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ECOR European Centre for Ontological Research Realist Ontology for the Semantic Web: Applications in Biomedical Informatics Werner Ceusters European Centre for Ontological Research Universität des Saarlandes Saarbrücken, Germany

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Page 1: ECO R European Centre for Ontological Research Realist Ontology for the Semantic Web: Applications in Biomedical Informatics Werner Ceusters European Centre

ECOREuropean Centre forOntological Research

Realist Ontology for the Semantic Web: Applications in

Biomedical Informatics

Werner CeustersEuropean Centre for Ontological Research

Universität des Saarlandes

Saarbrücken, Germany

Page 2: ECO R European Centre for Ontological Research Realist Ontology for the Semantic Web: Applications in Biomedical Informatics Werner Ceusters European Centre

ECOREuropean Centre forOntological Research

Lecture overview

• Credentials• The many faces of “ontology”• Realist ontology• Why is the concept-based approach so wide-

spread ?• The price you pay if you go for concepts ...• Can Description Logics save the world ?• And then there was OWL• Take home messages

Page 3: ECO R European Centre for Ontological Research Realist Ontology for the Semantic Web: Applications in Biomedical Informatics Werner Ceusters European Centre

ECOREuropean Centre forOntological Research

European Centre forOntological Research

Local members

Externalmembers

Partners

Status Dec 2, 2004

Page 4: ECO R European Centre for Ontological Research Realist Ontology for the Semantic Web: Applications in Biomedical Informatics Werner Ceusters European Centre

ECOREuropean Centre forOntological Research

European Centre forOntological Research

Directors Member representatives

AdvisoryBoard

Management Board

Status Dec 2, 2004

Page 5: ECO R European Centre for Ontological Research Realist Ontology for the Semantic Web: Applications in Biomedical Informatics Werner Ceusters European Centre

ECOREuropean Centre forOntological Research

Institute for Formal Ontologyand Medical Information Science

• an interdisciplinary research group – Philosophy, – Computer and Information Science, – Logic, – Medicine, – Medical Informatics.

• a center of theoretically grounded research in both formal and applied ontology.

• Main goal: to develop a formal ontology that will be applied and tested in the domain of medical and biomedical information science.

Page 6: ECO R European Centre for Ontological Research Realist Ontology for the Semantic Web: Applications in Biomedical Informatics Werner Ceusters European Centre

ECOREuropean Centre forOntological Research

IFOMIS competences•Logics X X X

•Informatics X X

•Spatio-temporal reasoning X

•Medicine X X X

•Knowledge engineering X

•Formal Ontology / metaphysics X X X X X

•Mathematics X X

•Qualitative spatial reasoning X X

•Ontological engineering X X

•History of philosophy X

•Philosophy of science X

•Linguistics X

Status Dec 2, 2004

•Formal Ontology / metaphysics

•Logics

•History of philosophy•Philosophy of science

Page 7: ECO R European Centre for Ontological Research Realist Ontology for the Semantic Web: Applications in Biomedical Informatics Werner Ceusters European Centre

ECOREuropean Centre forOntological Research

Our building

Page 8: ECO R European Centre for Ontological Research Realist Ontology for the Semantic Web: Applications in Biomedical Informatics Werner Ceusters European Centre

ECOREuropean Centre forOntological Research

What philosophers are good for...

Page 9: ECO R European Centre for Ontological Research Realist Ontology for the Semantic Web: Applications in Biomedical Informatics Werner Ceusters European Centre

ECOREuropean Centre forOntological Research

Short personal history

1959 - ...1977

1989

1992

1998

2002

2004

Page 10: ECO R European Centre for Ontological Research Realist Ontology for the Semantic Web: Applications in Biomedical Informatics Werner Ceusters European Centre

ECOREuropean Centre forOntological Research

“Ontology”

Page 11: ECO R European Centre for Ontological Research Realist Ontology for the Semantic Web: Applications in Biomedical Informatics Werner Ceusters European Centre

ECOREuropean Centre forOntological Research

WordNet 2.0 - 2003

Page 12: ECO R European Centre for Ontological Research Realist Ontology for the Semantic Web: Applications in Biomedical Informatics Werner Ceusters European Centre

ECOREuropean Centre forOntological Research

“Ontology” on the web

Status Nov 29, 2004

The most cited definition: Tom

Grüber 1993

Inactive since August 7, 2004.

W3C Web Ontology initiative

Ontology from a philosophical perspective.

Important bioinformatics

resource

Realist ontology in use.

Barry Smith

Popular ontology editor from Manchester

SUO Upper Ontology Initiative

John Sowa’s ontology page

Page 13: ECO R European Centre for Ontological Research Realist Ontology for the Semantic Web: Applications in Biomedical Informatics Werner Ceusters European Centre

ECOREuropean Centre forOntological Research

New search on Nov 30:

10.000 results more

• 1 What is an Ontology?• 3 Gene Ontology Consortium• 4 W3C Web Ontology (WebOnt) Working Group (OWL) (Closed)• 7 Buffalo Ontology Site• 15 MGED NETWORK :: Ontology Working Group (OWG)• 20 Laboratory for Applied Ontology (LOA)• 21 ONTOLOGY WORKS INC.• 34 John Bateman; ontology portal root• 53 The Protégé Ontology Editor and Knowledge Acquisition System• 59 Institute for Formal Ontology and Medical Information Science ...• 86 Autofellatio and Ontology• 188 EUROREC 2004, Implemantation Guidelines, ...• 192 Foundational Ontology (Leeds)• 676 Ontology Server research (StarLab)

?????

