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1
What is an Ontology and What is it Useful For?
Barry Smith
http://ontology.buffalo.edu/smith
• html demonstrated the power of the Web to allow sharing of information
• can we use semantic technology to create a Web 2.0 which would allow algorithmic reasoning with online information based on XLM, RDF and above all OWL (Web Ontology Language)?
• can we use RDF and OWL to break down silos, and create useful integration of on-line data and information
2
A brief history of the Semantic Web
people tried, but the more they were successful, they more they failed
OWL breaks down data silos via controlled vocabularies for the description of data dictionaries
Unfortunately the very success of this approach led to the creation of multiple, new, semantic silos – because multiple ontologies are being created in ad hoc ways
3
reasons for this effect• Tim Berners Lee mentality
– let a million ‘lite ontologies bloom’, and somehow intelligence will be created
– ‘links’ can mean anything (à la html)
• shrink-wrapped software mentality – you will not get paid for reusing old and good ontologies
• requirements-driven software development• reducing potential secondary uses
4/24
Ontology success stories, and some reasons for failure
•
A fragment of the “Linked Open Data” in the biomedical domain
5
What you get with ‘mappings’
HPO: all phenotypes (excess hair loss, duck feet)
6
What you get with ‘mappings’
HPO: all phenotypes (excess hair loss, duck feet ...)
NCIT: all organisms
7
What you get with ‘mappings’
all phenotypes (excess hair loss, duck feet)
all organisms
allose (a form of sugar)
8
What you get with ‘mappings’
all phenotypes (excess hair loss, duck feet)
all organisms
allose (a form of sugar)
Acute Lymphoblastic Leukemia (A.L.L.)
9
10
Mappings are hard
They are fragile, and expensive to maintainNeed a new authority to maintain, yielding new
risk of forkingThe goal should be to minimize the need for
mappingsInvest resources in disjoint ontology modules
which work well together – reduce need for mappings to minimum possible
11
Why should you care?
• you need to create systems for data mining and text processing which will yield useful digitally coded output
• if the codes you use are constantly in need of ad hoc repair huge resources will be wasted
• relevant data will not be found• serious reasoning will be defeated from the
start
12/24
13
14
15
…
How to do it right?
• how create an incremental, evolutionary process, where what is good survives, and what is bad fails
• where the number of ontologies needing to be linked is small
• where links are stable• create a scenario in which people will find it
profitable to reuse ontologies, terminologies and coding systems which have been tried and tested
16/24
Uses of ‘ontology’ in PubMed abstracts
17
By far the most successful: GO (Gene Ontology)
18
GO provides a controlled system of terms for use in annotating (describing, tagging) data
• multi-species, multi-disciplinary, open source
• contributing to the cumulativity of scientific results obtained by distinct research communities
• compare use of kilograms, meters, seconds in formulating experimental results
19
Hierarchical view representing relations between represented types 20
Pleural Cavity
Pleural Cavity
Interlobar recess
Interlobar recess
Mesothelium of Pleura
Mesothelium of Pleura
Pleura(Wall of Sac)
Pleura(Wall of Sac)
VisceralPleura
VisceralPleura
Pleural SacPleural Sac
Parietal Pleura
Parietal Pleura
Anatomical SpaceAnatomical Space
OrganCavityOrganCavity
Serous SacCavity
Serous SacCavity
AnatomicalStructure
AnatomicalStructure
OrganOrgan
Serous SacSerous Sac
MediastinalPleura
MediastinalPleura
TissueTissue
Organ PartOrgan Part
Organ Subdivision
Organ Subdivision
Organ Component
Organ Component
Organ CavitySubdivision
Organ CavitySubdivision
Serous SacCavity
Subdivision
Serous SacCavity
Subdivision
part
_of
is_a
Foundational Model of Anatomy (FMA)
21
US $100 mill. invested in literature and data curation using GO
over 11 million annotations relating gene products described in the UniProt, Ensembl and other databases to terms in the GOexperimental results reported in 52,000 scientific journal articles manually annoted by expert biologists using GO
22
23
Reasons why GO has been successful
It is a system for prospective standardization built with coherent top level but with content contributed and monitored by domain specialists
Based on community consensusUpdated every nightClear versioning principles ensure backwards
compatibility; prior annotations do not lose their value
Initially low-tech to encourage users, with movement to more powerful formal approaches (including OWL-DL – though GO community still recommending caution)
24
GO has learned the lessons of successful cooperation
• Clear documentation• The terms chosen are already familiar• Fully open source (allows thorough testing in
manifold combinations with other ontologies)• Subjected to considerable third-party critique• Rapid turnaround tracker and help desk• Usable also for education• Focus on reality
Why is the focus on reality important
Each community, each local data structure, has its own conceptualization
What shall serve as benchmark for the integration of the data generated by data communities?
