Ontology and Its Applications Barry Smith http://ontologist.com

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Ontology and Its ApplicationsBarry
Smithhttp//ontologist.com
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OVERVIEW

• Part I A Brief Overview of Developments in
  Ontology at the Borderlines of Philosophy and
  Computation
• Part II Ontology and Biomedical Informatics

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IFOMIS

• now part of
• European Centre for Ontological Research,
  Saarbrücken, Germany

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Institute for Formal Ontology and Medical
Information Science

• 16 staff
• 2 medical informaticians
• 1 neurologist
• 1 chemist
• 1 radiologist
• 2 computer scientists
• 9 philosophers

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The problem

• Different communities of researchers use
  different and often incompatible concepts /
  categories in expressing the results of their work

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Example Medicine

• blood is a tissue
• blood is a body fluid
• How to integrate competing conceptualizations?

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• Example Molecular Biology
• GDB
• Genome Database of Human Genome Project
• GenBank
• National Center for Biotechnology Information,
  Washington DC

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What is a gene?

• GDB a gene is a DNA fragment that can be
  transcribed and translated into a protein
• GenBank a gene is a DNA region of biological
  interest with a name and that carries a genetic
  trait or phenotype

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How to integrate competing conceptualizations

• for example across the granular divide between
  medicine and molecular biology?

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Answer

• ONTOLOGY!
• But what does ontology mean?

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Three senses of ontology

• Philosophical sense
• Aristotle an inventory of the types of entities
  and relations in reality
• Quine an inventory of ontological commitments
• Knowledge engineering sense an ontology as a
  consensus representation of the concepts used in
  a given domain
• Gene Ontology sense a controlled vocabulary for
  database annotation / indexing

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Two Communities

• Reference Ontology Community An ontology is an
  inventory of the types of entities and relations
  which exist in a given domain of reality
• KR Community an ontology is a consensus
  representation of the concepts used in a given
  domain of discourse

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Ontology as used in KR / AI

• had its roots in Quines doctrine of ontological
  commitment and in the internal metaphysics of
  Carnap/Putnam

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Quineanism

• ontology is the study of the ontological
  commitments or presuppositions embodied in
  scientific theories
• (or in the beliefs of those experts,
• or in the databases of that company)

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Quineanism, too, faces the integration problem

• If an ontology is the set of ontological
  commitments of a theory
• how can we cope with questions pertaining to the
  relations between the objects to which different
  theories are committed?
• Quine can tell us what there is
• but can he tell us how it is related together?

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The problem of the unity of science

• The logical positivist solution to this problem
  addressed a world in which sciences are
  identified with
• printed texts
• What if sciences are identified with
• information systems
• or with
• the contents of websites?

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The Semantic Web Initiative

• The Web is a vast edifice of heterogeneous data
  sources
• Needs the ability to query and integrate across
  different and often incompatible conceptual
  systems

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How resolve such incompatibilities and make the
various parts of the web interoperable?

• Enforce conceptual compatibility via
  standardized taxonomies applied to websites as
  meta-tags formulated within the framework of a
  common web language like OWL

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Tim Berners Lee

• hyperlinked vocabularies, called ontologies
  will be used by Web authors to explicitly define
  their words and concepts as they post their stuff
  online.
• codes would let software "agents" analyze the
  Web on our behalf, making smart inferences that
  go far beyond the simple linguistic analyses
  performed by today's search engines.

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A new silver bullet

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Metadata in Web commerce

• agree on a metadata standard for washing
  machines as concerns size, price, etc.
• create machine-readable databases and put them
  on the net
• ? consumers can query multiple sites
  simultaneously
• and search for highly specific, reliable,
  context-sensitive results

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Metadata in science

• agree on metadata standards for molecules
  (genes, proteins, drugs), clinical phenomena,
  therapies ...
• create machine-readable databases and put them
  on the net
• ? biomedical researchers can query multiple
  sites simultaneously
• and search for highly specific, reliable,
  context-sensitive results

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A world of exhaustive, reliable metadata

• would be utopia
• (Cary Doctorow)

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Problem 1 People lie

• Cheating in assigning meta-tags can confer
  benefits to the cheaters
• Metadata exists in a competitive world.
• Some people are crooks.
• Some people are cranks.