Page 14: ECO R European Centre for Ontological Research Realist Ontology for the Semantic Web: Applications in Biomedical Informatics Werner Ceusters European Centre

ECOREuropean Centre forOntological Research

If, later, you can remember just one thing of this presentation, then make

sure it is this one:

If you use the word “ontology”, ALWAYS

be specific about what you mean by it.

Page 15: ECO R European Centre for Ontological Research Realist Ontology for the Semantic Web: Applications in Biomedical Informatics Werner Ceusters European Centre

ECOREuropean Centre forOntological Research

Tom Gruber’s view

• In the context of knowledge sharing, I use the term ontology to mean a specification of a conceptualization. That is, an ontology is a description (like a formal specification of a program) of the concepts and relationships that can exist for an agent or a community of agents. This definition is consistent with the usage of ontology as set-of-concept-definitions, but more general. And it is certainly a different sense of the word than its use in philosophy.

• An ontology is a specification of a conceptualization.

• The word "ontology" seems to generate a lot of controversy in discussions about AI. It has a long history in philosophy, in which it refers to the subject of existence. It is also often confused with epistemology, which is about knowledge and knowing.

Page 16: ECO R European Centre for Ontological Research Realist Ontology for the Semantic Web: Applications in Biomedical Informatics Werner Ceusters European Centre

ECOREuropean Centre forOntological Research The O-word in science

N. Guarino, P. Giaretta, "Ontologies and Knowledge Bases: Towards a Terminological Clarification". In Towards Very Large Knowledge Bases: Knowledge Building and Knowledge Sharing, N. Mars (ed.), pp 25-32. IOS Press, Amsterdam, 1995.

Page 17: ECO R European Centre for Ontological Research Realist Ontology for the Semantic Web: Applications in Biomedical Informatics Werner Ceusters European Centre

ECOREuropean Centre forOntological Research The O-word in buzz-speak

• “An ontology is a classification methodology for formalizing a subject's knowledge or belief system in a structured way. Dictionaries and encyclopedias are examples of ontologies.”

(X1)

• “A terminology (or classification) is a kind of ontology by definition and it should preserve (and "understand") the relationships between the 1,000s of terms in it or else it would become a mere dictionary (or at best a thesaurus).”

(X2)

• “Ontologies are Web pages that contain a mystical unifying force that gives differing labels common meaning.”

(X3)

Page 18: ECO R European Centre for Ontological Research Realist Ontology for the Semantic Web: Applications in Biomedical Informatics Werner Ceusters European Centre

ECOREuropean Centre forOntological Research

“Ontology”

An ontology defines the terms used to describe and represent an area of knowledge, and are used by people, databases, and applications that need to share domain information (a domain is a specific subject area, such as health or medicine).

OWL Web Ontology Language; Use Cases and RequirementsW3C Recommendation 10 February 2004

http://www.w3.org/TR/webont-req/

e-Health - making healthcare better for European citizens: An action plan for a European e-Health Area

COM (2004) 356 final, 30.4.2004, p17

Page 19: ECO R European Centre for Ontological Research Realist Ontology for the Semantic Web: Applications in Biomedical Informatics Werner Ceusters European Centre

ECOREuropean Centre forOntological Research

• Ontologies need to specify descriptions for the following kinds of concepts:– Classes (general things) in the many domains

of interest – The relationships that can exist among things – The properties (or attributes) those things may

have

OWL Web Ontology Language; Use Cases and RequirementsW3C Recommendation 10 February 2004

http://www.w3.org/TR/webont-req/

“Ontology”

Page 20: ECO R European Centre for Ontological Research Realist Ontology for the Semantic Web: Applications in Biomedical Informatics Werner Ceusters European Centre

ECOREuropean Centre forOntological Research

Realist Ontology

Page 21: ECO R European Centre for Ontological Research Realist Ontology for the Semantic Web: Applications in Biomedical Informatics Werner Ceusters European Centre

ECOREuropean Centre forOntological Research

A visit to the operating theatre

Haydom Lutheran Hospital, Tanzania

This surgeon

This amputation stump

A lot ofobjects present

This mask

This hand

with some relations

Part of

Page 22: ECO R European Centre for Ontological Research Realist Ontology for the Semantic Web: Applications in Biomedical Informatics Werner Ceusters European Centre

ECOREuropean Centre forOntological Research

Haydom Lutheran Hospital, Tanzania

This wound being closed by holding ...

That wound fluid

drained

A lot ofprocesses going on

This kocher being held in that hand of that surgeon

with some relations

Part of

A visit to the operating theatre

Page 23: ECO R European Centre for Ontological Research Realist Ontology for the Semantic Web: Applications in Biomedical Informatics Werner Ceusters European Centre

ECOREuropean Centre forOntological Research “Axiom” 1

• If the picture is not a fake, we (i.e., me and this audience) KNOW that that hand, that surgeon, ... EXIST(ed), i.e. ARE (were) REAL.

• But importantly: that hand, surgeon, kocher, mask, ... EXIST(ed) independent of our knowledge about them and also the part-relationship between that hand and that surgeon, and the processes going on, are (were) equally real.

epistemology

ontology

Page 24: ECO R European Centre for Ontological Research Realist Ontology for the Semantic Web: Applications in Biomedical Informatics Werner Ceusters European Centre

ECOREuropean Centre forOntological Research

The realist ontological square (Ignacio Angelelli)

Substance Particulars Quality Particulars

SubstanceUniversals

QualityUniversals

instance instance

differentia

exemplify

inheres

Page 25: ECO R European Centre for Ontological Research Realist Ontology for the Semantic Web: Applications in Biomedical Informatics Werner Ceusters European Centre

ECOREuropean Centre forOntological Research

How to differentiatequalities from substances ?

