Building Ontologies from the Ground Up When users set out to model their professional activity

1
Building Ontologies from the Ground Up When
users set out to model their professional activity

• Mark A. Musen
• Professor 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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Porphyrys depiction of Aristotles Categories
Supreme genus SUBSTANCE
Differentiae material immaterial
Subordinate genera BODY SPIRIT
Differentiae animate inanimate
Subordinate genera LIVING
MINERAL
Differentiae sensitive insensitive
Proximate genera ANIMAL PLANT
Differentiae rational irrational
Species HUMAN BEAST
Individuals Socrates Plato Aristotle

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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-understandab
  le 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 arent 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
  products 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 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!
• Its 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?
A wonderful keynote talk from the recent meeting
on Standards and Ontologies for Functional
Genomics

• Professor Carole Goble
• University of Manchester, UK
• Warning
• This talk contains sweeping generalisations

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Prologue
? Carole Goble

• Two households, both alike in dignity,
• In fair genomics, where we lay our scene,
• (One, comforted by its logics rigour,
• Claims ontology for the realm of pure,
• The other, with blessed scientists 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 foes
• Researchers to unlock the book of life
• Whole misadventured piteous overthrows
• Can 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
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The Montagues
? Carole Goble
One, comforted by its logics rigour, Claims
ontology for the realm of pure

• Computer Science, Knowledge engineering, AI
• Logic and Languages
• Theory
• Top down, well-behaved neatness
• Generic and lots of toys
• Methodologies patterns
• Tools and standards
• Technology push
• Academic pursuit

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The Capulets
? Carole Goble
The other, with blessed scientists vigour, Acts
hastily on models that endure

• Life Scientists
• Practice
• Bottom up, real-world
• Specific and many of them
• Methodologies, community practice
• Tools and standards
• Application pull
• Practical pursuit build n use it

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The Philosophers
? Carole Goble
One, comforted by its logics rigour, Claims
ontology for the realm of pure

• Philosophers
• Theory
• Truth
• Generic the one true ontology?
• Methodologies, patterns foundational ontologies
• Not really into tools
• No push or pull
• Academic pursuit

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? Carole Goble
Philosophers
Spiritual guides
Aesthetics
Life Scientists Capulets
KR Montagues
Theoreticians
Pragmatists
A means to an end Content providers
The end Mechanism providers
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The Princes of Genomics
? Carole Goble

• 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 rage
• With purple fountains issuing from your veins,
• On pain of torture, from those bloody hands
• Throw 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 citizens
• Cast by their grave beseeming ornaments,
• To wield old partisans, in hands as old,
• Canker'd with peace, to part your canker'd hate

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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
• Create integrative terminology
• Evolve terminology scope from supporting grants
  management to supporting science
• 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 Use
• nciterms.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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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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Protégés 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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Editing OWL Ontologieswith Protégé

• Holger Knublauch
• Stanford 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 Web

• Shared ontologies help to exchange data and
  meaning between web-based services

(Image by Jim Hendler)
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Wine Example Scenario
Tell me what wines I should buy to serve with
each course of the following menu.
Books Agent
Wine Agent
I recommend Chardonney or DryRiesling
Grocery Agent
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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 (DAMLOIL)
• A Web Language Based on RDF(S)
• An Ontology Language Based on logic

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OWL Ontologies

• Whats 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 customers expectations
  with potential destinations
• Required Web Service that exploits formal
  information about the available destinations
• Accomodation (Hotels, BB, 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
OWL Metadata (Individuals)
OWL Metadata (Individuals)
Tourism Ontology
Destination
Accomodation
Activity
OWL Metadata (Individuals)
OWL Metadata (Individuals)
Web Services
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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

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ObjectProperties

• Link two individuals together
• Relationships (0..n, n..m)

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Inverse Properties

• Represent bidirectional relationships
• Adding a value to one property also adds a value
  to the inverse property

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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

