formal ontology for the improvement and integration of biomedical terminologies j. simon*...

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Formal Ontology for the improvement and integration of biomedical terminologies J. Simon* Ontology-based algorithms for error checking and semantic relationships expansion M. Casella dos Santos** AMIA 2003 titute for Formal Ontology and Medical Information Science (IFOMIS), Leipzig anguage & Computing nv, Zonnegem, Belgium

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Page 1: Formal Ontology for the improvement and integration of biomedical terminologies J. Simon* Ontology-based algorithms for error checking and semantic relationships

Formal Ontology for the improvement and integration of

biomedical terminologiesJ. Simon*

Ontology-based algorithms for error checking and semantic relationships

expansionM. Casella dos Santos**

AMIA

2003

*Institute for Formal Ontology and Medical Information Science (IFOMIS), Leipzig, Germany** Language & Computing nv, Zonnegem, Belgium

Page 2: Formal Ontology for the improvement and integration of biomedical terminologies J. Simon* Ontology-based algorithms for error checking and semantic relationships

PRESENTATION OVERVIEW

• Introducing LinKBase

• Introducing BFO; The Philosophical Ground

• Ontology integration problems and solutions

• Applying correct subsumption

• Axiomatizing LinKBase with BFO

• Conclusion

Page 3: Formal Ontology for the improvement and integration of biomedical terminologies J. Simon* Ontology-based algorithms for error checking and semantic relationships

Data structure andfunction library for

language understanding

Medical and linguisticknowledge required for

language understanding

NLU enabling tools forknowledge supported

data-entry and -retrieval

An Integrated Approach

Page 4: Formal Ontology for the improvement and integration of biomedical terminologies J. Simon* Ontology-based algorithms for error checking and semantic relationships

LinKBase

A Medical Domain Ontology designed to support NLP applications and to integrate different medical terminologies and ontologies.

•Enables cross-mappings between external medical terminologies (i.e. ICD-9-CM, ICD-10, SNOMED, Mesh, MedDRA, etc.).

•The world’s largest medical ontology totalling more than 2,000,000 concepts and 5,300,000 links.

•The ontological elements (concepts, linktypes, criteria) are language independent and are linked to about 3,500,000 terms in various languages (English, Spanish, French, etc.).

Page 5: Formal Ontology for the improvement and integration of biomedical terminologies J. Simon* Ontology-based algorithms for error checking and semantic relationships

Medico-linguistic Ontology

Formal Domain Ontology

Lexicon

Grammar

Language ALanguage A

Lexicon

Grammar

LanguageLanguage BB

Cassandra Linguistic Ontology MEDDRA

ICD

SNOMED

ICPC

Others ...

Proprietary Terminologies

Page 6: Formal Ontology for the improvement and integration of biomedical terminologies J. Simon* Ontology-based algorithms for error checking and semantic relationships
Page 7: Formal Ontology for the improvement and integration of biomedical terminologies J. Simon* Ontology-based algorithms for error checking and semantic relationships

Medico-linguistic Ontology

Formal Domain Ontology

Lexicon

Grammar

Language ALanguage A

Lexicon

Grammar

LanguageLanguage BB

Cassandra Linguistic Ontology MEDDRA

ICD

SNOMED

ICPC

Others ...

Proprietary Terminologies

Page 8: Formal Ontology for the improvement and integration of biomedical terminologies J. Simon* Ontology-based algorithms for error checking and semantic relationships
Page 9: Formal Ontology for the improvement and integration of biomedical terminologies J. Simon* Ontology-based algorithms for error checking and semantic relationships

BFO/MedO and LinkBase

BFO/MedO

“validates”

linguistic ontologies

(per language)

medical+linguistic ontology

normativeconcept system(s)

Realist ontology

Page 10: Formal Ontology for the improvement and integration of biomedical terminologies J. Simon* Ontology-based algorithms for error checking and semantic relationships

Theory of Granular Partitions (B. Smith)

Think of it as Alberti’s grid

Page 11: Formal Ontology for the improvement and integration of biomedical terminologies J. Simon* Ontology-based algorithms for error checking and semantic relationships