• Language may fool us:– Being pale– Being human– Being a person– Being sick

• Can all be properties of particulars, namely me and you !

But so does logic:– Pale(x)– Human(x)– Person(x)– Sick(x)

Page 26: ECO R European Centre for Ontological Research Realist Ontology for the Semantic Web: Applications in Biomedical Informatics Werner Ceusters European Centre

ECOREuropean Centre forOntological Research

“Realist ontology”

• describes what is fundamental in the totality of what exists,

• defines the most general categories to which we need to refer in constructing a description of reality,

• tells us how these categories are related.

• is able to be used to describe reality at any point in time.

Page 27: ECO R European Centre for Ontological Research Realist Ontology for the Semantic Web: Applications in Biomedical Informatics Werner Ceusters European Centre

ECOREuropean Centre forOntological Research

Basic Ontological Notions

• Identity– How are particulars distinguished from each

other ?

• Unity– How are all the parts of a particular isolated ?

• Essence– Can a property change over time ?

• Dependence– Can an entity exist without some others ?

Page 28: ECO R European Centre for Ontological Research Realist Ontology for the Semantic Web: Applications in Biomedical Informatics Werner Ceusters European Centre

ECOREuropean Centre forOntological Research Identity & instanciation

child adult

caterpillar butterfly

t

person

animal

Livingcreature

Page 29: ECO R European Centre for Ontological Research Realist Ontology for the Semantic Web: Applications in Biomedical Informatics Werner Ceusters European Centre

ECOREuropean Centre forOntological Research

• +I The property carries a common identity criterion for all its instances.

• −I The property does not carry a common identity criterion for all its instances.

• +U The property carries a common unity criterion for all its instances.

• −U The property does not carry a common unity criterion for all its instances.

• U No instance of the property satisfies a unity criterion.

• +R The property is essential to all its instances: an instance of a rigid property cannot stop satisfying that property.

• −R The property is not essential to all its instances: some instances of a non rigid property can stop satisfying that property.

• R No instance of the property has it essentially: all instances of the property can stop satisfying it.

A practical example: OntoClean

Guarino & Welty

Page 30: ECO R European Centre for Ontological Research Realist Ontology for the Semantic Web: Applications in Biomedical Informatics Werner Ceusters European Centre

ECOREuropean Centre forOntological Research

Ontological theories

• = theories between reality and “the ontology” (“ontology” as a representation)

– Granular Partition Theory (T Bittner & B. Smith)

– Logic of Classes (B. Smith)

– Foundational relations

Page 31: ECO R European Centre for Ontological Research Realist Ontology for the Semantic Web: Applications in Biomedical Informatics Werner Ceusters European Centre

ECOREuropean Centre forOntological Research

Theory of granular partitions (B. Smith)

Think of it as Alberti’s grid

Page 32: ECO R European Centre for Ontological Research Realist Ontology for the Semantic Web: Applications in Biomedical Informatics Werner Ceusters European Centre

ECOREuropean Centre forOntological Research

Granular partitions: main principles

• a partition is the drawing of a (typically complex) fiat boundary over a certain domain

• a partition typically comes with labels and/or an address system

• partitions are artefacts of our cognition• a partition is transparent (veridical)• bona fide objects exist independently of our

partitions, fiat objects are determined by partitions• different partitions may represent cuts through the

same reality which are skew to each other• entities (existing in reality) located in the same cell

of a partition share common characteristics

Page 33: ECO R European Centre for Ontological Research Realist Ontology for the Semantic Web: Applications in Biomedical Informatics Werner Ceusters European Centre

ECOREuropean Centre forOntological Research (Simplified) Logic of classes

• primitive: – entities: particulars versus universals– relation inst such that:

• all classes are universals; all instances are particulars

• some particulars are not instances; e.g. some mereological sums

• subsumption defined resorting to instances:

Page 34: ECO R European Centre for Ontological Research Realist Ontology for the Semantic Web: Applications in Biomedical Informatics Werner Ceusters European Centre

ECOREuropean Centre forOntological Research

Reference Ontology

• a theory of a domain of entities in the world

• based on realizing the goals of maximal expressiveness and adequacy to reality

• sacrificing computational tractability for the sake of representational adequacy

Page 35: ECO R European Centre for Ontological Research Realist Ontology for the Semantic Web: Applications in Biomedical Informatics Werner Ceusters European Centre

ECOREuropean Centre forOntological Research Basic Formal Ontology

Basic Formal Ontology consists in a series of sub-ontologies (most properly conceived as a series of perspectives on reality), the most important of which are: – SnapBFO, a series of snapshot ontologies (Oti ),

indexed by times: continuants– SpanBFO a single videoscopic ontology (Ov):

occurants.

Each Oti is an inventory of all entities existing at a time. Ov is an inventory (processory) of all processes unfolding through time.

Page 36: ECO R European Centre for Ontological Research Realist Ontology for the Semantic Web: Applications in Biomedical Informatics Werner Ceusters European Centre

ECOREuropean Centre forOntological Research

Occurants and continuants

Picture by Vladimir Brajic

Page 37: ECO R European Centre for Ontological Research Realist Ontology for the Semantic Web: Applications in Biomedical Informatics Werner Ceusters European Centre

ECOREuropean Centre forOntological Research

Page 38: ECO R European Centre for Ontological Research Realist Ontology for the Semantic Web: Applications in Biomedical Informatics Werner Ceusters European Centre

ECOREuropean Centre forOntological Research

SpanBFO

Page 39: ECO R European Centre for Ontological Research Realist Ontology for the Semantic Web: Applications in Biomedical Informatics Werner Ceusters European Centre

ECOREuropean Centre forOntological Research

• a for a computer understable representation of some pre-existing domain of REALITY, reflecting the properties of the objects within its domain in such a way that there obtain substantial and systematic correlations between reality and the ontology itself.

