to instantiate an ontology for the Semantic Web

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Tourism Semantic Web (2)

OWLMetadata

(Individuals)Tourism Ontology

Web Services

Destination

AccomodationActivity

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Ontology Import with Protégé

• On the Metadata tab:– Add namespace, define prefix– Check “Imported” and reload your project

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Individuals

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Individuals

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OWL File<?xml version="1.0"?>\<rdf:RDF xmlns="http://protege.stanford.edu/plugins/owl/owl-library/heli-bunjee.owl#" xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#" xmlns:rdfs="http://www.w3.org/2000/01/rdf-schema#" xmlns:owl="http://www.w3.org/2002/07/owl#" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:travel="http://protege.stanford.edu/plugins/owl/owl-library/travel.owl#" xml:base="http://protege.stanford.edu/plugins/owl/owl-library/heli-bunjee.owl">

<owl:Ontology rdf:about=""> <owl:imports rdf:resource="http://protege.stanford.edu/plugins/owl/owl-library/travel.owl"/> </owl:Ontology>

<owl:Class rdf:ID="HeliBunjeeJumping"> <rdfs:subClassOf rdf:resource="http://protege.stanford.edu/plugins/owl/owl-library/travel.owl#BunjeeJumping"/> </owl:Class>

<HeliBunjeeJumping rdf:ID="ManicSuperBunjee"> <travel:isPossibleIn> <rdf:Description rdf:about="http://protege.stanford.edu/plugins/owl/owl-library/travel.owl#Sydney"> <travel:hasActivity rdf:resource="#ManicSuperBunjee"/> </rdf:Description> </travel:isPossibleIn> <travel:hasContact> <travel:Contact rdf:ID="MSBInc"> <travel:hasEmail rdf:datatype="http://www.w3.org/2001/XMLSchema#string">msb@manicsuperbunjee.com </travel:hasEmail> <travel:hasCity rdf:datatype="http://www.w3.org/2001/XMLSchema#string">Sydney</travel:hasCity> <travel:hasStreet rdf:datatype="http://www.w3.org/2001/XMLSchema#string">Queen Victoria St</travel:hasStreet> <travel:hasZipCode rdf:datatype="http://www.w3.org/2001/XMLSchema#int">1240</travel:hasZipCode> </travel:Contact> </travel:hasContact> <rdfs:comment rdf:datatype="http://www.w3.org/2001/XMLSchema#string">Manic super bunjee now offers nerve wrecking jumps from 300 feet right out of a helicopter. Satisfaction guaranteed.</rdfs:comment> </HeliBunjeeJumping>

</rdf:RDF>