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Ontology Tutorial Buffalo Ontology Site

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					Ontology Tutorial Part 1
   What is Ontology
 and What Can It Do?

       Barry Smith
   http://ontology.buffalo.edu/smith




                                       1
The problem of data integration /
       information fusion
   About 30,000 genes in a human
   Probably 100-200,000 proteins
   Individual variation in most genes
   100s of cell types
   100,000s of disease types




                                        2
                            Musculo-skeletal system
                            Circulatory system
                            Respiratory system
Organism                    Digestive system
                            Nervous system
                            Urinary system
           Organ            Reproductive system
                            Endocrine system
                            Lymphoidal system         Muscle tissue
                                                      Nerve tissue
                   Tissue                             Connective tissue
                                                      Epithelial tissue
                                                      Blood


                                   Cell
                                                                  Mitochondria
                                                                  Nucleus
                                                  Organelle       Endoplasmic
                                                                  reticulum
                                                                  Cell membrane

                                                                      Protein


                                                                                  DNA




                                                                                  3
         The Challenge
Each (clinical, pathological, genetic,
proteomic, pharmacological …) information
system uses its own terminology and
category system
biomedical research demands the ability to
navigate through all such information
systems
How can we overcome the incompatibilities
which become apparent when data from
distinct sources is combined?
                                        4
  Answer:

“Ontology”



             5
     Three senses of ontology
1. Philosophical sense: an inventory of the
   types of entities and relations in reality
2. Knowledge engineering sense: an
   ontology as a consensus representation
   of the concepts used in a given domain
   (Semantic Web)
3. Ontology as controlled vocabulary
   (Gene Ontology, Open Biological
   Ontologies Consortium)
                                                6
     Three senses of ontology
1. Philosophical sense: an inventory of the
   types of entities and relations in reality
2. Knowledge engineering sense: an ontology as
   a consensus representation of the concepts
   used in a given domain
   (Semantic Web)
3. Ontology as controlled vocabulary
   (Gene Ontology, Open Biological Ontologies
   Consortium)

                                                 7
   Ontology as a branch of
         philosophy
seeks to establish
the basic formal-ontological structures
the kinds and structures of objects,
properties, events, processes and
relations in each material domain of
reality


                                          8
Formal ontology an analogue of
      pure mathematics
 Can be applied to different domains




                                       9
Material ontology a kind of
generalized chemistry or zoology
(Aristotle’s ontology grew out of
biological classification)




                                    10
         Aristotle




world’s first ontologist
                           11
               World„s first ontology
(from Porphyry‟s Commentary on Aristotle‟s Categories)




                                                         12
Linnaean Ontology




                    13
          Formal Ontology
– theory of part and whole
– theory of dependence / unity
– theory of boundary, continuity and contact
– theory of universals and instances
– theory of continuants and occurrents (objects
  and processes)
– theory of functions and functioning
– theory of granularity

                                                  14
          Formal Ontology

the theory of those ontological structures
(such as part-whole, universal-particular)
which apply to all domains whatsoever




                                             15
Formal-Ontological Categories
   substance
   process
   function
   unity
   plurality
   site
   dependent part
   independent part

are able to form complex structures in non-
arbitrary ways joined by relations such as part,
dependence, location.
                                                   16
A Network of Domain
    Ontologies


Basic Formal Ontology




Material (Regional) Ontologies

                                 17
18
     Three senses of ontology
1. Philosophical sense: an inventory of the types
   of entities and relations in reality
2. Knowledge engineering sense: an ontology
   as a consensus representation of the
   concepts used in a given domain
   (Semantic Web)
3. Ontology as controlled vocabulary
   (Gene Ontology, Open Biological Ontologies
   Consortium)

                                                19
            Assumptions
Communication / compatibility problems
  should be solved automatically
(by machine)
Hence ontologies must be applications
  running in real time




                                         20
      Application ontology:

Ontologies are inside the computer
thus subject to severe constraints on
expressive power
(effectively the expressive power of
Description Logic)



                                        21
  Problem: Confusion of concepts
       and entities in reality
Don‟t construct theories of reality; construct
 „models‟ of „concepts‟


                                                 22
Ontology in the Knowledge Engineering
Sense


  The Semantic Web




                                        23
A new silver bullet




                      24
       The Semantic Web
designed to integrate the vast amounts of
heterogeneous online data and services
via dramatically better support at the level
of metadata designed to yield the ability to
query and integrate across different
conceptual systems