“A” Realist Ontology

to be used by software (agents) in

a machine, and NOT by humans

• does not rely on what people know or think, hence no “concepts”

• instance driven, although it accepts universals that are not instanciated

• does not “create” or “constrain” reality

The T-Box has no meaning without

the A-Box

Page 40: ECO R European Centre for Ontological Research Realist Ontology for the Semantic Web: Applications in Biomedical Informatics Werner Ceusters European Centre

ECOREuropean Centre forOntological Research

Why is the concept-basedapproach so wide-spread ?

Page 41: ECO R European Centre for Ontological Research Realist Ontology for the Semantic Web: Applications in Biomedical Informatics Werner Ceusters European Centre

ECOREuropean Centre forOntological Research Back to the operating theatre

Haydom Lutheran Hospital, Tanzania

I must get rid of that

blood

Suction, please !

He wants me to

remove that blood

Fluid being removed

Page 42: ECO R European Centre for Ontological Research Realist Ontology for the Semantic Web: Applications in Biomedical Informatics Werner Ceusters European Centre

ECOREuropean Centre forOntological Research

= ?

This is communication !

kocher Give me a kocher, please.

Page 43: ECO R European Centre for Ontological Research Realist Ontology for the Semantic Web: Applications in Biomedical Informatics Werner Ceusters European Centre

ECOREuropean Centre forOntological Research

Triadic models of meaning: The Semiotic/Semantic triangle

Sign:Language/

Term/Symbol

Referent:Reality/Object

Reference: Concept / Sense / Model / View / Partition

Page 44: ECO R European Centre for Ontological Research Realist Ontology for the Semantic Web: Applications in Biomedical Informatics Werner Ceusters European Centre

ECOREuropean Centre forOntological Research Aristotle’s triadic meaning

model

semeia

gramma/ phoné pragma

pathemaWords spoken are signs or symbols (symbola) of affections or impressions (pathemata) of the soul (psyche); written words (graphomena) are the signs of words spoken (phoné). As writing (grammatta), so also is speech not the same for all races of men. But the mental affections themselves, of which these words are primarily signs (semeia), are the same for the whole of mankind, as are also the objects (pragmata) of which those affections are representations or likenesses, images, copies (homoiomata).

Aristotle, 'On Interpretation', 1.16.a.4-9, Translated by Cooke & Tredennick,

Loeb Classical Library, William Heinemann, London, UK, 1938.

Page 45: ECO R European Centre for Ontological Research Realist Ontology for the Semantic Web: Applications in Biomedical Informatics Werner Ceusters European Centre

ECOREuropean Centre forOntological Research An interesting sidestep:

“understanding”• “understanding” Latin “substare”

– literally: “to stand under”• Websters Dictionary (1961) understanding = the power to render

experience intelligible by bringing perceived particulars under appropriate concepts.

• “particulars” = what is NOT SAID of a subject (Aristotle)– substances: this patient, that tumor, ...– qualities: the red of that patient’s skin, his body temperature,

blood pressure, ...– processes: that incision made by that surgeon, the rise of that

patient’s temperature,...• “concepts”: may be taken in the above definition as Aristotle’s

“universals” = what is SAID OF a subject– Substantial concepts: patient, tumor, ...– Quality concepts: white, temperature– ...

Page 46: ECO R European Centre for Ontological Research Realist Ontology for the Semantic Web: Applications in Biomedical Informatics Werner Ceusters European Centre

ECOREuropean Centre forOntological Research Richards’ semantic triangle

• Reference (“concept”): “indicates the realm of memory where recollections of past experiences and contexts occur”.

• Hence: as with Aristotle, the reference is “mind-related”: thought.

• But: not “the same for all”, rather individual mind-related

symbol referent

referenceunderstandingmy your understanding

Page 47: ECO R European Centre for Ontological Research Realist Ontology for the Semantic Web: Applications in Biomedical Informatics Werner Ceusters European Centre

ECOREuropean Centre forOntological Research

Don’t confuse with homonymy !

“mole” mole (animal)

R1

mole (unit)

R2

mole (skin lesion)

R3

Page 48: ECO R European Centre for Ontological Research Realist Ontology for the Semantic Web: Applications in Biomedical Informatics Werner Ceusters European Centre

ECOREuropean Centre forOntological Research

Different thoughts Homonymy

“mole” mole “animal”

R1

mole “unit”

R2

mole“skin lesion”

R3

symbol referent

understanding

One conceptof x understanding of y

Page 49: ECO R European Centre for Ontological Research Realist Ontology for the Semantic Web: Applications in Biomedical Informatics Werner Ceusters European Centre

ECOREuropean Centre forOntological Research

And by the way, synonymy...

the Aristotelian view Richards’ view

“perspiration”

“sweat”“sweat”

“perspiration”

Page 50: ECO R European Centre for Ontological Research Realist Ontology for the Semantic Web: Applications in Biomedical Informatics Werner Ceusters European Centre

ECOREuropean Centre forOntological Research Frege’s view

• “sense” is an objective feature of how words are used and not a thought or concept in somebody’s head

• 2 names with the same reference can have different senses (mst/ist)

• 2 names with the same sense have the same reference (synonyms)

• a name with a sense does not need to have a reference (“Beethoven’s 10th symphony”)

reference(=referent)

sense

name

Page 51: ECO R European Centre for Ontological Research Realist Ontology for the Semantic Web: Applications in Biomedical Informatics Werner Ceusters European Centre

ECOREuropean Centre forOntological Research

Ontology and the semantic triangle• In Information Science:

– “An ontology is a description (like a formal specification of a program) of the concepts and relationships that can exist for an agent or a community of agents.”