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Semantic Web effort

• thus far devoted primarily to developing systems
  for standardized representation of web pages and
  web processes
• ( ontology of web typography)
• not to the harder task of developing ontologies
• (reliable taxonomies, term hierarchies)
• for the content of such web pages

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Problem 2 People are lazy

• Half the pages on Geocities are called Please
  title this page

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Problem 3 People are stupid

• The vast majority of the Internet's users
• (even those who are native speakers of English)
• cannot spell or punctuate
• Will internet users learn to accurately tag
  their information with whatever taxonomy and
  syntax they're supposed to be using?

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even with correct XML-syntax

• ltBUSINESS-CARDgt  ltFIRSTNAMEgtJuleslt/FIRSTNAMEgt
   ltLASTNAMEgtDerycklt/LASTNAMEgt  ltCOMPANYgtNewcolt/CO
  MPANYgt  ltMEMBEROFgtXTC Grouplt/MEMBEROFgt
   ltJOBTITLEgtBusiness Managerlt/JOBTITLEgt
   ltTELgt32(0)3.471.99.60lt/TELgt  ltFAXgt32(0)3.891.
  99.65lt/FAXgt  ltGSMgt32(0)465.23.04.34lt/GSMgt
   ltWEBSITEgtwww.newco.comlt/WEBSITEgt  ltADDRESSgt  
  ltSTREETgtDendersesteenweg 17 lt/STREETgt  

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errors still abound
Is "Jules" the first name of the person, or of
the business-card?

• ltBUSINESS-CARDgt  ltFIRSTNAMEgtJuleslt/FIRSTNAMEgt
   ltLASTNAMEgtDerycklt/LASTNAMEgt  ltCOMPANYgtNewcolt/CO
  MPANYgt  ltMEMBEROFgtXTC Grouplt/MEMBEROFgt
   ltJOBTITLEgtBusiness Managerlt/JOBTITLEgt
   ltTELgt32(0)3.471.99.60lt/TELgt  ltFAXgt32(0)3.891.
  99.65lt/FAXgt  ltGSMgt32(0)465.23.04.34lt/GSMgt
   ltWEBSITEgtwww.newco.comlt/WEBSITEgt  ltADDRESSgt  
  ltSTREETgtDendersesteenweg 17lt/STREETgt  
  ltZIPgt2630lt/ZIPgt

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errors still abound
Is Jules or Newco the member of XTC Group?

• ltBUSINESS-CARDgt  ltFIRSTNAMEgtJuleslt/FIRSTNAMEgt
   ltLASTNAMEgtDerycklt/LASTNAMEgt  ltCOMPANYgtNewcolt/CO
  MPANYgt  ltMEMBEROFgtXTC Grouplt/MEMBEROFgt
   ltJOBTITLEgtBusiness Managerlt/JOBTITLEgt
   ltTELgt32(0)3.471.99.60lt/TELgt  ltFAXgt32(0)3.891.
  99.65lt/FAXgt  ltGSMgt32(0)465.23.04.34lt/GSMgt
   ltWEBSITEgtwww.newco.comlt/WEBSITEgt  ltADDRESSgt  
  ltSTREETgtDendersesteenweg 17lt/STREETgt  
  ltZIPgt2630lt/ZIPgt   ltCITYgtAartselaarlt/CITYgt  
  ltCOUNTRYgtBelgiumlt/COUNTRYgt  lt/ADDRESSgt
  lt/BUSINESS-CARDgt

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errors still abound

• ltBUSINESS-CARDgt  ltFIRSTNAMEgtJuleslt/FIRSTNAMEgt
   ltLASTNAMEgtDerycklt/LASTNAMEgt  ltCOMPANYgtNewcolt/CO
  MPANYgt  ltMEMBEROFgtXTC Grouplt/MEMBEROFgt
   ltJOBTITLEgtBusiness Managerlt/JOBTITLEgt
   ltTELgt32(0)3.471.99.60lt/TELgt  ltFAXgt32(0)3.891.
  99.65lt/FAXgt  ltGSMgt32(0)465.23.04.34lt/GSMgt
   ltWEBSITEgtwww.newco.comlt/WEBSITEgt  ltADDRESSgt  
  ltSTREETgtDendersesteenweg 17lt/STREETgt  
  ltZIPgt2630lt/ZIPgt   ltCITYgtAartselaarlt/CITYgt  
  ltCOUNTRYgtBelgiumlt/COUNTRYgt  lt/ADDRESSgt
  lt/BUSINESS-CARDgt

Do the phone numbers and address belong to Jules
or to the business?
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Problem 4 Building good ontologies/standardized
taxonomies is very difficult

• and the constraints imposed by OWL and similar
  languages make the job even harder

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Problem 5 Ontology Impedance