Answer: Reality, as understood by bench scientists
Conclusion: Bench scientists have to be involved in the construction and coordination of ontologies
25
26
Data structures and ontologies have different purposes
Information models and ontologies are at different levels• The purpose of an information model is:to
specify valid data structures to carry information
• To constrain the data structures to just those which a given software system can process
The purpose of an ontology is to represent the world
27
Data structures and ontologies have different characteristics
All persons have a sex
However not all data structures about people have a field for sex
Information structures are intrinsically closed
We can describe them completely
Ontologies are intrinsically open
We can never describe the real world completely
Benefits of GO
Establishing a bridge between the molecular/gene level and higher order biology – you get nothing by just looking at genes.
Building up a larger picture of biological systems as a mosaic of areas studied in depth by one or other of the model organism databases (but never all, and not all in any one)
Creating a view to link studies on different organisms.
28
Sample Gene Array Data
29
30
where in the body ?
what kind of disease process ?
need for semantic annotation of data
31
natural language labels
to make the data cognitively accessible to human beings
32
compare: legends for mapscompare: legends for maps
33
ontologies are legends for data
34
annotation with Gene Ontology
supports reusability of data
supports search of data by humans
supports reasoning with data by humans and machines
GO has been amazingly successful in overcoming the data balkanization
problembut it covers only generic biological entities of three sorts:
– cellular components– molecular functions– biological processes
and it does not provide representations of diseases, symptoms, …
35
RELATION TO TIME
GRANULARITY
CONTINUANT OCCURRENT
INDEPENDENT DEPENDENT
ORGAN ANDORGANISM
Organism(NCBI
Taxonomy)
Anatomical Entity(FMA, CARO)
OrganFunction
(FMP, CPRO) Phenotypic
Quality(PaTO)
Biological Process
(GO)CELL AND CELLULAR
COMPONENT
Cell(CL)
Cellular Compone
nt(FMA, GO)
Cellular Function
(GO)
MOLECULEMolecule
(ChEBI, SO,RnaO, PrO)
Molecular Function(GO)
Molecular Process
(GO)
Original OBO Foundry ontologies (Gene Ontology in yellow) 36
37
RELATION TO TIME
GRANULARITY
CONTINUANT OCCURRENT
INDEPENDENT DEPENDENT
ORGAN ANDORGANISM
Organism(NCBI
Taxonomy)
Anatomical Entity(FMA, CARO)
OrganFunction
(FMP, CPRO) Phenotypic
Quality(PaTO)
Biological Process
(GO)CELL AND CELLULAR
COMPONENT
Cell(CL)
Cellular Compone
nt(FMA, GO)
Cellular Function
(GO)
MOLECULEMolecule
(ChEBI, SO,RnaO, PrO)
Molecular Function(GO)
Molecular Process
(GO)
Environment Ontology
envi
ron
men
ts
are
her
e
38
RELATION TO TIME
GRANULARITY
CONTINUANT OCCURRENT
INDEPENDENT DEPENDENT
COMPLEX OFORGANISMS
Family, Community, Deme, Population
OrganFunction
(FMP, CPRO)
Population Phenotype
PopulationProcess
ORGAN ANDORGANISM
Organism(NCBI
Taxonomy)
Anatomical Entity(FMA, CARO) Phenotypic
Quality(PaTO)
Biological Process
(GO)CELL AND CELLULAR
COMPONENT
Cell(CL)
Cellular Componen
t(FMA, GO)
Cellular Function
(GO)
MOLECULEMolecule
(ChEBI, SO,RnaO, PrO)
Molecular Function(GO)
Molecular Process
(GO)
http://obofoundry.org
Ontology success stories, and some reasons for failure
•
39
40
RELATION TO TIME
GRANULARITY
CONTINUANT OCCURRENT
INDEPENDENT DEPENDENT
COMPLEX OFORGANISMS
Family, Community, Deme, Population
OrganFunction
(FMP, CPRO)
Population Phenotype
PopulationProcess
ORGAN ANDORGANISM
Organism(NCBI
Taxonomy)
Anatomical Entity(FMA, CARO) Phenotypic
Quality(PaTO)
Biological Process
(GO)CELL AND CELLULAR
COMPONENT
Cell(CL)
Cellular Componen
t(FMA, GO)
Cellular Function
(GO)
MOLECULEMolecule
(ChEBI, SO,RnaO, PrO)
Molecular Function(GO)
Molecular Process
(GO)
http://obofoundry.org
Developers commit to working to ensure that, for each domain, there is community convergence on a single ontology
and agree in advance to collaborate with developers of ontologies in adjacent domains.