• In Philosophy:– “Ontology is the science of

what is, of the kinds and structures of objects, properties, events, processes and relations in every area of reality.”

concept

term referent

Page 52: ECO R European Centre for Ontological Research Realist Ontology for the Semantic Web: Applications in Biomedical Informatics Werner Ceusters European Centre

ECOREuropean Centre forOntological Research

Current “state of the art” onmeaning in biomedical informatics

• A pervasive bias towards “concepts”– Content wise:

• Work based on ISO/TC37 that advocates the Ogden-Richards theory of meaning

• Corresponds with a linguistic reading of “concept”

– Architecture wise: • In Europe: work based on CEN/TC251 WG1 & WG2

that follow ISO/TC37• In the US: HL7, inspired by Speech Act Theory• “Concepts” used as elements of information models,

hence mixing a linguistic and engineering reading.

Page 53: ECO R European Centre for Ontological Research Realist Ontology for the Semantic Web: Applications in Biomedical Informatics Werner Ceusters European Centre

ECOREuropean Centre forOntological Research Before the introduction of

“concepts”, it was even worse ...

Characteristics of an ideal medical knowledge system• a unique code for each term (word, phrase) • each code-term being defined• each term independent, not defined as the result of other

terms in the system • synonyms recognisable through the codes• to each codes could be attached codes of related terms • the system would encompass all of medicine• the system would be in the public domain• the format of the KB should be functionally described,

independent from hard- or software(C. Bishop, 1989)

Page 54: ECO R European Centre for Ontological Research Realist Ontology for the Semantic Web: Applications in Biomedical Informatics Werner Ceusters European Centre

ECOREuropean Centre forOntological Research

With “concepts”, it became:

Characteristics of an ideal medical knowledge system• a unique code for each term (word, phrase) and concept

• each code-term concept being defined• each term concept independent, not defined as the result

of other terms in the system ???

• synonyms recognisable through the codes concepts • to each code concept could be attached codes concepts of

related terms • the system would encompass all of medicine• the system would be in the public domain• the format of the KB should be functionally described,

independent from hard- or software

Page 55: ECO R European Centre for Ontological Research Realist Ontology for the Semantic Web: Applications in Biomedical Informatics Werner Ceusters European Centre

ECOREuropean Centre forOntological Research Requirements for clinical

vocabularies (1)• Domain completeness: coverage of all

possible terms that lie within a vocabulary’s domain

• Non-vagueness: the term should represent the concept behind it as close as possible

• Non-ambiguity: the same term cannot refer to more than one concept

• Non-redundancy: each concept must be represented by one unique identifier

(Cimino, 1989)

Page 56: ECO R European Centre for Ontological Research Realist Ontology for the Semantic Web: Applications in Biomedical Informatics Werner Ceusters European Centre

ECOREuropean Centre forOntological Research Requirements for clinical

vocabularies (2)

• Synonomy: multiple ways for expressing a word (or concept) must be allowed

• Multiple classification: concepts must be allowed to be classified in multiple hierarchies

• Consistency of view: concepts must have the same relationships in all views

• Explicit relationships: all relationships (e.g. class, synonymy,…) must be explicitly labelled.

Page 57: ECO R European Centre for Ontological Research Realist Ontology for the Semantic Web: Applications in Biomedical Informatics Werner Ceusters European Centre

ECOREuropean Centre forOntological Research

The price you pay if you gofor concepts ...

Page 58: ECO R European Centre for Ontological Research Realist Ontology for the Semantic Web: Applications in Biomedical Informatics Werner Ceusters European Centre

ECOREuropean Centre forOntological Research

Border’s classification of medicine

• Medicine– Mental health– Internal medicine

• Endocrinology–Oversized endocrinology

• Gastro-enterology• ...

– Pediatrics– ...– Oversized medicine

Page 59: ECO R European Centre for Ontological Research Realist Ontology for the Semantic Web: Applications in Biomedical Informatics Werner Ceusters European Centre

ECOREuropean Centre forOntological Research MeSH:

Medical Subject Headings

• Designed for bibliographic indexing, eg Index Medicus

• Basis for MedLINE• focuses on biomedicine and other basic

healthcare sciences• clinically very impoverished• Consistency amongst indexers:

– 60% for headings– 30% for sub-headings

Page 60: ECO R European Centre for Ontological Research Realist Ontology for the Semantic Web: Applications in Biomedical Informatics Werner Ceusters European Centre

ECOREuropean Centre forOntological Research

MeSH Tree Structures - 20041.  Anatomy [A] 2.  Organisms [B] 3.  Diseases [C] 4.  Chemicals and Drugs [D] 5.  Analytical, Diagnostic and Therapeutic Techniques and Equipment [E] 6.  Psychiatry and Psychology [F] 7.  Biological Sciences [G] 8.  Physical Sciences [H] 9.  Anthropology, Education, Sociology and Social Phenomena [I] 10.  Technology and Food and Beverages [J] 11.  Humanities [K] 12.  Information Science [L] 13.  Persons [M] 14.  Health Care [N] 15. Geographic Locations [Z]

What about this as a top ontology ???