• semantic mismatch between ontologies
• gene used in websites issued by
• biotech companies involved in gene patenting
• medical researchers interested in role of genes
  in predisposition to smoking
• insurance companies

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Problem 6 The Concept Orientation

• Tom Gruber An ontology is a specification of a
  conceptualization
• Semantic Web specify Toms, and Dicks, and
  Harrys conceptualizations carefully,
• ensure that all are formulated in a common
  (XML-based) syntax
• Presto conceptualizations will somehow become
  integrated

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even a world of exhaustive, reliable metadata

• would not solve the problem of integration

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expressing different systems of concepts

• in a common syntactic environment does not
  resolve conceptual incompatibilities

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different conceptualizations
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need not interconnect at all
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we cannot make incompatible terminology-systems
interconnect
just by looking at concepts, or knowledge or
language
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to decide which of a plurality of competing
conceptualizations to accept
we need some tertium quid
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we need, in other words,
to take the world itself into account
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Compare the way biologists resolve disagreements
as to whether they mean the same thing by
different words

• by pointing to the objects in their lab

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The Semantic Web

• is a machine for creating syllogisms (Clay
  Shirky)
• Humans are mortalGreeks are humanTherefore,
  Greeks are mortal

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Lewis Carroll

• No interesting poems are unpopular among people
  of real taste No modern poetry is free from
  affectation All your poems are on the subject
  of soap-bubbles No affected poetry is popular
  among people of real taste No ancient poetry is
  on the subject of soap-bubbles
• Therefore All your poems are bad.

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the promise of the Semantic Web

• it will improve all the areas of your life where
  you currently use syllogisms

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Semantic Web

• compatibility problems should be solved
  automatically
• (by machine)
• Hence ontologies must be applications running in
  real time

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Semantic Web methodology

• Get syntax right first
• (Conceptualism weak expressive resource weak
  Description Logics to ensure computational
  tractability)
• and integration of concepts will take care of
  itself
• but only at the price of Procrustean
  simplification

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IFOMIS methodology

• Get ontology right first
• (use powerful logic to develop ontology as theory
  of reality
• and solve tractability problems later)
• only thus will we have some hope of genuine
  integration across different disciplines and data
  resources

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Belnap

• it is a good thing logicians were around before
  computer scientists
• if computer scientists had got there first,
  then we wouldnt have numbers
• because arithmetic is undecidable

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It is a good thing

• philosophical ontology was around before
  Description Logics, because otherwise
• we would have only hierarchies of concepts
  together with abstract mathematical models
• and no universals or instances in reality

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Recall

• GDB a gene is a DNA fragment that can be
  transcribed and translated into a protein
• Genbank a gene is a DNA region of biological
  interest with a name and that carries a genetic
  trait or phenotype

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Ontology

• fragment, region, name, carry, trait,
  type
• ... part, whole, function, inhere,
  substance
• are ontological terms in the sense of traditional
  (philosophical) ontology

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The idea of a reference ontology

• a theory of the kinds of entities existing in
  reality and of the relations between them

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The Reference Ontology Community

• IFOMIS (Saarbrücken)
• Laboratories for Applied Ontology (Trento/Rome,
  Turin)
• Ontology Works (Baltimore)
• Department of Biological Structure (Seattle)
• Medical Ontology Research (Bethesda)
• The Gene Ontology / Open Biological Ontologies
  Consortium

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IFOMISs long-term goal

• Build a robust high-level reference ontology
• THE WORLDS FIRST INDUSTRIAL-STRENGTH PHILOSOPHY
• as the basis for an ontologically coherent
  unification of biomedical knowledge and
  terminology

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Two upper-level ontologies reference

• BFO (Saarbrücken) Basic Formal Ontology
• DOLCE (Trento/Rome)

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Aristotle
First ontologist

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Edmund Husserl
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Formal Ontology

• term coined by Husserl
• the theory of those ontological structures
• such as part-whole, universal-particular
• which apply to all domains whatsoever

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Husserls Logical Investigations1900/01

• Aristotelian theory of universals and particulars
• theory of part and whole
• theory of ontological dependence
• the theory of boundaries and fusion

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Formal Ontology

• contrasted with material or regional ontologies
• (compare relation between pure and applied
  mathematics)
• Husserls idea
• If we can build a good formal ontology, this
  should save time and effort in building reference
  ontologies for each successive material domain

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In formal ontology

• as in formal logic, we can grasp the properties
  of given structures in such a way as to establish
  in one go the properties of all formally similar
  structures

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Compare

1. pure mathematics (theories of structures such as
   order, set, function, mapping) employed in every
   domain
2. applied mathematics, applications of these
   theories re-using the same definitions,
   theorems, proofs in new application domains
3. physical chemistry, biophysics, etc. adding
   detail

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Three levels of ontology
?????