http://obofoundry.org
The OBO Foundry: a step-by-step, evidence-based approach to expand
the GO
41
OBO Foundry Principles
Common governance (coordinating editors)
Common training
Common architecture to overcome Tim Berners Lee-ism:
• simple shared top level ontology
• shared Relation Ontology: www.obofoundry.org/ro
42
Open Biomedical Ontologies Foundry
Seeks to create high quality, validated terminology modules across all of the life sciences which will be
• one ontology for each domain, so no need for mappings
• close to language use of experts
• evidence-based
• incorporate a strategy for motivating potential developers and users
• revisable as science advances
43
44
A prospective standard
designed to guarantee interoperability of ontologies from the very start (and to keep out weeds)
initial set of 10 criteria tested in the annotation of
scientific literature
model organism databases
life science experimental results
45
ORTHOGONALITY
modularity ensures • annotations can be additive• division of labor amongst domain experts• high value of training in any given module• lessons learned in one module can benefit
work on other modules• incentivization of those responsible for
individual modules
Benefits of coordination
Can profit from lessons learned through mistakes made by others
Can more easily reuse what is made by others
Can more easily inspect and criticize results of others’ work
Leads to innovations (e.g. Mireot in strategies for combining ontologies and for importing terms from other ontologies)
46
Problems with the OBO Foundry
1. the results are over-complex for almost all users
2. high quality ontology development is slow, slow, slow
For 1., views (Brinkley, Uvic, ontodog, …)
For 2., the hub and spokes model
47
The Hub and Spokes Model
“Constructing a lattice of Infectious Disease Ontologies from a Staphylococcus aureus Isolate Repository”
Albert Goldfain, Lindsay Cowell and Barry Smith, Proceeedings of the Third International Conference on Biomedical Ontology, Graz, July 22-25, 2012, forthcoming.
48
Infectious Disease Ontology (IDO)
– IDO Core: • General terms in the ID domain. • A hub for all IDO extensions.
– IDO Extensions: • Disease specific. • Developed by subject matter experts.
• Provides:– Clear, precise, and consistent natural language
definitions– Computable logical representations (OWL, OBO)
How IDO evolvesIDOCore
IDOSa
IDOHumanSa
IDORatSa
IDOStrep
IDORatStrep
IDOHumanStrep
IDOMRSa
IDOHumanBacterial
IDOAntibioticResistant
IDOMAL IDOHIVCORE and SPOKES:Domain ontologies
SEMI-LATTICE:By subject matter experts in different communities of interest.
IDOFLU
IDO Core
• Contains general terms in the ID domain:– E.g., ‘colonization’, ‘pathogen’, ‘infection’
• A contract between IDO extension ontologies and the datasets that use them.
• Intended to represent information along several dimensions:– biological scale (gene, cell, organ, organism, population)– discipline (clinical, immunological, microbiological) – organisms involved (host, pathogen, and vector types)
Sample IDO Definitions
• Host of Infectious Agent (BFO Role): A role borne by an organism in virtue of the fact that its extended organism contains an infectious agent.
• Extended Organism (OGMS): An object aggregate consisting of an organism and all material entities located within the organism, overlapping the organism, or occupying sites formed in part by the organism.
• Infectious Agent: A pathogen whose pathogenic disposition is an infectious disposition.