                                          25
Tim Berners-Lee, inventor of the
           internet
„sees a more powerful Web emerging, one
where documents and data will be
annotated with special codes allowing
computers to search and analyze the Web
automatically. The codes … are designed
to add meaning to the global network in
ways that make sense to computers‟



                                      26
hyperlinked vocabularies, called
„ontologies‟ will be used by Web authors
„to explicitly define their words and
concepts as they post their stuff online.
„The idea is the 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.‟


                                            27
     Exploiting tools such as:
 XML
 OWL (Ontology Web Language)
 RDF (Resource Descriptor Framework)
 DAML-OIL (Darpa Agent Mark-Up
 Language – Ontology Inference Layer)

(confusing syntactic integration with
  semantic integration)
                                        28
Ontology confused with: the language of ontology

„Ontology‟ for semantic webbers is without content

Philosophical ontology = build a theory of reality
Semantic-web-style ontology = build a model of
  the data in our computers



                                                     29
           Defining „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




                                         30
Example: The Enterprise Ontology
A Sale is an agreement between two Legal-
  Entities for the exchange of a Product for a Sale-
  Price.

A Strategy is a Plan to Achieve a high-level
  Purpose.

A Market is all Sales and Potential Sales within a
  scope of interest.


                                                     31
Example: Statements of Accounts

Company Financial statements may be
prepared under either the (US) GAAP or
the (European) IASC standards
These allocate cost items to different
categories depending on the laws of the
countries involved.


                                          32
                   Job:

to develop an algorithm for the automatic
conversion of income statements and balance
sheets between the two systems.
Not even this relatively simple problem has been
satisfactorily resolved
                            … why not?

Because the very same terms mean different
things
and are applied in different ways
in different cultures
                                               33
 The Semantic Web Initiative
The Web is a vast edifice of
heterogeneous data sources
Needs the ability to query and integrate
across different conceptual systems




                                           34
     How resolve incompatibilities?

enforce terminological compatibility via
standardized term hierarchies, with
standardized definitions of terms, which
1. satisfy the constraints of a description logic
(DL)
2. are applied as meta-tags to the content of
websites

                                              35
             Clay Shirky
The Semantic Web is a machine for creating
 syllogisms.

 Humans are mortal
 Greeks are human
 Therefore, Greeks are mortal



                                         36
            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.
                                              37
 the promise of the Semantic Web
it will improve all the areas of your life where
   you currently use syllogisms




                                               38
 We can use the Semantic Web
  to prove that Joe loves Mary
we found two documents on a trusted site, one of which
said that ":Joe :loves :MJS", and another of which said
that ":MJS daml:equivalentTo :Mary". We also got the
checksums of the files in person from the maintainer of
the site.
To check this information, we can list the checksums in a
local file, and then set up some FOPL rules that say "if
file 'a' contains the information Joe loves mary and has
the checksum md5:0qrhf8q3hfh, then record SuccessA",
"if file 'b' contains the information MJS is equivalent to
Mary, and has the checksum md5:0892t925h, then
record SuccessB", and "if SuccessA and SuccessB, then
Joe loves Mary". [http://infomesh.net/2001/swintro/]

                                                          39
        Merging Databases
Merging databases simply becomes a matter of
recording in RDF somewhere that "Person
Name" in your database is equivalent to "Name"
in my database, and then throwing all of the
information together and getting a processor to
think about it. [http://infomesh.net/2001/swintro/]

Is your "Person Name = John Smith" the same
person as my "Name = John Q. Smith"? Who
knows? Not the Semantic Web

                                                  40
     XML-syntax does not help
<BUSINESS-CARD>
   <FIRSTNAME>Jules</FIRSTNAME>
   <LASTNAME>Deryck</LASTNAME>
   <COMPANY>Newco</COMPANY>
   <MEMBEROF>XTC Group</MEMBEROF>
   <JOBTITLE>Business Manager</JOBTITLE>
   <TEL>+32(0)3.471.99.60</TEL>
   <FAX>+32(0)3.891.99.65</FAX>
   <GSM>+32(0)465.23.04.34</GSM>
   <WEBSITE>www.newco.com</WEBSITE>
   <ADDRESS>
   <STREET>Dendersesteenweg 17</STREET>
   <ZIP>2630</ZIP>
   <CITY>Aartselaar</CITY>
   <COUNTRY>Belgium</COUNTRY>
   </ADDRESS>
  </BUSINESS-CARD>

