eco r european centre for ontological research realist ontology for the semantic web: applications...
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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
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
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European Centre forOntological Research
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Status Dec 2, 2004
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Management Board
Status Dec 2, 2004
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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.
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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
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Our building
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What philosophers are good for...
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Short personal history
1959 - ...1977
1989
1992
1998
2002
2004
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“Ontology”
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WordNet 2.0 - 2003
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“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
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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)
?????
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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.
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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.
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.
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)
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“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
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• 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”
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Realist Ontology
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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
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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
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
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The realist ontological square (Ignacio Angelelli)
Substance Particulars Quality Particulars
SubstanceUniversals
QualityUniversals
instance instance
differentia
exemplify
inheres
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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)
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“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.
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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 ?
ECOREuropean Centre forOntological Research Identity & instanciation
child adult
caterpillar butterfly
t
person
animal
Livingcreature
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• +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
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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
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Theory of granular partitions (B. Smith)
Think of it as Alberti’s grid
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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
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:
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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
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.
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Occurants and continuants
Picture by Vladimir Brajic
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SpanBFO
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• 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
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Why is the concept-basedapproach so wide-spread ?
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
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= ?
This is communication !
kocher Give me a kocher, please.
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Triadic models of meaning: The Semiotic/Semantic triangle
Sign:Language/
Term/Symbol
Referent:Reality/Object
Reference: Concept / Sense / Model / View / Partition
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.
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– ...
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
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Don’t confuse with homonymy !
“mole” mole (animal)
R1
mole (unit)
R2
mole (skin lesion)
R3
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Different thoughts Homonymy
“mole” mole “animal”
R1
mole “unit”
R2
mole“skin lesion”
R3
symbol referent
understanding
One conceptof x understanding of y
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And by the way, synonymy...
the Aristotelian view Richards’ view
“perspiration”
“sweat”“sweat”
“perspiration”
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
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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
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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.
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)
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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
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)
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.
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The price you pay if you gofor concepts ...
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Border’s classification of medicine
• Medicine– Mental health– Internal medicine
• Endocrinology–Oversized endocrinology
• Gastro-enterology• ...
– Pediatrics– ...– Oversized medicine
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
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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 ???
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• 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
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• 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 !
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• 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 ?
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
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
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 ?
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
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: ...
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. :-)
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UMLS Semantic Network
ECOREuropean Centre forOntological Research Semantic Network
Relationships• Is_a
• physically related to
• spatially related to
• temporally related to
• functionally related to
• conceptually related to
ECOREuropean Centre forOntological Research Semantic Network “Biologic
Function” Hierarchy
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Semantic Network "affects" Hierarchy
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“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, ...
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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”
• ...
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Ok, then Description Logicswill save us ... ?
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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)
ECOREuropean Centre forOntological Research
Snomed and DL
SNOMED-RT (2000)
SNOMED-CT (2003)
DL don’t guarantee you to get parthood right !
ECOREuropean Centre forOntological Research Use of description logics does not
guarantee correct representations !
ECOREuropean Centre forOntological Research Sloppiness in definitions
new-1
new-2
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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
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 ?
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
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Definition of “cancer gene”
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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 ?
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
ECOREuropean Centre forOntological Research
Thanks x there is OWL ?
Where x {
}
, , ,
,
ECOREuropean Centre forOntological Research
Understanding content (1)
“John Doe has a pyogenic granuloma of the left thumb”
ECOREuropean Centre forOntological Research
Understanding content (2)
<record><patient>John Doe</patient>
<diagnosis>pyogenic granuloma of the left thumb</diagnosis>
</record>
< >
< > </ >
< > </ >
</ >
ECOREuropean Centre forOntological Research
Understanding content (3)
<129465004><116154003>John Doe</116154003>
< 8319008 > 17372009
<finding site> 76505004
<laterality>7771000</laterality>
</finding site>
</ 8319008 >
</129465004>
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 ?
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.
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.
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.