IDO and IDOSa
• Scale of the infection (disorder)
from Shetty, Tang, and Andrews, 200912/10/2010 53
Staphylococcus aureus (Sa)
MSSa MRSa
HA-MRSa CA-MRSa
UK CA-MRSa Australian CA-MRSa
Specific Strains
{Antibiotic Resistance
{Pathogenesis Location Type
{Geographic Region
{Various Differentia
Differentiated by:
Sample Application: A lattice of infectious disease application ontologies from NARSA isolate data
Network on Antimicrobial Resistance in Staphylococcus aureus–http://www.narsa.net/content/staphLinks.jsp
True personalized medicine – YourDiseaseOntology
Ways of differentiating Staphylococcus aureus infectious diseases
• Infectious Disease– By host type– By (sub-)species of pathogen– By antibiotic resistance– By anatomical site of infection
• Bacterial Infectious Disease– By PFGE (Strain)– By MLST (Sequence Type)– By BURST (Clonal Complex)
• Sa Infectious Disease– By SCCmec type
• By ccr type• By mec class
– spa type
http://www.sccmec.org/Pages/SCC_ClassificationEN.html
ido.owl
narsa.owl
narsa-isolates.owl
ndf-rt
NRS701’s resistance to clindamycin
New York State Center of Excellence in Bioinformatics & Life Sciences
R T U New York State Center of Excellence in Bioinformatics & Life Sciences
R T U
Ontologies make data collections comparable
...
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case5
case4
case3
case2
case1
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CharacteristicsCases
...
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case1
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CharacteristicsCases
...
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case4
case3
case2
case1
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CharacteristicsCases
...
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case5
case4
case3
case2
case1
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CharacteristicsCases
...
case6
case5
case4
case3
case2
case1
...ch6ch5ch4ch3ch2ch1
CharacteristicsCases
...
case6
case5
case4
case3
case2
case1
...ch6ch5ch4ch3ch2ch1
CharacteristicsCases
Linking the variables of distinct data collections to a realism-based ontology.
New York State Center of Excellence in Bioinformatics & Life Sciences
R T U New York State Center of Excellence in Bioinformatics & Life Sciences
R T U
Werner Ceusters
1R01DE021917-01A1
National Institute of Dental and Craniofacial Research (NIDCR).
OPMQoL: an Ontology for pain-related disablement, mental
health and quality of life
IASP definition for ‘pain’:– ‘an unpleasant sensory and emotional experience
associated with actual or potential tissue damage, or described in terms of such damage’;
which asserts:– a common phenomenology (‘unpleasant sensory
and emotional experience’) to all instances of pain,
– the recognition of three distinct subtypes of pain involving, respectively:
1. actual tissue damage, 2. what is called ‘potential tissue damage’, and 3. a description involving reference to tissue damage
whether or not there is such damage.
data collection
data item
1
1..*
A data collection consists of at least 1 data item, each data item belonging to exactly 1 collection
data collection
data dictionaryuses
1..*
1
used-for
data item
1
1..*
1
explained-in
1..*
exp
lain
s
Data dictionaries provide information about data items and data collections
data collection
assessmentinstrument
data dictionary
uses
used-in
1..*
uses
1..*
1
used-for
data item
0..*
terminology
1
1..*
uses 1..* usedfor
0..*1
explained-in
1..*
exp
lain
s
uses1..*
usedfor
0..*
Data dictionaries provide also information about terminologies and assessment instruments used for data
generation, in addition to information about the collection’s structure
data collection
assessmentinstrument
data dictionary
uses
used-in
1..*
uses
1..*
1
used-for
data item
0..*
terminology
1
1..*
uses 1..* usedfor
0..*1
explained-in
1..*
exp
lain
s
uses1..*
usedfor
0..*
Relation of Terminology component to Data component
Terminology component
Data component
term
concept
1broader
narrower1..*
1..*
used in
uses0..*
0..*
1..*
means
expressed-by
data collection
assessmentinstrument
data dictionary
uses
used-in
1..*
uses
1..*
1
1..*
used-for
Terminology component
Data component
data item
0..*
terminology1
1
1..*
uses 1..* usedfor
0..*1
explained-in
1..*
exp
lain
s