Partitions

• An ontology is a partition of reality• A partition cuts the world in a certain

way• There can be many different

partitions of the same reality

Page 12: Formal Ontology for the improvement and integration of biomedical terminologies J. Simon* Ontology-based algorithms for error checking and semantic relationships

Maryland Congressional Representative Voting Zones

Page 13: Formal Ontology for the improvement and integration of biomedical terminologies J. Simon* Ontology-based algorithms for error checking and semantic relationships

Maryland Appellate Judicial Districts

Page 14: Formal Ontology for the improvement and integration of biomedical terminologies J. Simon* Ontology-based algorithms for error checking and semantic relationships
Page 15: Formal Ontology for the improvement and integration of biomedical terminologies J. Simon* Ontology-based algorithms for error checking and semantic relationships
Page 16: Formal Ontology for the improvement and integration of biomedical terminologies J. Simon* Ontology-based algorithms for error checking and semantic relationships
Page 17: Formal Ontology for the improvement and integration of biomedical terminologies J. Simon* Ontology-based algorithms for error checking and semantic relationships

A Partition View on Meningitis

anatomicalpartition

disorderpartition

inflammationpartition

meninges

disorder of meninges

inflammationof CNS

meningitis

Page 18: Formal Ontology for the improvement and integration of biomedical terminologies J. Simon* Ontology-based algorithms for error checking and semantic relationships

Partitions and LinkBase®

• domain-entity: represents cells of different partitions of reality– MENINGITIS (captured e.g. by the inflammation partition)– MENINGES (captured by an anatomical map)

• meta-entity: represents cells of a partition prepared by third parties– ICD-10 : G03.9 : MENINGITIS, UNSPECIFIED

• domain-entity-link: aspect of domain-entities determining a partition/perspective– HAS-SYSTEMIC-MEDIUM– HAS-CONSEQUENCE

• criterion: perspective on a domain-entity yielded by a given partition– HAS-SYSTEMIC-MEDIUM MENINGES– HAS-CONSEQUENCE HEADACHE

Page 19: Formal Ontology for the improvement and integration of biomedical terminologies J. Simon* Ontology-based algorithms for error checking and semantic relationships

Substances, States, Powers and Functions

• Strict Dependence: ODP(A,B)• A strictly depends on B whenever A

cannot exist unless B does• John’s headache depends on John• Mary’s smile depends on Mary• Peter’s power of performing

weddings depends on Peter• The beating function of Sarah’s

heart depends on Sarah’s heart

Page 20: Formal Ontology for the improvement and integration of biomedical terminologies J. Simon* Ontology-based algorithms for error checking and semantic relationships

• Generic Dependence:• A generically depends on Bs

whenever A cannot exist without there being some B

• A person cannot exist without having some temperature

Generic Dependence

Page 21: Formal Ontology for the improvement and integration of biomedical terminologies J. Simon* Ontology-based algorithms for error checking and semantic relationships

Weak Foundation

• Weak Foundation: WF(A,B)• A is weakly founded on B whenever

A strictly depends on B and all parts of B

Page 22: Formal Ontology for the improvement and integration of biomedical terminologies J. Simon* Ontology-based algorithms for error checking and semantic relationships

Substances

• A Substance is an entity which is not strictly dependent on anything

• SB(x)• SB(x) iff y (x strictly depends on y)

Page 23: Formal Ontology for the improvement and integration of biomedical terminologies J. Simon* Ontology-based algorithms for error checking and semantic relationships

States, Powers and Functions

• States (the state of being happy, having a headache, having a temperature of 98.6°)

• Powers (The power to wed people)• Functions (the function of pumping

blood)• These are not substances; they have

bearers on whom they strictly depend

Page 24: Formal Ontology for the improvement and integration of biomedical terminologies J. Simon* Ontology-based algorithms for error checking and semantic relationships

Inherence

• States, Powers and Functions inhere on the substances that bear them

• IH(x,y)• Thus,• Inhere(x,y) StrictlyDepends(x,y)

Page 25: Formal Ontology for the improvement and integration of biomedical terminologies J. Simon* Ontology-based algorithms for error checking and semantic relationships

Endurants and Perdurants

• Some things persist differently through time than others

• There are on the one hand objects: tables, chairs, countries, and people. These entities are said to endure through time, which means that they do not have temporal parts, but rather are wholly present at every moment in which they exist.