Page 61: ECO R European Centre for Ontological Research Realist Ontology for the Semantic Web: Applications in Biomedical Informatics Werner Ceusters European Centre

ECOREuropean Centre forOntological Research

• Cardiovascular Diseases [C14] – Heart Diseases [C14.280]

• Arrhythmia [C14.280.067] + • Carcinoid Heart Disease [C14.280.129] • Cardiomegaly [C14.280.195] + • Endocarditis [C14.280.282] + • Heart Aneurysm [C14.280.358] • Heart Arrest [C14.280.383] + • Heart Defects, Congenital [C14.280.400]

– Aortic Coarctation [C14.280.400.090] – Arrhythmogenic Right Ventricular Dysplasia [C14.280.400.145] – Cor Triatriatum [C14.280.400.200] – Coronary Vessel Anomalies [C14.280.400.210] – Crisscross Heart [C14.280.400.220] – Dextrocardia [C14.280.400.280] +

MeSH Tree Structures - 2004

Page 62: ECO R European Centre for Ontological Research Realist Ontology for the Semantic Web: Applications in Biomedical Informatics Werner Ceusters European Centre

ECOREuropean Centre forOntological Research

• Body Regions [A01] – Extremities [A01.378]

• Lower Extremity [A01.378.610] – Buttocks [A01.378.610.100] – Foot [A01.378.610.250]

» Ankle [A01.378.610.250.149] » Forefoot, Human [A01.378.610.250.300] + » Heel [A01.378.610.250.510]

– Hip [A01.378.610.400] – Knee [A01.378.610.450] – Leg [A01.378.610.500] – Thigh [A01.378.610.750]

MeSH Tree Structures - 2004

The most abundantsort of mistakes !

Page 63: ECO R European Centre for Ontological Research Realist Ontology for the Semantic Web: Applications in Biomedical Informatics Werner Ceusters European Centre

ECOREuropean Centre forOntological Research

• Body Regions [A01] – Abdomen [A01.047] + – Back [A01.176] + – Breast [A01.236] + – Extremities [A01.378]

• Amputation Stumps [A01.378.100] • Lower Extremity [A01.378.610] + • Upper Extremity [A01.378.800] +

– Head [A01.456] + – Neck [A01.598] – Pelvis [A01.673] + – Perineum [A01.719] – Thorax [A01.911] + – Viscera [A01.960]

MeSH Tree Structures - 2004

And here ?

Page 64: ECO R European Centre for Ontological Research Realist Ontology for the Semantic Web: Applications in Biomedical Informatics Werner Ceusters European Centre

ECOREuropean Centre forOntological Research SNOMED International (1995)

• Multi-axial coding system: – morphology, disease, function, procedure, ...

• Each axis has an hierarchical structure• Translations in other languages than English only for

older versions• Informal internal structuring • Being translated in CG formalism, but with only

internal consistency • Possibility to generate meaningless concepts• Mixing of hierarchies:

– Bone• Long Bone• Periosteum• Shaft

Page 65: ECO R European Centre for Ontological Research Realist Ontology for the Semantic Web: Applications in Biomedical Informatics Werner Ceusters European Centre

ECOREuropean Centre forOntological Research Snomed International (1995)

Number of records (V3.1)• T Topography 12,385• M Morphology 4,991• F Function 16,352• L Living Organisms 24,265• C Drugs &Biological Products 14,075• A Physical Agents, Forces and Activities 1,355• D Disease/ Diagnosis 28,623• P Procedures 27,033• S Social Context 433• J Occupations 1,886• G General Modifiers 1,176• TOTAL RECORDS 132,641

Page 66: ECO R European Centre for Ontological Research Realist Ontology for the Semantic Web: Applications in Biomedical Informatics Werner Ceusters European Centre

ECOREuropean Centre forOntological Research Snomed International (1995):

knowledge in the codes.

posterior anatomic leaflet

mitral cardiac valve

cardiovascular

T - 23 5 3 2

Why was this not a good idea ?

Page 67: ECO R European Centre for Ontological Research Realist Ontology for the Semantic Web: Applications in Biomedical Informatics Werner Ceusters European Centre

ECOREuropean Centre forOntological Research Snomed International :

multiple ways to express the same thing

D5-46210 Acute appendicitis, NOS

D5-46100 Appendicitis, NOS

G-A231 Acute

M-41000 Acute inflammation, NOS

G-C006 In

T-59200 Appendix, NOS

G-A231 Acute

M-40000 Inflammation, NOS

G-C006 In

T-59200 Appendix, NOS

Page 68: ECO R European Centre for Ontological Research Realist Ontology for the Semantic Web: Applications in Biomedical Informatics Werner Ceusters European Centre

ECOREuropean Centre forOntological Research The International

Classification of diseases (WHO).• ...

• Chapter II: Neoplasms (C00-D48)• Chapter III: Diseases of the Blood and Blood-forming organs and

certain disorders involving the immune mechanism (D50-D89)• Excludes : auto-immune disease (systemic) NOS (M35.9)• ....• Nutritional Anemias (D50-D53)• D50 Iron deficiency anaemia• Includes: ...• D50.0 Iron deficiency anaemia secondary to blood loss (chronic)• Excludes : ...• D50.1 ...• D51 Vit B12 deficiency anaemia• Haemolytic Anemias (D55-D59) • ...• Chapter IV: ...