uses1..*
usedfor
0..*
Terminology links terms to ‘concepts’
term
concept
1broader
narrower1..*
1..*
used in
uses0..*
0..*
1..*
means
expressed-by
data collection
assessmentinstrument
data dictionary
uses
used-in
1..*
uses
1..*
1
1..*
used-for
Terminology component
Data component
data item
0..*
terminology1
1
1..*
uses 1..* usedfor
0..*1
explained-in
1..*
exp
lain
s
uses1..*
usedfor
0..*
Not ‘concepts’ are of interest, but entities in reality
Ontologycomponent
entity
term
concept
1broader
narrower1..*
1..*
used in
uses0..*
0..*
1..*
means
expressed-by
data collection
assessmentinstrument
data dictionary
uses
used-in
1..*
uses
1..*
1
1..*
used-for
Terminology component
Data component
data item
0..*
terminology1
1
1..*
uses 1..* usedfor
0..*1
explained-in
1..*
exp
lain
s
uses1..*
usedfor
0..*
It is real entities that should be denoted in ontologies
Ontologycomponent
entity
ontology
reference ontology1..*
1
denotes0..*
denoted by
1
denotator
term
concept
1broader
narrower1..*
1..*
used in
uses0..*
0..*
1..*
means
expressed-by
data collection
assessmentinstrument
data dictionary
uses
used-in
1..*
uses
1..*
1
1..*
used-for
Terminology component
Data component
data item
0..*
terminology1
1
1..*
uses 1..* usedfor
0..*1
explained-in
1..*
exp
lain
s
uses1..*
usedfor
0..*
Application ontologies cover the domains of the sources
Ontologycomponent
entity
ontology
reference ontology1..*
1
denotes0..*
denoted by
1
denotator
1
used-for1..*
usedfor
1
uses
applicationontology
data collectionontology
assessment instrument ontology
1uses
term
concept
1broader
narrower1..*
1..*
used in
uses0..*
0..*
1..*
means
expressed-by
data collection
assessmentinstrument
0..1expresses
0..*
ontology
data dictionary
uses
used-in
1
1..*
uses
1..*
1
reference ontology
1..*
used-for1..*
usedfor
1
uses
bridging axiom
used-for
usedfor
0..*
uses1..*
applicationontology
Terminology component
Data component
Ontologycomponent
data item
representationalartifact
1..*
data collectionontology
assessment instrument ontology
1uses
0..*
terminology
1..*
uses1
used-for
entity 1
denotes0..*
denoted by
1
1
1..*
uses 1..* usedfor
0..*
1
corresponds-to
1
explained-in
1..*
exp
lain
s
uses1..*
usedfor
0..*
denotator
Bridging axioms link data to ontologies and terminologies
Anatomy Ontology(FMA*, CARO)
Environment
Ontology(EnvO)
Infectious Disease
Ontology(IDO*)
Biological Process
Ontology (GO*)
Cell Ontology
(CL)
CellularComponentOntology
(FMA*, GO*) Phenotypic Quality
Ontology(PaTO)
Subcellular Anatomy Ontology (SAO)Sequence Ontology
(SO*) Molecular Function
(GO*)Protein Ontology(PRO*) OBO Foundry Modular Organization 71
top level
mid-level
domain level
Information Artifact Ontology
(IAO)
Ontology for Biomedical
Investigations(OBI)
Spatial Ontology(BSPO)
Basic Formal Ontology (BFO)
BFO: the very top
Continuant Occurrent(Process, Event)
IndependentContinuant
DependentContinuant
73
RELATION TO TIME
GRANULARITY
CONTINUANT OCCURRENT
INDEPENDENT DEPENDENT
ORGAN ANDORGANISM
Organism(NCBI
Taxonomy)
Anatomical Entity(FMA, CARO)
OrganFunction
(FMP, CPRO) Phenotypic
Quality(PaTO)
Biological Process
(GO)CELL AND CELLULAR
COMPONENT
Cell(CL)
Cellular Compone
nt(FMA, GO)
Cellular Function
(GO)
MOLECULEMolecule
(ChEBI, SO,RnaO, PrO)
Molecular Function(GO)
Molecular Process
(GO)
CONTINUANT OCCURRENT
INDEPENDENT DEPENDENT
ORGAN ANDORGANISM
Organism(NCBI
Taxonomy)
Anatomical Entity
(FMA, CARO)
OrganFunction
(FMP, CPRO) Phenotypic
Quality(PaTO)
Organism-Level Process
(GO)
CELL AND CELLULAR
COMPONENT
Cell(CL)
Cellular Compone
nt(FMA, GO)
Cellular Function
(GO)
Cellular Process
(GO)
MOLECULEMolecule
(ChEBI, SO,RnaO, PrO)
Molecular Function(GO)
Molecular Process
(GO)
obofoundry.org
GRANULARITY
RELATION TO TIME
Basic Formal Ontology
continuant occurrent
biological processes
independentcontinuant
cellular component
dependentcontinuant
molecular function
BFO: The Very Top
continuant
independentcontinuant
dependentcontinuant
qualityfunctionroledisposition
occurrent
Basic Formal Ontology
Continuant Occurrent
process, eventIndependentContinuant
thing
DependentContinuant
quality
.... ..... .......
types
instances
Basic of BFO in GO
Continuant Occurrent
biological processIndependent
Continuant
cellular component
DependentContinuant
molecular function
..... ..... ........