Page 26: Formal Ontology for the improvement and integration of biomedical terminologies J. Simon* Ontology-based algorithms for error checking and semantic relationships

Endurants and Perdurants

• On the other hand are processes like brain surgeries, heart attacks, lives. These are said to perdure through time, which means that they do have temporal parts, such as the first half of the surgery, the last phase of the heart attack, one’s childhood

Page 27: Formal Ontology for the improvement and integration of biomedical terminologies J. Simon* Ontology-based algorithms for error checking and semantic relationships

Endurants and Perdurants

• We call enduring, objectual entities “Endurants”: End(x)

• We call perduring, processual entities “perdurants”: Perd(x)

• No endurant is a perdurant, and no perdurant is an endurant

Page 28: Formal Ontology for the improvement and integration of biomedical terminologies J. Simon* Ontology-based algorithms for error checking and semantic relationships

Endurants and Perdurants

• Endurants and perdurants relate in the relationships of participation and realization

• Perdurants strictly depend on endurants

Page 29: Formal Ontology for the improvement and integration of biomedical terminologies J. Simon* Ontology-based algorithms for error checking and semantic relationships

Participation

• The surgeon operates, the heart beats, lungs inhale

• PP(x,y)• PP(surgeon, surgery)• PP(heart,beating processes)• PP(lungs, respiratory processes)

Page 30: Formal Ontology for the improvement and integration of biomedical terminologies J. Simon* Ontology-based algorithms for error checking and semantic relationships

Realization

• Powers and Functions may go unrealized

• A stopped heart is not realizing its function of pumping blood

• The heart of a tachycardic is not fulfilling the function of beating at a proper rate

• Peter may not currently be realizing his power of wedding couples

Page 31: Formal Ontology for the improvement and integration of biomedical terminologies J. Simon* Ontology-based algorithms for error checking and semantic relationships

Participation and Realization

• Participation is generally a relation between a substance and a process which depends on it (it would not have been the same particular surgery if Dr. Jones had not been there)

• Realization is a relation between a power or function and a process

Page 32: Formal Ontology for the improvement and integration of biomedical terminologies J. Simon* Ontology-based algorithms for error checking and semantic relationships

Functions and Processes

• No function is the same as a process realizing it

• No process is the same as any endurant participating in it

Page 33: Formal Ontology for the improvement and integration of biomedical terminologies J. Simon* Ontology-based algorithms for error checking and semantic relationships

Parts and Wholes

• Proper Parthood: x x• x y y x• x y & y z x z

• Parthood: • x y iff x y or x = y

Page 34: Formal Ontology for the improvement and integration of biomedical terminologies J. Simon* Ontology-based algorithms for error checking and semantic relationships

Parthood

B

AA < B

Page 35: Formal Ontology for the improvement and integration of biomedical terminologies J. Simon* Ontology-based algorithms for error checking and semantic relationships

SNAP BFO

Page 36: Formal Ontology for the improvement and integration of biomedical terminologies J. Simon* Ontology-based algorithms for error checking and semantic relationships

SPAN BFO

Page 37: Formal Ontology for the improvement and integration of biomedical terminologies J. Simon* Ontology-based algorithms for error checking and semantic relationships

Terminology Integration in LinKBase

The Endurant/Perdurant Distinction at Work

Page 38: Formal Ontology for the improvement and integration of biomedical terminologies J. Simon* Ontology-based algorithms for error checking and semantic relationships

Homonymy!