• formal (top-level) ontology
• biomedical ontology has nothing like the
  technology of definitions, theorems and proofs
  provided by pure mathematics
• 2) domain ontology
• UMLS Semantic Network, GO, GALEN CORE
• 3) terminology-based ontology
• UMLS, SNOMED-CT, GALEN, FMA

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The Concept Orientation An ontology is a
consensus representation of concepts
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concept runs together

1. meaning shared in common by synonymous terms
2. idea shared in common in the minds of those who
   use these terms
3. universal, type, feature or property shared in
   common by entities in the world

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There are more word meanings than there are
universals / types of entities in reality

• unicorn
• devil
• canceled workshop
• prevented pregnancy
• imagined mammal
• fractured lip ...

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space of word meanings
space of universals
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space of word meanings
space of word meanings
space of word meanings
space of word meanings
space of universals
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space of word meanings
space of word meanings
space of word meanings
space of word meanings
space of universals
space of universals
space of universals
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if ontological relations are defined across the
whole space of word meanings

• rather than across the space of universals
  instantiated in reality
• then our tools for dealing with such relations
  are blunted

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meningitis is_a disease of the nervous system
is a statement about universals in reality
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A is_a B def. A is narrower in meaning
than B

• unicorn is_a one-horned mammal

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The linguistic reading of concept

• yields a smudgy view of reality, built out of
  relations like
• synonymous_with
• associated_to

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Goble Shadbolt
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The concept-based approach

• can provide some half-way coherent treatment of
  is_a relations

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but it cant cope at all with relations like

• part_of def. composes, with one or more other
  physical units, some larger whole
• contains def. is the receptacle for fluids or
  other substances

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connected_to def. Directly attached to another
physical unit as tendons are connected to
muscles.

• How can a meaning or concept be directly
  attached to another physical unit as tendons are
  connected to muscles ?

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An example of the concept orientation

• Unified Medical Language System (UMLS)

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• UMLS Metathesaurus
• 1 million biomedical concepts
• 2.8 million concept names
• from more than 100 controlled vocabularies and
  classifications
• built by US National Library of Medicine

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UMLS Source Vocabularies

• MeSH Medical Subject Headings
• ICD International Classification of Diseases
• GO Gene Ontology
• FMA Foundational Model of Anatomy

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To reap the benefits of standardization

• we need to make ONE SYSTEM out of many different
  terminologies
• UMLS Semantic Network
• nearest thing to an ontology in the UMLS

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UMLS SN

• described by its authors as An Upper Level
  Ontology for the Biomedical Domain
• (Compare the Semantic Web initiative)

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UMLS SN

• 134 Semantic Types
• 54 types of edges (relations)
• yielding a graph containing more than 6,000 edges

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Fragment of UMLS SN
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UMLS SN Top Level

• entity event
• physical conceptual
• object entity
• organism

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conceptual entity

• Organism Attribute
• Finding
• Idea or Concept
• Occupation or Discipline
• Organization
• Group
• Group Attribute
• Intellectual Product
• Language

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• 
  conceptual
• entity
• idea or concept
• functional concept
• body system

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• entity
• physical conceptual
• object entity
• idea or concept
• functional concept
• body system

confusion of entity and concept
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Functional Concept

• Body system is_a Functional Concept.
• but
• Concepts do not perform functions or have
  physical parts.

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This
is not a concept
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Confusion of Ontology and Epistemology

• Physical Object
• Substance
• Food Chemical Body Substance

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Confusion of Ontology and Epistemology

• Chemical
• Chemical Chemical
• Viewed Viewed
• Structurally Functionally

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• Chemical
• Chemical Chemical
• Viewed Viewed
• Structurally Functionally
• Inorganic Organic Enzyme
  Biomedical or
• Chemical Chemical Dental
  Material

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• Chemical
• Chemical Chemical
• Viewed Viewed
• Structurally Functionally
• Inorganic Organic
  Biomedical or
• Chemical Chemical Dental
  Material

Enzyme
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The Hydraulic Equation

• BP COPVR
• arterial blood pressure is directly proportional
  to the product of blood flow (cardiac output, CO)
  and peripheral vascular resistance (PVR)

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Confusion of Ontology and Epistemology

