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
Digestive system
Nervous system
Urinary system
Reproductive system
Endocrine system
Lymphoidal system
Organism
Organ
Tissue
Muscle tissue
Nerve tissue
Connective tissue
Epithelial tissue
Blood
Cell
Organelle
Mitochondria
Nucleus
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 nonarbitrary 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 soapbubbles
- No affected poetry is popular among people of
real taste
- No ancient poetry is on the subject of soapbubbles
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:
Is "Jules" the
<BUSINESS-CARD>
<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:
Is Jules or
<BUSINESS-CARD>
<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>
numbers and
<TEL>+32(0)3.471.99.60</TEL>
<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 DLhierarchy 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/About/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
siamese
frog
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
Anatomical Entity
Conceptual
Anatomical Entity
-is a-
Anatomical
Relationship
Material Physical
Anatomical Entity
Body
Substance
Anatomical
Space
Anatomical
Structure
Biological
Macromolecule
Cell
Part
Non-material Physical
Anatomical Entity
Cell
Tissue
Organ
Organ
Part
Organ
System
Body
Part
Human
Body
92
Anatomical Entity
Physical
Anatomical Entity
Conceptual
Anatomical Entity
-is a-
Anatomical
Relationship
Material Physical
Anatomical Entity
Body
Substance
Anatomical
Space
Anatomical
Structure
Biological
Macromolecule
Cell
Part
Non-material Physical
Anatomical Entity
Cell
Tissue
Organ
Organ
Part
Organ
System
Body
Part
A window on reality
Human
Body
93
Anatomical
Structure
Anatomical Space
Organ Cavity
Subdivision
Organ
Cavity
Organ
Serous Sac
Cavity
Subdivision
Serous Sac
Cavity
Serous Sac
Organ
Component
Organ
Subdivision
Pleural Sac
Pleural
Cavity
Parietal
Pleura
Interlobar
recess
Organ Part
Mediastinal
Pleura
Tissue
Pleura(Wall
of Sac)
Visceral
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
biological
processes
molecular
functions
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
Plant Ontology
Yeast Ontology
Disease Ontology
Mouse Anatomy
Ontology
Cell 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 highlevel interdisciplinary research
to assist in coordination and integration of
projects in ontological research being
pursued in Buffalo
122
Gary Byrd
Charles Dement
Randall Dipert
John Eisner
Daniel Fischer
Louis Goldberg
Jorge Gracia
David Hershenov
Rajiv Kishore
Eric Little
James Llinas
David Mark
Bill Rapaport
Galina Rogova
Ram Ramesh
Stuart C. Shapiro
Barry Smith
Rohini Srihari
Moises Sudit
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