Page 39: Formal Ontology for the improvement and integration of biomedical terminologies J. Simon* Ontology-based algorithms for error checking and semantic relationships
Page 40: Formal Ontology for the improvement and integration of biomedical terminologies J. Simon* Ontology-based algorithms for error checking and semantic relationships

Terminology Integration in LinKBase

Mereological Scrutiny at Work

Page 41: Formal Ontology for the improvement and integration of biomedical terminologies J. Simon* Ontology-based algorithms for error checking and semantic relationships
Page 42: Formal Ontology for the improvement and integration of biomedical terminologies J. Simon* Ontology-based algorithms for error checking and semantic relationships

Terminology Integration in LinKBase

The Function/Realization Distinction at Work

Page 43: Formal Ontology for the improvement and integration of biomedical terminologies J. Simon* Ontology-based algorithms for error checking and semantic relationships

Functions and Processes

LIVER

ABERRANT LIVER

LIVER ACTIVITY

IS-A

IS-ACTOR-OF(HAS-FUNCTION)

IS-ACTOR-OF

Page 44: Formal Ontology for the improvement and integration of biomedical terminologies J. Simon* Ontology-based algorithms for error checking and semantic relationships

Functions and Processes

LIVER

ABERRANT LIVER

LIVER ACTIVITY

IS-A

HAS-ACTOR

LIVER FUNCTION

HAS-FUNCTION

IS-REALIZATION-OF

Page 45: Formal Ontology for the improvement and integration of biomedical terminologies J. Simon* Ontology-based algorithms for error checking and semantic relationships

LIVER

HAS-FUNCTION

LIVER FUNCTION

Page 46: Formal Ontology for the improvement and integration of biomedical terminologies J. Simon* Ontology-based algorithms for error checking and semantic relationships

The Need for a Systematic Top-Level

• While LinkBase currently features certain reasoning capabilities, it lacks the sort of coherent underlying structure necessary for advanced reasoning applications

• A more systematic top-level is needed

Page 47: Formal Ontology for the improvement and integration of biomedical terminologies J. Simon* Ontology-based algorithms for error checking and semantic relationships

What Does LinKBase Say About the World ?

• if a real-world entity is an instance of a domain-entity, all that is said about the domain-entity applies to the instance;

• the statement “A-Link-B” says something about all instances of A, but nothing about instances of B unless the Link is declared to have an inverse;

Page 48: Formal Ontology for the improvement and integration of biomedical terminologies J. Simon* Ontology-based algorithms for error checking and semantic relationships

The BFO Top-Level Standard

• To each concept and link there is already a space for definitions and characterization, but this is specified informally, – it is not relevant to current applications, and there are no standards governing definitions of links or concepts

• This means there is no systematic uniformity to how we understand them, and consequently their information content is much lower than it could be

Page 49: Formal Ontology for the improvement and integration of biomedical terminologies J. Simon* Ontology-based algorithms for error checking and semantic relationships

The BFO Top-Level Standard

• Define a standard protocol for definitions of concepts and links (ideally in some formal language with as concise a set of predicates as possible).

• This is a repair-the-ship-at-sea kind of project: It may be necessary to revise the links, as well as to try and be creative enough to find a logical form common to all of them

Page 50: Formal Ontology for the improvement and integration of biomedical terminologies J. Simon* Ontology-based algorithms for error checking and semantic relationships

The BFO Top-Level Standard

• An extra level of structure and coherent information will allow for the automation of processes currently run by hand

• Preliminary work already enables L&C to infer flaws in their taxonomy: links that unite categories and are missing, existing links that are misclassified

Page 51: Formal Ontology for the improvement and integration of biomedical terminologies J. Simon* Ontology-based algorithms for error checking and semantic relationships

The BFO Top-Level Standard

• The Proposed reading (in explicit logical form) of : CONCEPT A- LINK -CONCEPT B is:

• For all a in the class associated with CONCEPT A, there is a b in the class associated with CONCEPT B, such that aRb

• R is some relation expressed in the logical language of BFO or MEDo (ideally)

Page 52: Formal Ontology for the improvement and integration of biomedical terminologies J. Simon* Ontology-based algorithms for error checking and semantic relationships