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DatatypeProperties

• Link individuals to primitive values(integers,
  floats, strings, booleans etc)
• Often AnnotationProperties without formal
  meaning

hasSize 4,500,000 isCapital true rdfscomment
Dont miss the opera house
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Classes

• Sets of individuals with common characteristics
• Individuals are instances of at least one class

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Range and Domain

• Property characteristics
• Domain left side of relation (Destination)
• Range right side (Accomodation)

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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 undefinedProperty 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

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Class Relationships

• Classes can overlap arbitrarily

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Class Disjointness

• All classes could potentially overlap
• In many cases we want to make sure they dont
  share instances

disjointWith
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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

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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 OWLs 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 checkingCan a class have any
  instances?
• ClassificationIs A a subclass of B?
• Instance classificationWhich 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

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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

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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

102
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

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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

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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)
(not everything that fulfills theseconditions is
a NationalPark)
(everything that fulfills theseconditions is a
QuietDestination)
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Classification

• A RuralArea is a Destination
• A Campground is BudgetAccomodation
• Hiking is a Sport
• ThereforeEvery 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)
109
(Create a hasValue restriction)
110
(Create a hasValue restriction)
111
(Create a defined class)
112
(Classify Campground)
113
(Add restrictions to City and Capital)
114
(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

124
Tourism Semantic Web (2)
OWL Metadata (Individuals)
Tourism Ontology
Destination
Accomodation
Activity
Web Services
125
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
lt?xml version"1.0"?gt\ ltrdfRDF
xmlns"http//protege.stanford.edu/plugins/owl/owl
-library/heli-bunjee.owl" xmlnsrdf"http//w
ww.w3.org/1999/02/22-rdf-syntax-ns"
xmlnsrdfs"http//www.w3.org/2000/01/rdf-schema"
xmlnsowl"http//www.w3.org/2002/07/owl"
xmlnsdc"http//purl.org/dc/elements/1.1/"
xmlnstravel"http//protege.stanford.edu/plugins/
owl/owl-library/travel.owl" xmlbase"http//pr
otege.stanford.edu/plugins/owl/owl-library/heli-bu
njee.owl"gt ltowlOntology rdfabout""gt
ltowlimports rdfresource"http//protege.stanford
.edu/plugins/owl/owl-library/travel.owl"/gt
lt/owlOntologygt ltowlClass rdfID"HeliBunjeeJu
mping"gt ltrdfssubClassOf rdfresource"http//
protege.stanford.edu/plugins/owl/owl-library/trave
l.owlBunjeeJumping"/gt lt/owlClassgt
ltHeliBunjeeJumping rdfID"ManicSuperBunjee"gt
lttravelisPossibleIngt ltrdfDescription
rdfabout"http//protege.stanford.edu/plugins/owl
/owl-library/travel.owlSydney"gt
lttravelhasActivity rdfresource"ManicSuperBunje
e"/gt lt/rdfDescriptiongt
lt/travelisPossibleIngt lttravelhasContactgt
lttravelContact rdfID"MSBInc"gt
lttravelhasEmail rdfdatatype"http//www.w3.org/2
001/XMLSchemastring"gtmsb_at_manicsuperbunjee.com
lt/travelhasEmailgt lttravelhasCity
rdfdatatype"http//www.w3.org/2001/XMLSchemastr
ing"gtSydneylt/travelhasCitygt
lttravelhasStreet rdfdatatype"http//www.w3.org/
2001/XMLSchemastring"gtQueen Victoria
Stlt/travelhasStreetgt lttravelhasZipCode
rdfdatatype"http//www.w3.org/2001/XMLSchemaint
"gt1240lt/travelhasZipCodegt
lt/travelContactgt lt/travelhasContactgt
ltrdfscomment rdfdatatype"http//www.w3.org/2001
/XMLSchemastring"gtManic super bunjee now offers
nerve wrecking jumps from 300 feet right
out of a helicopter. Satisfaction
guaranteed.lt/rdfscommentgt lt/HeliBunjeeJumpinggt
lt/rdfRDFgt