Experience with BFO in building ontologies provides
• a community of skilled ontology developers and users (google user group has 118 members)
• associated logical tools • documentation for different types of users• a methodology for building conformant ontologies
by starting with BFO and populating downwards
Example: The Cell Ontology
:.
Users of BFOPharmaOntology (W3C HCLS SIG)
MediCognos / Microsoft Healthvault
Cleveland Clinic Semantic Database in Cardiothoracic Surgery
Major Histocompatibility Complex (MHC) Ontology (NIAID)
Neuroscience Information Framework Standard (NIFSTD) and Constituent Ontologies
Interdisciplinary Prostate Ontology (IPO)
Nanoparticle Ontology (NPO): Ontology for Cancer Nanotechnology Research
Neural Electromagnetic Ontologies (NEMO)
ChemAxiom – Ontology for Chemistry
81
:.
Users of BFOGO Gene Ontology
CL Cell Ontology
SO Sequence Ontology
ChEBI Chemical Ontology
PATO Phenotype (Quality) Ontology
FMA Foundational Model of Anatomy Ontology
ChEBI Chemical Entities of Biological Interest
PRO Protein Ontology
Plant Ontology
Environment Ontology
Ontology for Biomedical Investigations
RNA Ontology
82
:.
Users of BFOOntology for Risks Against Patient Safety (RAPS/REMINE)
eagle-i an VIVO (NCRR)
IDO Infectious Disease Ontology (NIAID)
National Cancer Institute Biomedical Grid Terminology (BiomedGT)
US Army Biometrics Ontology
US Army Command and Control Ontology
Sleep Domain Ontology
Subcellular Anatomy Ontology (SAO)
Translaftional Medicine On (VO)
Yeast Ontology (yOWL)
Zebrafish Anatomical Ontology (ZAO)
83
Basic Formal Ontology
continuant occurrent
independentcontinuant
dependentcontinuant
organism
84
Continuants
• continue to exist through time, preserving their identity while undergoing different sorts of changes
• independent continuants – objects, things, ...
• dependent continuants – qualities, attributes, shapes, potentialities ...
85
Occurrents
• processes, events, happenings– your life– this process of accelerated cell
division
86
Qualitiestemperatureblood pressuremass...
are continuantsthey exist through time while undergoing changes
87
Qualitiestemperature / blood pressure /
mass ...are dimensions of variation within the structure of the entitya quality is something which can change while its bearer remains one and the same
88
A Chart representing how John’s temperature
changes
89
A Chart representing how John’s temperature
changes
90
John’s temperature,the temperature he has throughout his entire life, cycles through different determinate temperatures from one time to the next
John’s temperature is a physiology variable which, in thus changing, exerts an influence on other physiology variables through time
91
BFO: The Very Top
continuant
independentcontinuant
dependentcontinuant
quality
occurrent
temperature 92
Blinding Flash of the Obvious
independentcontinuant
dependentcontinuant
quality
temperature types
instances
organism
John John’s
temperature 93
Blinding Flash of the Obvious
independentcontinuant
dependentcontinuant
quality
temperature types
instances
organism
John John’s
temperature 94
Blinding Flash of the Obvious
temperature types
instances
organism
John John’s
temperature .
95
inheres_in
temperature types
instances
John’s temperature
96
37ºC37.1º
C37.5º
C37.2º
C37.3º
C37.4º
C
instantiates at t1
instantiates at t2
instantiates at t3
instantiates at t4
instantiates at t5
instantiates at t6
human types
instances
John
97
embryo
fetus adultneonat
einfant child
instantiates at t1
instantiates at t2
instantiates at t3
instantiates at t4
instantiates at t5
instantiates at t6
Temperature subtypesDevelopment-stage
subtypes
are threshold divisions (hence we do not have sharp boundaries, and we have a certain degree of choice, e.g. in how many subtypes to distinguish, though not in their ordering)
98
independentcontinuant
dependentcontinuant
quality
temperature types
instances
organism
John John’s
temperature
99
independentcontinuant
dependentcontinuant
quality
temperature
organism
John John’s
temperature
occurrent
process
course of temperature
changes
John’s temperature history
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independentcontinuant
dependentcontinuant
quality
temperature
organism
John John’s
temperature
occurrent
process
temperature process profile
John’s temperature history
independentcontinuant
dependentcontinuant
quality
temperature
organism
John John’s
temperature
occurrent
process
life of an organism
John’s life
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BFO: The Very Top
continuant occurrent
independentcontinuant
dependentcontinuant
quality disposition
103
Disposition- of a glass vase, to shatter if dropped- of a human, to eat - of a banana, to ripen- of John, to lose hair
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Dispositionif it ceases to exist, then its bearer and/or its immediate surrounding environment is physically changedits realization occurs when its bearer is in some special physical circumstancesits realization is what it is in virtue of the bearer’s physical make-up
105
:.