                                           41
 and with correct XML-syntax:
<BUSINESS-CARD>
  <FIRSTNAME>Jules</FIRSTNAME>
  <LASTNAME>Deryck</LASTNAME>
  <COMPANY>Newco</COMPANY>
  <MEMBEROF>XTC Group</MEMBEROF>
  <JOBTITLE>Business
 Manager</JOBTITLE>
  <TEL>+32(0)3.471.99.60</TEL>
  <FAX>+32(0)3.891.99.65</FAX>
  <GSM>+32(0)465.23.04.34</GSM>
  <WEBSITE>www.newco.com</WEBSITE>
  <ADDRESS>
  <STREET>Dendersesteenweg 17   42
 </STREET>
   and with correct XML-syntax:
<BUSINESS-CARD>                          Is "Jules" the
   <FIRSTNAME>Jules</FIRSTNAME>          first name of the
   <LASTNAME>Deryck</LASTNAME>           person, or of the
   <COMPANY>Newco</COMPANY>
   <MEMBEROF>XTC Group</MEMBEROF> business-card?
   <JOBTITLE>Business Manager</JOBTITLE>
   <TEL>+32(0)3.471.99.60</TEL>
   <FAX>+32(0)3.891.99.65</FAX>
   <GSM>+32(0)465.23.04.34</GSM>
   <WEBSITE>www.newco.com</WEBSITE>
   <ADDRESS>
   <STREET>Dendersesteenweg 17</STREET>
   <ZIP>2630</ZIP>
   <CITY>Aartselaar</CITY>
   <COUNTRY>Belgium</COUNTRY>
   </ADDRESS>
  </BUSINESS-CARD>

                                                        43
  and with correct XML-syntax:
<BUSINESS-CARD>                          Is Jules or
   <FIRSTNAME>Jules</FIRSTNAME>          Newco the
   <LASTNAME>Deryck</LASTNAME>           member of XTC
   <COMPANY>Newco</COMPANY>
   <MEMBEROF>XTC Group</MEMBEROF> Group?
   <JOBTITLE>Business Manager</JOBTITLE>
   <TEL>+32(0)3.471.99.60</TEL>
   <FAX>+32(0)3.891.99.65</FAX>
   <GSM>+32(0)465.23.04.34</GSM>
   <WEBSITE>www.newco.com</WEBSITE>
   <ADDRESS>
   <STREET>Dendersesteenweg 17</STREET>
   <ZIP>2630</ZIP>
   <CITY>Aartselaar</CITY>
   <COUNTRY>Belgium</COUNTRY>
   </ADDRESS>
  </BUSINESS-CARD>

                                                     44
  and with correct XML-syntax:
<BUSINESS-CARD>
   <FIRSTNAME>Jules</FIRSTNAME>
   <LASTNAME>Deryck</LASTNAME>
   <COMPANY>Newco</COMPANY>
   <MEMBEROF>XTC Group</MEMBEROF> Do the phone
   <JOBTITLE>Business Manager</JOBTITLE>
   <TEL>+32(0)3.471.99.60</TEL>          numbers and
   <FAX>+32(0)3.891.99.65</FAX>          address belong
   <GSM>+32(0)465.23.04.34</GSM>
   <WEBSITE>www.newco.com</WEBSITE> to Jules or to the
   <ADDRESS>                             business?
   <STREET>Dendersesteenweg 17</STREET>
   <ZIP>2630</ZIP>
   <CITY>Aartselaar</CITY>
   <COUNTRY>Belgium</COUNTRY>
   </ADDRESS>
  </BUSINESS-CARD>

                                                     45
                Shirkey:
The Semantic Web's philosophical
argument -- the world should make more
sense than it does -- is hard to argue with.
The Semantic Web, with its neat
ontologies and its syllogistic logic, is a nice
vision. However, like many visions that
project future benefits but ignore present
costs, it requires too much coordination
and too much energy to be effective in the
real world …
                                             46
        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 of
  ontologies (term hierarchies) for the
  content of such web pages


                                           47
       Cory Doctorow

A world of exhaustive, reliable
metadata would be a utopia.




                                  48
     Problem 1: People lie
Meta-utopia is a world of reliable
metadata.
But poisoning the well can confer benefits
to the poisoners

Metadata exists in a competitive world.
Some people are crooks.
Some people are cranks.
Some people are French philosophers.
                                             49
 Problem 2: People are lazy
Half the pages on Geocities are called
“Please title this page”




                                         50
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 DL-
hierarchy they're supposed to be using?