• blood pressure is an Organism Function,
• cardiac output is a Laboratory or Test Result or
  Diagnostic Procedure
• BP COPVR thus asserts that
• blood pressure is proportional either to a
  laboratory or test result or to a diagnostic
  procedure

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Fragment of UMLS SN
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UMLS Semantic Network

• anatomical abnormality associated_with daily or
  recreational activity
• educational activity associated with pathologic
  function
• bacterium causes experimental model of disease

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GO the Gene Ontology

• 3 large telephone directories of standardized
  designations for gene functions and products
• organized into hierarchies via is_a and part_of

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When a gene is identified

• three important types of questions need to be
  addressed
• 1. Where is it located in the cell?
• 2. What functions does it have on the molecular
  level?
• 3. To what biological processes do these
  functions contribute?

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GOs three ontologies
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GO is three ontologies

• cellular components
• molecular functions
• biological processes
• December 16, 2003
• 1372 component terms
• 7271 function terms
• 8069 process terms

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The Cellular Component Ontology (counterpart of
anatomy)

• flagellum
• chromosome
• membrane
• cell wall
• nucleus

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The Molecular Function Ontology

• ice nucleation
• protein stabilization
• kinase activity
• binding
• The Molecular Function ontology is (roughly) an
  ontology of actions on the molecular level of
  granularity

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Biological Process Ontology

• Examples
• glycolysis
• death
• adult walking behavior
• response to blue light
• occurrents on the level of granularity of
  cells, organs and whole organisms

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Each of GOs ontologies

• is organized in a graph-theoretical structure
  involving two sorts of links or edges
• is-a ( is a subtype of )
• (copulation is-a biological process)
• part-of
• (cell wall part-of cell)

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GO is species-independent

• an ontology of the unchanging universal building
  blocks of life
• (substances and processes)
• and of the structures they form

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The Gene Ontology

• error prone
• in part because of its sloppy treatment of
  relations
• menopause part_of death

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Primary aim of GO

• not rigorous definition and principled
  classification
• but rather providing a practically useful
  framework for keeping track of the biological
  annotations that are applied to gene products

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Problems with GO Molecular Functions

• anti-coagulant activity (defined as a
  substance that retards or prevents coagulation)
• enzyme activity (defined as a substance that
  catalyzes)
• structural molecule (defined as the action of
  a molecule that contributes to structural
  integrity)

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GO0005199 structural constituent of cell wall

• Definition The action of a molecule that
  contributes to the structural integrity of a cell
  wall.
• confuses actions, which GO includes in its
  function ontology, with constituents, which GO
  includes in its cellular component ontology

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cars

• red cars Cadillacs cars with
  radios

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Why do these problems arise?

• Because GO has no clear formal understanding of
  the role of relations in organizing an ontology
• (thus also no clear understanding of the
  difference between a function and the activity
  which is the realization of a function GO runs
  these two together)

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Thesis

• GO can realize its goal more adequately (and
  avoid many coding errors) by taking ontology
  (especially the logic of classifications and
  definitions) seriously

127
Digital Anatomist

• Foundational Model of Anatomy(Department of
  Biological Structure, University of Washington,
  Seattle)

The first crack in the wall of the Concept
Orientation
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Anatomical Space
Anatomical Structure
is_a
Organ Cavity Subdivision
Organ Cavity
Organ
Serous Sac
Organ Component
Serous Sac Cavity
Tissue
Serous Sac Cavity Subdivision
Pleural Sac
Pleura(Wall of Sac)
Pleural Cavity
part_of
Parietal Pleura
Visceral Pleura
Interlobar recess
Mediastinal Pleura
Mesothelium of Pleura
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part_of
Reference Ontology for Anatomy at every level
of granularity
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The Gene Ontology
The second crack in the wall

• European Bioinformatics Institute, ...
• Open source
• Transgranular
• Cross-Species
• Components, Processes, Functions

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But

• No logical structure
• Viciously circular definitions
• Poor rules for coding, definitions, treatment of
  relations, classifications
• so highly error-prone

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New GO / OBO Reform Effort

• OBO Open Biological Ontologies

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OBO Library

• Gene Ontology
• MGED Ontology
• Cell Ontology
• Disease Ontology
• Sequence Ontology
• Fungal Ontology
• Plant Ontology
• Mouse Anatomy Ontology
• Mouse Development Ontology
• ...

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coupled with

• Relations Ontology (IFOMIS)
• suite of relations for biomedical ontology to be
  submitted to CEN as basis for standardization of
  biomedical ontologies
• alignment of FMA and GALEN

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