Function - of liver: to store glycogen- of birth canal: to enable transport- of eye: to see- of mitochondrion: to produce ATP
functions are dispositions which are designed or selected for
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independentcontinuant
dependentcontinuant
function
to seeeye
John’s eye function of John’s eye: to see
occurrent
process
process of seeing
John seeing
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OGMSOntology for General Medical
Science
http://code.google.com/p/ogms
108
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Physical Disorder
:.
Physical Disorder
– independent continuantfiat object part
A causally linked combination of physical components of the extended organism that is clinically abnormal.
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Clinically abnormal
– (1) not part of the life plan for an organism of the relevant type (unlike aging or pregnancy),
– (2) causally linked to an elevated risk either of pain or other feelings of illness, or of death or dysfunction, and
– (3) such that the elevated risk exceeds a certain threshold level.*
*Compare: baldness111
Big Picture
112
http://code.google.com/p/ogms
Disease =def. – A disposition to undergo pathological processes that exists in an organism because of one or more disorders in that organism.
Disease course =def. – The aggregate of processes in which a disease disposition is realized.
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Pathological Process=def. A bodily process that is a manifestation of a disorder and is clinically abnormal.
Disease =def. – A disposition to undergo pathological processes that exists in an organism because of one or more disorders in that organism.
114
Cirrhosis - environmental exposure
• Etiological process - phenobarbitol-induced hepatic cell death– produces
• Disorder - necrotic liver– bears
• Disposition (disease) - cirrhosis– realized_in
• Pathological process - abnormal tissue repair with cell proliferation and fibrosis that exceed a certain threshold; hypoxia-induced cell death– produces
• Abnormal bodily features– recognized_as
• Symptoms - fatigue, anorexia• Signs - jaundice, enlarged spleen
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Influenza - infectious
• Etiological process - infection of airway epithelial cells with influenza virus
– produces
• Disorder - viable cells with influenza virus
– bears
• Disposition (disease) - flu
– realized_in
• Pathological process - acute inflammation
– produces
• Abnormal bodily features
– recognized_as
• Symptoms - weakness, dizziness
• Signs - fever 116
Dispositions and Predispositions
All diseases are dispositions; not all dispositions are diseases.
Predisposition to Disease
=def. – A disposition in an organism that constitutes an increased risk of the organism’s subsequently developing some disease.
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Huntington’s Disease - genetic
• Etiological process - inheritance of >39 CAG repeats in the HTT gene– produces
• Disorder - chromosome 4 with abnormal mHTT– bears
• Disposition (disease) - Huntington’s disease– realized_in
• Pathological process - accumulation of mHTT protein fragments, abnormal transcription regulation, neuronal cell death in striatum– produces
• Abnormal bodily features– recognized_as
• Symptoms - anxiety, depression• Signs - difficulties in speaking and
swallowing
Symptoms & Signs used_in
Interpretive process produces
Hypothesis - rule out Huntington’s suggests
Laboratory tests produces
Test results - molecular detection of the HTT gene with >39CAG repeats used_in
Interpretive process produces
Result - diagnosis that patient X has a disorder that bears the disease Huntington’s disease
HNPCC - genetic pre-disposition
• Etiological process - inheritance of a mutant mismatch repair gene– produces
• Disorder - chromosome 3 with abnormal hMLH1– bears
• Disposition (disease) - Lynch syndrome– realized_in
• Pathological process - abnormal repair of DNA mismatches– produces
• Disorder - mutations in proto-oncogenes and tumor suppressor genes with microsatellite repeats (e.g. TGF-beta R2)– bears
• Disposition (disease) - non-polyposis colon cancer
Systemic arterial hypertension
• Etiological process – abnormal reabsorption of NaCl by the kidney
– produces
• Disorder – abnormally large scattered molecular aggregate of salt in the blood
– bears
• Disposition (disease) - hypertension
– realized_in
• Pathological process – exertion of abnormal pressure against arterial wall
– produces