                                              51
  Problem 4: Ontology Impedance

= semantic mismatch between ontologies
  being merged
This problem recognized in Semantic Web
  literature:
http://ontoweb.aifb.uni-karlsruhe.de
/About/Deliverables/ontoweb-del-7.6-swws1.pdf



                                                52
               Solution 1:
         treat it as (inevitable)
              „impedance‟
and learn to find ways to cope with the
  disturbance which it brings

Suggested here:
http://ontoweb.aifb.uni-karls-ruhe.de/Ab-
  out/Deliverables/ontoweb-del-7.6-swws1.pdf


                                               53
  Solution 2: resolve the impedance
  problem on a case-by-case basis

  Suppose two databases are put on the
  web.
  Someone notices that "where" in the
  friends table and "zip" in the places table
  mean the same thing.

http://www.w3.org/DesignIssues/Semantic.html
                                                54
          Both solutions fail
1. treating mismatches as „impedance‟
   ignores the problem of error propagation
   (and is inappropriate in an area like
   medicine)
2. resolving impedance on a case-by-case
   basis defeats the very purpose of the
   Semantic Web


                                          55
         Ontology Impedance


„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

                                              56
                The idea:
distinguish two separate tasks:
- developing an expressively rich correct
  ontologies of given domains
- developing on this basis computer
  applications capable of running in real time




                                            57
Basic Formal Ontology


     BFO
   The Vampire Slayer




                        58
59
                  BFO
ontology not the „standardization‟ or
„specification‟ of concepts
(not a branch of knowledge or concept
engineering)
but an inventory of the types of entities
existing in reality



                                            60
 BFO not a computer application

        but a reference ontology



in the sense of Aristotelian philosophy
- it sacrifices tractability for the sake of
              expressive power

                                           61
           Defining „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




                                         62
                  Ontology
„fragment‟, „region‟, „name‟, „carry‟, „trait‟,
   „type‟
    ... „part‟, „whole‟, „function‟, „inhere‟,
   „substance‟ …
are ontological terms in the sense of
   traditional (philosophical) ontology



                                                  63
                    BFO
not just a system of categories
but a formal theory
with definitions, axioms, theorems
designed to provide formal resources for the
  building of reference ontologies for specific
  domains
the latter should be of sufficient richness that
  terminological incompatibilities can be
  resolved intelligently rather than by brute
  force
                                              64
       The Reference Ontology
            Community
IFOMIS (Saarbrücken)
Laboratories for Applied Ontology (Trento/Rome,
  Turin)
Foundational Ontology Project (Leeds)
Ontology Works (Baltimore
Department of Structural Biology (Seattle)
Virtual Soldier Project (DARPA)
Open Biological Ontologies Consortium
  (Cambridge, Berkeley, Bar Harbor)
                                                  65
66
 Ontology Tutorial Part 2
The Future of Ontology in
      Biomedicine




                            67
Ontology Tutorial Part 2:
The Future of Ontology in
        Buffalo




                            68
 Ontology Tutorial Part 2
The Future of Ontology in
      Biomedicine




                            69
     Three senses of ontology
1. Philosophical sense: an inventory of the
   types of entities and relations in reality
2. Knowledge engineering sense: an ontology as
   a consensus representation of the concepts
   used in a given domain
   (Semantic Web)
3. Ontology as controlled vocabulary
   (Gene Ontology, Open Biological Ontologies
   Consortium)

                                             70
     Philosophical Ontology
 Ontologies are WINDOWS ON REALITY
           Ontologies deal with
   classes/universals/invariants in reality
which exist independently of our theorizing
   and independently of our language




                                          71
   What are universals?
        invariants in reality




      satisfying biological laws
(there are truths about universals in
         biological textbooks)
                                        72
A universal is not determined by its
  instances as a state is not determined by
  its citizens

A universal may vary with time as an
  organism may vary with time (by gaining
  and losing molecules)


                                              73
  Universals are Not Sets

A set is an abstract structure,
existing outside time and space.
The set of Romans timelessly has
Julius Caesar as a member.
Universals exist in time.