The BFO Top-Level Standard

In technical terms:

For every LinKBase link: X–LINK–Y, the definition is a mapping to a п2 – complexity formula:

x (xX y (yY & xRy))

(where X and Y are variables ranging over LinKBase concepts, and R is a relation on instances in the formal language of BFO):

Page 53: Formal Ontology for the improvement and integration of biomedical terminologies J. Simon* Ontology-based algorithms for error checking and semantic relationships

The BFO Top-Level Standard

• Example:• Liver Activity – Has-Actor – Liver

• For every (actual particular process of) liver activity, A, there is some liver, B, and B is the principal participant of A.

Page 54: Formal Ontology for the improvement and integration of biomedical terminologies J. Simon* Ontology-based algorithms for error checking and semantic relationships

LARYNGOTOMY WITH REMOVAL OF TUMOR

INCISION OF LARYNX TUMOR EXCISION

IS-A INCISIONHAS-PARTICIPANT LARYNX

IS-A EXCISIONHAS-PARTICIPANT TUMOR

IS-A INCISIONIS-A EXCISIONHAS-PARTICIPANT TUMORHAS-PARTICIPANT LARYNX

IS-A IS-A

FULLY DEFINED BYFULLY DEFINED BY

FULLY DEFINED BY

IS-A INCISION OF LARYNXIS-A TUMOR EXCISION

=

Multiple Inheritance Problem

Page 55: Formal Ontology for the improvement and integration of biomedical terminologies J. Simon* Ontology-based algorithms for error checking and semantic relationships

Multiple Inheritance Problem

LARYNGOTOMY WITH REMOVAL OF TUMOR

FULLY DEFINED BY

IS-A INCISIONIS-A EXCISIONHAS-PARTICIPANT TUMORHAS-PARTICIPANT LARYNX

LARYNGECTOMY

FULLY DEFINED BY

IS-A EXCISIONHAS-PARTICIPANT LARYNX

IS-A

WRONG SUBSUMPTION!

Page 56: Formal Ontology for the improvement and integration of biomedical terminologies J. Simon* Ontology-based algorithms for error checking and semantic relationships
Page 57: Formal Ontology for the improvement and integration of biomedical terminologies J. Simon* Ontology-based algorithms for error checking and semantic relationships

What Does LinKBase Say About the World ?

• if you know that a real-world entity satisfies the Full Definition of a domain-entity-type, then you may infer that that object is an instance of that type.

Page 58: Formal Ontology for the improvement and integration of biomedical terminologies J. Simon* Ontology-based algorithms for error checking and semantic relationships

• everything that is true for a domain-entity is true for all its subsumers

Page 59: Formal Ontology for the improvement and integration of biomedical terminologies J. Simon* Ontology-based algorithms for error checking and semantic relationships

Necessary and Sufficient Criteria

REMOVAL OF LARINGEAL TUMOR

FULLY DEFINED BY

LARYNGECTOMY

FULLY DEFINED BYIS-A

WRONG SUBSUMPTION!

IS-A EXCISIONHAS-PARTICIPANT TUMORHAS-PARTICIPANT LARYNX

IS-A EXCISIONHAS-PARTICIPANT LARYNX

Page 60: Formal Ontology for the improvement and integration of biomedical terminologies J. Simon* Ontology-based algorithms for error checking and semantic relationships

Necessary and Sufficient Criteria

IS-A EXCISIONHAS-THEME TUMORHAS SOURCE LARYNX

IS-A EXCISIONHAS-THEME LARYNX

REMOVAL OF LARINGEAL TUMOR

FULLY DEFINED BY

LARYNGECTOMY

FULLY DEFINED BY

Page 61: Formal Ontology for the improvement and integration of biomedical terminologies J. Simon* Ontology-based algorithms for error checking and semantic relationships

Necessary and Sufficient Criteria

GASTRITIS

FULLY DEFINED BY

IS-A INFLAMMATORY PROCESSHAS-SYSTEMIC-MEDIUM STOMACH“AFFECTS” GASTRIC ACTIVITY

ULCERATIVE GASTRITIS

ABDOMINAL ORGAN INFLAMMATION

STOMACH

IS-A

HAS-SYSTEMIC-MEDIUM

CORRECT SUBSUMPTION NOT FOUND!