• Abnormal bodily features
– recognized_as
• Symptoms -
• Signs – elevated blood pressure
Symptoms & Signs used_in
Interpretive process produces
Hypothesis - rule out hypertension suggests
Laboratory tests produces
Test results - used_in
Interpretive process produces
Result - diagnosis that patient X has a disorder that bears the disease hypertension
Type 2 Diabetes Mellitus
• Etiological process – – produces
• Disorder – abnormal pancreatic beta cells and abnormal muscle/fat cells
– bears• Disposition (disease) – diabetes mellitus
– realized_in• Pathological processes – diminished
insulin production , diminished muscle/fat uptake of glucose
– produces• Abnormal bodily features
– recognized_as• Symptoms – polydipsia, polyuria,
polyphagia, blurred vision• Signs – elevated blood glucose and
hemoglobin A1c
Symptoms & Signs used_in
Interpretive process produces
Hypothesis - rule out diabetes mellitus suggests
Laboratory tests – fasting serum blood glucose, oral glucose challenge test, and/or blood hemoglobin A1c produces
Test results - used_in
Interpretive process produces
Result - diagnosis that patient X has a disorder that bears the disease type 2 diabetes mellitus
Type 1 hypersensitivity to penicillin
• Etiological process – sensitizing of mast cells and basophils during exposure to penicillin-class substance
– produces• Disorder – mast cells and basophils with
epitope-specific IgE bound to Fc epsilon receptor I
– bears• Disposition (disease) – type I
hypersensitivity– realized_in
• Pathological process – type I hypersensitivity reaction
– produces• Abnormal bodily features
– recognized_as• Symptoms – pruritis, shortness of breath• Signs – rash, urticaria, anaphylaxis
Symptoms & Signs used_in
Interpretive process produces
Hypothesis - suggests
Laboratory tests – produces
Test results – occasionally, skin testing used_in
Interpretive process produces
Result - diagnosis that patient X has a disorder that bears the disease type 1 hypersensitivity to penicillin
Early Onset Alzheimer’s Disease
Disorder – mutations in APP, PSEN1 and PSEN2bears
Disposition – impaired APP processingrealized in
Pathological process – accumulation of intra- and extracellular protein in the brainproduces
Disorder – amyloid plaque and neurofibrillary tanglesbearsDisposition – of neurons to dierealized in Pathological process – neuronal loss
producesDisorder – cognitive brain regions damaged and reduced in size
bearsDisposition (disease) – Alzheimer’s dementia
realized inSymptoms – episodic memory loss and other cognitive domain impairment
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Arterial Aneurysm• Disposition – atherosclerosis
– realized in• Pathological process – fatty material collects within the walls of arteries
– produces• Disorder – artery with weakened wall
– bears• Disposition – of artery to become distended
– realized_in• Pathological process – process of distending
– produces• Disorder – arterial aneurysm
– bears• Disposition – of artery to rupture
– realized in• Pathological process – (catastrophic event) of rupturing
– produces• Disorder – ruptured artery, arterial system with dangerously low blood pressure
– bears• Disposition – circulatory failure
– realized in• Pathological process – exsanguination, failure of homeostasis
– produces• Death
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Hemorrhagic stroke
• Disorder – cerebral arterial aneurysm– bears
• Disposition – of weakened artery to rupture– realized in
• Pathological process – rupturing of weakened blood vessel– produces
• Disorder – Intraparenchymal cerebral hemorrhage– bears
• Disposition (disease) – to increased intra-cranial pressure– realized in
• Pathological process – increasing intra-cranial pressure, compression of brain structures– produces
• Disorder – Cerebral ischemia, Cerebral neuronal death– bears
• Disposition (disease) – stroke– realized in
• Symptoms – weakness/paralysis, loss of sensation, etc
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coronary heart disease
John’s coronary heart disease
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asymptomatic (‘silent’) infarction
early lesions and small
fibrous plaques
stable angina
surface disruption of plaque
unstable angina
instantiates at t1
instantiates at t2
instantiates at t3
instantiates at t4
instantiates at t5
time
independentcontinuant
dependentcontinuant
disposition
diseasedisorder
John’s disordered
heart
John’s coronary heart
disease
occurrent
process
course of disease
course of John’s disease
128