                                   74
A Window on Reality




                      75
Medical Diagnostic Hierarchy




                                        76
        a hierarchy in the realm of diseases
  Dependence Relations




                           77
Organisms       Diseases
   A Window on Reality




                           78
Organisms       Diseases
A Window on Reality




                      79
universals                           substance

                              organism

                         animal

                mammal

          cat
                                         frog
siamese



instances
                                                 80
81
Many current standard „ontologies‟
ramshackle because they have no
  counterpart of formal ontology
The Universal Medical Language System (UMLS)
a compendium of source vocabularies including:
  HL7 RIM
  SNOMED
  International Classification of Diseases
  MeSH – Medical Subject Headings
  Gene Ontology
                                                 82
     Three senses of ontology
1. Philosophical sense: an inventory of the
   types of entities and relations in reality
2. Knowledge engineering sense: an
   ontology as a consensus representation
   of the concepts used in a given domain
   (Semantic Web)
3. Ontology as controlled vocabulary
   (Gene Ontology, Open Biological
   Ontologies Consortium)
                                                83
  Problem: The different source
vocabularies are incompatible with
           each other




                                 84
Problem: They contain bad coding
which often derives from failure to pay
attention to simple logical or ontological
principles or from principles of good
definitions




                                             85
         Bad Coding
Plant roots is-a Plant
Plant leaves is-a Plant
Pollen is-a Plant
Both testes is a testis
Both uterii is a uterus




                          86
            Bad definitions
Heptolysis =def the cause of heptolysis

Biological process =def a biological goal that
  requires more than one function




                                                 87
   The Concept Orientation
Work on biomedical ontologies grew out
 of work on medical dictionaries and
 nomenclatures
Has focused almost exclusively on
 „concepts‟ conceived (sometimes
 confused with terms/descriptions).




                                         88
    The Curse of Linguistics
Work on biomedical ontologies grew out
 of work on medical dictionaries and
 nomenclatures
This led to the assumption that all that
 need be said about classes can be said
 without appeal to time or to instances in
 reality.
Ontology is about meanings/terms/strings

                                             89
An alternative research programme
            for ontology
 based on philosophical principles
 Terms in bio-ontologies refer not
 to „concepts‟
 but to universals in reality



                                     90
       already reformed
Foundational Model of Anatomy
Anatomy Reference Ontology




                                91
                         Anatomical Entity

     Physical                                      Conceptual
  Anatomical Entity                -is a-        Anatomical Entity

                                                        Anatomical
                                                        Relationship

   Material Physical                        Non-material Physical
   Anatomical Entity                          Anatomical Entity

    Body                                                     Anatomical
                               Anatomical
  Substance                                                    Space
                                Structure


 Biological
                            Cell                Organ
Macromolecule

        Cell                       Organ     Organ          Body       Human
                Tissue
        Part                        Part     System         Part        Body

                                                                               92
                         Anatomical Entity

     Physical                                      Conceptual
  Anatomical Entity                -is a-        Anatomical Entity

                                                        Anatomical
                                                        Relationship

   Material Physical                        Non-material Physical
   Anatomical Entity                          Anatomical Entity

    Body                                                     Anatomical
                               Anatomical
  Substance                                                    Space
                                Structure


 Biological
                            Cell                Organ
Macromolecule

        Cell                       Organ     Organ          Body       Human
                Tissue
        Part                        Part     System         Part        Body


                A window on reality                                            93
                                                        Anatomical
        Anatomical Space
                                                         Structure


Organ Cavity          Organ
                                          Organ                         Organ Part
 Subdivision          Cavity


 Serous Sac          Serous Sac                          Organ            Organ
   Cavity              Cavity
                                       Serous Sac      Component        Subdivision
                                                                                      Tissue
 Subdivision




                                                Pleural Sac             Pleura(Wall
                        Pleural                                            of Sac)
                         Cavity
                                          Parietal
                                           Pleura                    Visceral
               Interlobar                                            Pleura
                 recess           Mediastinal
                                   Pleura              Mesothelium
                                                        of Pleura
                                                                                         94
To represent ontological relations we
 need to take instances into account
To say A part_of B is not to say
 anything about Bs‟ need for As as
 parts




                                     95
part_of as a relation between universals
  A part_of B =def
    given any x, if inst(x, A) then there is
    some y such that inst(y, B) and
    part(x, y)

    human testis part_of human being,
       But not:
    heart part_of human being.

                                           96
       already reformed
Foundational Model of Anatomy
Anatomy Reference Ontology




                                97
under construction / overhaul
 Physiology Reference Ontology
 Gene Ontology
 OBOL




                                 98
     The Gene Ontology
a controlled vocabulary for
annotations of genes and gene
products




                                99
  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?

