manchester medical informatics group opengalen 1 linking formal ontologies: scale, granularity and...

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Manchester Medical Informatics Group OpenGALEN

Linking Formal Ontologies: Scale, Granularity and Context

Alan Rector

Medical Informatics Group, University of Manchesterwww.cs.man.ac.uk/mig

www.opengalen.orgimg.cs.man.ac.uk

[email protected]

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Why use Logic-based Ontologies?

because

Knowledge is Fractal!&

Changeable!

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Four Roles of Terminology/Ontologies

• Content of Databases and Patient Records – Structural linkage within EPR/EHR & messages– Content of EPR/EHR & messages

• Capturing information - the user interface

• Linkage between domainsLinkage between domains– Health and Bio Sciences Health and Bio Sciences – Macro, Micro, and Molecular scalesMacro, Micro, and Molecular scales– Contexts: Normal / abnormal; species; stage of developmentContexts: Normal / abnormal; species; stage of development– Healthcare delivery and Clinical research– Patient Records and Decision Support

• Indexing Information– Metadata and the semantic web

• www.semanticweb.org www.w3c.org

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Logic based ontologies

• The descendants of frame systems and object hierarchies via KL-ONE

• “is-kind-of” = “implies” – “Dog is a kind of wolf”

means“All dogs are wolves”

– Therefore logically computable

• Modern examples: OIL, DAML+OIL (“OWL”?)– Underpinned by the FaCT family of Description Logic Reasoners

• Others LOOM, CLASSIC, BACK, GRAIL,...

• www.ontoknowledge.org/oil www.semanticweb.org

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Logic-based Ontologies: Conceptual Lego

hand

extremity

body

acute

chronic

abnormal

normalischaemic

deletion

bacterial

polymorphism

cell

protein

gene

infection

inflammation

Lung

expression

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Logic-based Ontologies: Conceptual Lego

“SNPolymorphism of CFTRGene causing Defect in MembraneTransport of ChlorideIon causing Increase in Viscosity of Mucus in CysticFibrosis…”

“Hand which isanatomicallynormal”

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What’s in a “Logic based ontology”?

• Primitive concepts - in a hierarchy– Described but not defined

• Properties - relations between concepts– Also in a hierarchy

• Descriptors - property-concept pairs – qualified by “some”, “only”, “at least”, “at most”

• Defined concepts– Made from primitive concepts and descriptors

• Axioms– disjointness, further description of defined concepts

• A Reasoner– to organise it for you

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Encrustation

+ involves: MitralValve

Thing

+ feature: pathological

Structure

+ feature: pathological

+ involves: Heart

Logic Based Ontologies: A crash course

Thing

Structure

Heart MitralValve EncrustationMitralValve* ALWAYS partOf: Heart

Encrustation* ALWAYS feature: pathological

Feature

pathological red

+ (feature: pathological)

red

+ partOf: Heart

red

+ partOf: Heart

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Bridging Bio and Health Informatics

• Define concepts with ‘pieces’ from different scales and disciplines– “Polymorphism which causes defect which causes disease”

• Define concepts which make context explicit– “ ‘Hand which is anatomically normal’

has five fingers”

• Separate properties for different contexts/views – “Abnormalities of clinical parts of the heart”

• includes pericardium

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Bridging Scales and

context with Ontologies

GenesSpecies

Protein

Function

Disease

Protein coded bygene in species

Function ofProtein coded bygene in species

Disease caused by abnormality inFunction ofProtein coded bygene in species

Gene in Species

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Representing context and views by variant properties

Organ

HeartPericardium

OrganPart

CardiacValve

Disease of (is_part_of) Heart

Disease of Pericardium

is_part_of

is_structurally_part_ofis_clinically_part_of

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The cost: Ontologies are not Thesauri

organ } kind heart } part heart valve } kind aortic valve } part aortic valve cusp

A Mixed Hierarchy

Works for navigation by humans

Works for “Disease of…’ and ‘Procedure on…’

Fails for “Surface of…”

How can the computer know the difference?

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From a thesaurus to a logic-based ontology

disorder of organ

disorder of heart

disorder of valve in heart

disorder of aortic valve in heart

disorder of cusp in aortic valve in heart

A logic-based is-kind-of (subsumption) hierarchy

Untangle part-whole and is-kind-of in anatomic ontology

Link Clinical Ontology with Anatomical ontology

Add rule that “Disorder of part disorder of whole”

Reasoner can then create automatically:

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Examples common in Bio Ontologies

Is part ofGolgi membrane Integral protein

Is part ofPlasma membrane Apical plasma membrane

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The Cost: Normalising (untangling) Ontologies

StructureFunction

Part-wholeStructure Function

Part-w

hole

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The Cost: Normalising (untangling) Ontologies

Making each meaning explicit and separate

… ActionRole PhysiologicRole HormoneRole CatalystRole …

… Substance BodySubstance Protein Steroid …

PhysSubstance Protein ProteinHormone Insulin Enzyme Steroid SteroidHormone Hormone ProteinHormone^ Insulin^ SteroidHormone^ Catalyst Enzyme^

Hormone = Substance & playsRole-HormoneRoleProteinHormone = Protein & playsRole-HormoneRoleSteroidHormone = Steroid & playsRole-HormoneRoleCatalyst = Substance & playsRole CatalystRole

...and helping keep argument rational and meetings short!

Enzyme ?=? Protein & playsRole-CatalystRole

PhysSubstance Protein ‘ ProteinHormone’ Insulin ‘Enzyme’ Steroid ‘SteroidHormone’ ‘Hormone’ ‘ProteinHormone’ Insulin^ ‘SteroidHormone’ ‘Catalyst’ ‘Enzyme’

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The Cost

• You can’t say everything you want to– Expressiveness costs computational complexity

• More inference takes more time– Scaling for complex tasks still being investigated

• Many other kinds of reasoning needed

It doesn’t make the! Coffee!

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Other benefits• Limit combinatorial explosions

From “phrase book” to “dictionary + grammar” Avoid the “exploding bicycle”

– 1980 - ICD-9 (E826) 8 – 1990 - READ-2 (T30..) 81– 1995 - READ-3 87– 1996 - ICD-10 (V10-19) 587

• V31.22 Occupant of three-wheeled motor vehicle injured in collision with pedal cycle, person on outside of vehicle, nontraffic accident, while working for income

– and meanwhile elsewhere in ICD-10

• W65.40 Drowning and submersion while in bath-tub, street and highway, while engaged in sports activity

• X35.44 Victim of volcanic eruption, street and highway, while resting, sleeping, eating or engaging in other vital activities

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Study a phase 2

Other benefits

Hypertension

Idiopathic Hypertension

In our company’s studies

Study a

Phase 2

Hypertension

Idiopathic Hypertension`

In our company’s studies

Phase 2

• Index and assemble information

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Summary: Logic based ontologies because

Knowledge is Fractal• Link “Conceptual Lego”

– at all levels• indefinitely

– Spanning scales, genotype, phenotype, etc.

• Model context and views– Express differences explicitly

• Manage combinatorial explosion

• Index information efficiently

Next step: Larger scale demonstrations in Genotype to Phenotype

manchester medical informatics group opengalen 1 linking formal ontologies: scale, granularity and...

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