Page 69: ECO R European Centre for Ontological Research Realist Ontology for the Semantic Web: Applications in Biomedical Informatics Werner Ceusters European Centre

ECOREuropean Centre forOntological Research UMLS: Unified Medical

Language System (NLM)• Tool for information retrieval of 4 components:

– Metathesaurus contains information about biomedical concepts and how they are represented in diverse terminological systems.

– Semantic Network contains information about concept categories and the permissible relationships among them

– Information Sources Map contains both human-readable and machine-processable information about all kinds of biomedical terminological systems

– Specialist lexicon: english words with POS

• “The” tool from and for the U.S. :-)

Page 70: ECO R European Centre for Ontological Research Realist Ontology for the Semantic Web: Applications in Biomedical Informatics Werner Ceusters European Centre

ECOREuropean Centre forOntological Research

UMLS Semantic Network

Page 71: ECO R European Centre for Ontological Research Realist Ontology for the Semantic Web: Applications in Biomedical Informatics Werner Ceusters European Centre

ECOREuropean Centre forOntological Research Semantic Network

Relationships• Is_a

• physically related to

• spatially related to

• temporally related to

• functionally related to

• conceptually related to

Page 72: ECO R European Centre for Ontological Research Realist Ontology for the Semantic Web: Applications in Biomedical Informatics Werner Ceusters European Centre

ECOREuropean Centre forOntological Research Semantic Network “Biologic

Function” Hierarchy

Page 73: ECO R European Centre for Ontological Research Realist Ontology for the Semantic Web: Applications in Biomedical Informatics Werner Ceusters European Centre

ECOREuropean Centre forOntological Research

Semantic Network "affects" Hierarchy 

Page 74: ECO R European Centre for Ontological Research Realist Ontology for the Semantic Web: Applications in Biomedical Informatics Werner Ceusters European Centre

ECOREuropean Centre forOntological Research

“Axiom” 2

• Concept-based terminology (and standardisation thereof) is there as a mechanism to improve understanding of messages by humans.

• It is NOT the right device – to explain why reality is what it is, how it is organised,

etc., (although it is needed to allow communication), – to reason about reality, – to make machines understand what is real,– to integrate across different views, languages,

conceptualisations, ...

Page 75: ECO R European Centre for Ontological Research Realist Ontology for the Semantic Web: Applications in Biomedical Informatics Werner Ceusters European Centre

ECOREuropean Centre forOntological Research

Why not ?• Does not take care of universals and particulars

appropriately• Concepts not necessarily correspond to

something that (will) exist(ed)– Sorcerer, unicorn, leprechaun, ...

• Definitions set the conditions under which terms may be used, and may not be abused as conditions an entity must satisfy to be what it is

• Language can make strings of words look as if it were terms– “Middle lobe of left lung”

• ...

Page 76: ECO R European Centre for Ontological Research Realist Ontology for the Semantic Web: Applications in Biomedical Informatics Werner Ceusters European Centre

ECOREuropean Centre forOntological Research

Ok, then Description Logicswill save us ... ?

Page 77: ECO R European Centre for Ontological Research Realist Ontology for the Semantic Web: Applications in Biomedical Informatics Werner Ceusters European Centre

ECOREuropean Centre forOntological Research

Description Logics• A decidable fragment of FOL• A propositional modal logic• A classes and properties (concepts and

roles) oriented KR language• Subsumption and satisfiability (consistency)

are the key inferences• Most DLs are supersets of ALC

– Boolean operators on concepts– Existential and Universal quantifiers

• OWL-DL is a large superset (SHOIN):– Property hierarchies & Transitive roles (SH)– Inverse (I)– Nominals (O) (hasValue and one of)– Number restrictions (counting quantifiers)

Page 78: ECO R European Centre for Ontological Research Realist Ontology for the Semantic Web: Applications in Biomedical Informatics Werner Ceusters European Centre

ECOREuropean Centre forOntological Research

Snomed and DL

SNOMED-RT (2000)

SNOMED-CT (2003)

DL don’t guarantee you to get parthood right !

Page 79: ECO R European Centre for Ontological Research Realist Ontology for the Semantic Web: Applications in Biomedical Informatics Werner Ceusters European Centre

ECOREuropean Centre forOntological Research Use of description logics does not

guarantee correct representations !

Page 80: ECO R European Centre for Ontological Research Realist Ontology for the Semantic Web: Applications in Biomedical Informatics Werner Ceusters European Centre

ECOREuropean Centre forOntological Research Sloppiness in definitions

new-1

new-2

Page 81: ECO R European Centre for Ontological Research Realist Ontology for the Semantic Web: Applications in Biomedical Informatics Werner Ceusters European Centre

ECOREuropean Centre forOntological Research

NCI Thesaurus

• a biomedical thesaurus created specifically to meet the needs of the National Cancer Institute.

• semantically modeled cancer-related terminology built using description logics

Page 82: ECO R European Centre for Ontological Research Realist Ontology for the Semantic Web: Applications in Biomedical Informatics Werner Ceusters European Centre

ECOREuropean Centre forOntological Research

NCI Thesaurus Root concepts

Anatomic Structure, Anatomic System, or Anatomic Substance ?Or ? Does the NCI not know to which categoryAny item classified there belongs ?Anatomic Substance ? If yes, why is geneproduct not subsumed by it ? If no, why aredrugs and chemicals not subsumed by it ?