IS-A

Page 62: Formal Ontology for the improvement and integration of biomedical terminologies J. Simon* Ontology-based algorithms for error checking and semantic relationships
Page 63: Formal Ontology for the improvement and integration of biomedical terminologies J. Simon* Ontology-based algorithms for error checking and semantic relationships
Page 64: Formal Ontology for the improvement and integration of biomedical terminologies J. Simon* Ontology-based algorithms for error checking and semantic relationships

=

Page 65: Formal Ontology for the improvement and integration of biomedical terminologies J. Simon* Ontology-based algorithms for error checking and semantic relationships

BFO entities axioms: apply when LinkBase concepts are subsumed by a BFO entity.

BFO SUBSTANCESpecified by axiom: SBx <=> y(yIHx)

BODY OF ORGANISM

SUBSUMED BY

HUMAN BODY

IS-A

Axiom is then applied, what allows properties and states (temperature, shape,colour...) to inhere in the HUMAN BODY.

Implementation of BFO Axioms

Page 66: Formal Ontology for the improvement and integration of biomedical terminologies J. Simon* Ontology-based algorithms for error checking and semantic relationships

BFO formal relations axioms: apply on instances of particular Linktype mapped to BFO formal relations.

BFO formal relation PARTICIPATION Specified by axiom: xPPy => End(x) & Perd(y)

Linktype IS-ACTEE-OF

MAPS TO

INFECTED CYST INFECTIONIS-ACTEE-OF

Axiom is then applied, what allows the deduction that INFECTION is aPerdurant and consequentely has temporal parts.

Implementation of BFO Axioms

Page 67: Formal Ontology for the improvement and integration of biomedical terminologies J. Simon* Ontology-based algorithms for error checking and semantic relationships

Other examples of mapped relations

BFO formal relation FOUNDATION Linktype IS-CONSEQUENCE-OF

MAPS TO

BFO formal relation INHERENCE Linktype IS-STATE-OF-WE-OF

MAPS TO

BFO formal relation PARTICIPATION Linktype HAS-THEME

MAPS TO

Page 68: Formal Ontology for the improvement and integration of biomedical terminologies J. Simon* Ontology-based algorithms for error checking and semantic relationships

Instance level (NLP applications) X Domain ontology level (LinkBase)Applied at instance level axioms help to transform natural language text into formalsemantic representation by:

- Inferring semantic relations between instances of concepts in the ontology.- Identifying new instances of concepts not explicitily mentioned or mapped.

PERDURANT ENDURANT

SUBSUMED BY SUBSUMED BY

PARTICIPATION

ABDOMINAL CRAMP

HAS-SYSTEMIC MEDIUM

ABDOMINAL PAIN

HAS-CONSEQUENCE

“The patient complained of cramps in his abdomen.”

ABDOMENCRAMP

:: ::

::

Identified relation: HAS-SYSTEMIC-MEDIUM(mapped to PARTICIPATION)

Implementation of BFO Axioms

Page 69: Formal Ontology for the improvement and integration of biomedical terminologies J. Simon* Ontology-based algorithms for error checking and semantic relationships

Domain ontology level (LinkBase)*BFO is an “upper level” ontology formalized according to a first order language of logical entailments that work on the instance level. LinkBase, however, is a system of generalizations, or categorical relations.

*In LinkBase most linktypes, for example HAS-MATERIAL-PART, have a reverse link, IS-MATERIAL-PART-OF. We determined that the reverse links require reverse axioms in order to be maintain the generalizability governed by the 2

formula.