                                         100
  GO has three ontologies

molecular                biological
functions                processes




              cellular
            components




                                      101
   GO astonishingly influential
used by all major species genome projects
used by all major pharmacological research
  groups
used by all major bioinformatics research
  groups




                                         102
  GO part of the Open Biological
     Ontologies consortium
Fungal Ontology    Mouse Anatomy
Plant Ontology     Ontology
Yeast Ontology     Cell Ontology
Disease Ontology   Sequence Ontology
                   Relations Ontology




                                        103
      Each of GO‟s 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)

                                              104
105
106
cellular components
molecular functions
biological processes

1372 component terms
7271 function terms
8069 process terms




                       107
    The Cellular Component
Ontology (counterpart of anatomy)

         flagellum
         chromosome
         membrane
         cell wall
         nucleus


                               108
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
                                          109
 Biological Process Ontology
              glycolysis
              copulation
              death
An ontology of occurrents on the level of
granularity of cells, organs and whole
organisms



                                            110
     GO built by biologists

free of the Curse of Linguistics
 free of the Curse of Computer
              Science




                                   111
    but problems still remain
menopause part_of aging
aging part_of death

menopause part_of death




                                112
             heptolysis

Definition
The causes of heptolysis …




                             113
regulation of sleep part_of sleep
extrinsic to membrane part_of membrane




                                         114
GO uses only two relations
       is_a and part_of




                             115
 hence GO has only sentences of
the forms A is_a B and A part_of B
 no way to express „not‟ and no way
 to express „is localized at‟ and no
 way to express „I don‟t know‟:




                                       116
 Holliday junction helicase complex
 is-a
 unlocalized

cellular component unknown is-a
 cellular component




                                      117
Old GO definition of part_of
 A part_of B =def A can be part of B




                                       118
  New GO definition of part_of as
 part of current OBOL reform effort
A part_of B =def


 given any x, if inst(x, A) then there is
 some y such that inst(y, B) and
 part(x, y)



                                        119
Analogous problems for nearly all foundational
relations of ontologies and semantic networks:


A causes B
A is associated with B
A is located in B
etc.

Reference to instances is necessary to
clear up these problems
                                                 120
121
 The Future of Ontology in Buffalo
      http://ontology.buffalo.edu/bcor/

to provide a forum within which philosophical
   ontologists and those involved in ontology
     applications can work together in high-
         level interdisciplinary research
  to assist in coordination and integration of
      projects in ontological research being
                pursued in Buffalo
                                            122
Gary Byrd         James Llinas
Charles Dement    David Mark
Randall Dipert    Bill Rapaport
John Eisner       Galina Rogova
Daniel Fischer    Ram Ramesh
Louis Goldberg    Stuart C. Shapiro
Jorge Gracia      Barry Smith
David Hershenov   Rohini Srihari
Rajiv Kishore     Moises Sudit
Eric Little


                                      123
College of Arts and Sciences
Computer Science and Engineering
School of Management
Center of Excellence in Bioinformatics
School of Informatics
School of Dental Medicine
Center for Multisource Information Fusion
National Center for Geographic Information
  and Analysis
School of Medicine and Biomedical Sciences


                                             124
Computer Science and Engineering
    School of Management

          Charles Dement
        Pharma of the Future




                               125
Computer Science and
    Engineering

    Daniel Fischer
    Bill Rapaport
    Stuart Shapiro
    Rohini Srihari



                       126
School of Management
     Ram Ramesh
     Rajiv Kishore




                       127
Center of Excellence in
   Bioinformatics
     Daniel Fischer




                          128
School of Informatics / School of
            Medicine

              Gary Byrd
Medical Informatics Certificate Program




                                      129
School of Dental Medicine

       John Eisner
      Louis Goldberg

        SNODENT




                            130
Center for Multisource
 Information Fusion

       Eric Little
     James Llinas
     Galina Rogova
      Moises Sudit




                         131
National Center for Geographic
   Information and Analysis


           David Mark
           Barry Smith




                             132
Department of Philosophy
    Barry Smith (Director?)
        Randall Dipert
         Jorge Gracia
       David Hershenov
      Ingvar Johansson
          Jiyuan Yu


                              133
                 Goal
To show how philosophical ontology can
contribute to the successful application of
ontologies in information systems




                                          134

				
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