Page 83: ECO R European Centre for Ontological Research Realist Ontology for the Semantic Web: Applications in Biomedical Informatics Werner Ceusters European Centre

ECOREuropean Centre forOntological Research

Conceptual entity

• Definition: none• Semantic type:

– Conceptual entity– Classification

• Subconcepts:– Action:

• definition: action; a thing done

– And: • Definition: an article which expresses the relation of

connection or addition, used to conjoin a word with a word, ...

– Classification• Definition: the grouping of things into classes or categories

Page 84: ECO R European Centre for Ontological Research Realist Ontology for the Semantic Web: Applications in Biomedical Informatics Werner Ceusters European Centre

ECOREuropean Centre forOntological Research

Definition of “cancer gene”

Page 85: ECO R European Centre for Ontological Research Realist Ontology for the Semantic Web: Applications in Biomedical Informatics Werner Ceusters European Centre

ECOREuropean Centre forOntological Research

NCI Thesaurus architecture

Disease

BreastBreast neoplasmDisease-has-associated-anatomy

ISA

Findings-And-Disorders-Kind Anatomy-Kind

“Formal subsumption” or

“inheritance”

“Associative” relationships providing

“differentiae”

“Kinds” restrict the domain and range of

associative relationships

What diseases have a diameter of over 3 cm ?

Page 86: ECO R European Centre for Ontological Research Realist Ontology for the Semantic Web: Applications in Biomedical Informatics Werner Ceusters European Centre

ECOREuropean Centre forOntological Research

Ontology versusDescription Logics

• In the Description Logic world – terms and definitions come first,– the job is to validate them and reason with them by

means of a model– but whether the model correspond to reality is not its

problem (Workshop on DL, Saarbrücken, 22-23/11/2004)

• In the realist ontology world – robust ontology (with all its reasoning power) comes

first– terms, term-hierarchies and record architectures must

be subjected to the constraints of ontological coherence

Page 87: ECO R European Centre for Ontological Research Realist Ontology for the Semantic Web: Applications in Biomedical Informatics Werner Ceusters European Centre

ECOREuropean Centre forOntological Research

Thanks x there is OWL ?

Where x {

}

, , ,

,

Page 88: ECO R European Centre for Ontological Research Realist Ontology for the Semantic Web: Applications in Biomedical Informatics Werner Ceusters European Centre

ECOREuropean Centre forOntological Research

Understanding content (1)

“John Doe has a pyogenic granuloma of the left thumb”

Page 89: ECO R European Centre for Ontological Research Realist Ontology for the Semantic Web: Applications in Biomedical Informatics Werner Ceusters European Centre

ECOREuropean Centre forOntological Research

Understanding content (2)

<record><patient>John Doe</patient>

<diagnosis>pyogenic granuloma of the left thumb</diagnosis>

</record>

< >

< > </ >

< > </ >

</ >

Page 90: ECO R European Centre for Ontological Research Realist Ontology for the Semantic Web: Applications in Biomedical Informatics Werner Ceusters European Centre

ECOREuropean Centre forOntological Research

Understanding content (3)

<129465004><116154003>John Doe</116154003>

< 8319008 > 17372009

<finding site> 76505004

<laterality>7771000</laterality>

</finding site>

</ 8319008 >

</129465004>

Page 91: ECO R European Centre for Ontological Research Realist Ontology for the Semantic Web: Applications in Biomedical Informatics Werner Ceusters European Centre

ECOREuropean Centre forOntological Research

XML OWL

• XML– Pure syntax– Simulated semantics

• OWL:– Very precise semantics– But is the semantics of the right sort to faithfully

describe simple medical facts ?

Page 92: ECO R European Centre for Ontological Research Realist Ontology for the Semantic Web: Applications in Biomedical Informatics Werner Ceusters European Centre

ECOREuropean Centre forOntological Research NCIT’s “Lung” in OWL

<owl:Class rdf:ID="Lung"><rdfs:label>Lung</rdfs:label><code>C12468</code><hasType>primitive</hasType><rdfs:subClassOf rdf:resource="#Organ"/><rdfs:subClassOf>

<owl:Restriction><owl:onProperty

rdf:resource="#rAnatomic_Structure_Has_Location"/><owl:someValuesFrom rdf:resource="#Thoracic_Cavity"/>

</owl:Restriction></rdfs:subClassOf>...</owl>

“All instances of lung must be located in at least one

instance of thoracic cavity”Hence: total lung excision is

impossible.

Page 93: ECO R European Centre for Ontological Research Realist Ontology for the Semantic Web: Applications in Biomedical Informatics Werner Ceusters European Centre

ECOREuropean Centre forOntological Research NCIT’s “Lung” in OWL

<owl:Class rdf:ID="Lung"><rdfs:label>Lung</rdfs:label><code>C12468</code><hasType>primitive</hasType><rdfs:subClassOf rdf:resource="#Organ"/><rdfs:subClassOf>

<owl:Restriction><owl:onProperty

rdf:resource="#rAnatomic_Structure_Has_Location"/><owl:allValuesFrom rdf:resource="#Thoracic_Cavity"/>

</owl:Restriction></rdfs:subClassOf>...</owl>

“every assigned location of pleura must be an instance of

the class Thoracic Cavity”Allows lungs not to be

located at all.

Page 94: ECO R European Centre for Ontological Research Realist Ontology for the Semantic Web: Applications in Biomedical Informatics Werner Ceusters European Centre

ECOREuropean Centre forOntological Research

Take home messages

• Very few “ontologies” are ontologies.

• Realist ontology offers a good methodology for building consistent representations.

• DLs are helpful, but only if you know how to use them properly.

• OWL is inadequate to represent even the most obvious facts.

• Please ... be critical when buzz words are used.