BFO INHERENCE Specified by axiom: xIHy => xODPy

Linktype IS-STATE-OF-WE-OF

MAPS TO

Linktype HAS-WE-STATE

CONTRA-LINK

CAPILLARY HYPERPERMEABILITY

CAPILLARYIS-STATE-OF-WE-OF

IS-O-S-DEPENDENT-ON

CAPILLARYHAS-WE-STATE

PERMEABILITY

ONE-SIDEDDEPENDENCY?NECESSITY FOR REVERSE AXIOM.

Implementation of BFO Axioms

Page 70: Formal Ontology for the improvement and integration of biomedical terminologies J. Simon* Ontology-based algorithms for error checking and semantic relationships

*The requirement of generalizability in LinkBase entails that we cannot simply reverse the terms from x <IS-STATE-OF-WE-OF> y (xIHy) to y <HAS-WE-STATE>x (yRIHx),an operation perfectly valid at the instance level. Consequently axioms cannot be reverted byreverting the variables!

Domain ontology level (LinkBase)

CAPILLARY HYPERPERMEABILITY CAPILLARY

IS-STATE-OF-WE-OF

HAS-WE-STATE Link violates the Π2 formula:Not all instances of CAPILARRYhave a hyperpermeability.

Reverse axiom xRIHy => yODPx is then incorrect!

*Our solution then, has been to introduce a set of reverse axioms through the entire chain offormal relations, till the most primitive BFO formal relation (Weak Foundation). For the example

above the correct reverse axiom is: xRIHy => xRODPy

Implementation of BFO Axioms

Page 71: Formal Ontology for the improvement and integration of biomedical terminologies J. Simon* Ontology-based algorithms for error checking and semantic relationships

Applied at domain ontology level axioms help us improve and expand the ontology by:- Inferring new relations between concepts in the ontology.- Supporting automated check for ontological errors.- Constraining the modelling space.

INFECTION OF SKIN ULCER

ULCER

SKIN

SKIN ULCER

HAS-ACTEE

HAS-ACTEE

HAS-ACTEE

IS-PROPER-MATERIAL-PART-OF

IS-A

The link HAS-ACTEE is mapped to the BFO relation PARTICIPATION which leads to Weak Foundation and its axiom:

xWFy & zy => xWFz

Axioms at the Domain Ontology Level

Page 72: Formal Ontology for the improvement and integration of biomedical terminologies J. Simon* Ontology-based algorithms for error checking and semantic relationships

Supporting automated check for ontological errors & Constraining the modelling space

OESOPHAGUS BYPASS BYPASS OF OESOPHAGUS

BYPASS SURGERY

PERDURANTENDURANT

IS-A

IS-A

IS-A

IS-A

SURGICALLY ALTERED STRUCTURE

REMOVAL OF BYPASS OF OESOPHAGUS

HAS-THEME HAS-THEME

The link HAS-THEME is mapped to the reverse BFO relation PARTICIPATION,defined by the axiom:xRPPy => Perd(x) & End(y)

Link is not allowed becauseaccording to the axiom the target congept must be an Endurant!

Axioms at the Domain Ontology Level

Page 73: Formal Ontology for the improvement and integration of biomedical terminologies J. Simon* Ontology-based algorithms for error checking and semantic relationships

Conclusions

• Our collaboration still in its infancy• Already, philosophically inspired

changes have led to greater internal consistency of LinKBase, and aided its capacity to integrate diverse ontology and terminology systems

Page 74: Formal Ontology for the improvement and integration of biomedical terminologies J. Simon* Ontology-based algorithms for error checking and semantic relationships

Conclusions

• Integration and efficiency problems arise from ad hoc solutions to constraints on database and algorithm design.

• Ad hoc solutions solve local problems, but generate further ones later on

Page 75: Formal Ontology for the improvement and integration of biomedical terminologies J. Simon* Ontology-based algorithms for error checking and semantic relationships

Conclusions

• The project of philosophical ontology is to achieve natural, elegant and accurate organizational partitions of reality

• By heeding its lessons, we may design comprehensive applications ontologies without feet of clay, that are able to tackle global integration and efficiency problems.

Page 76: Formal Ontology for the improvement and integration of biomedical terminologies J. Simon* Ontology-based algorithms for error checking and semantic relationships

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