From Knowledge Representation to Reality Representation

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From Knowledge Representation to Reality Representation. Barry Smith. 2002. Institute for Formal Ontology and Medical Information Science (Germany) initially: work on formal ontology and on ontology-based quality control in medical terminologies (UMLS, SNOMED, NCI Thesaurus, etc.). - PowerPoint PPT Presentation

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  • From Knowledge Representation to Reality Representation Barry Smith

  • 2002Institute for Formal Ontology and Medical Information Science (Germany)initially: work on formal ontology and on ontology-based quality control in medical terminologies(UMLS, SNOMED, NCI Thesaurus, etc.)

  • Problem: Associative approach to word meaningsFruitOrangeVegetableSimilarToApfelsineSynonymWithNarrowerThanGoble & Shadbolt

  • both testes is_a testisplant leaves is_a plantmenopause part_of deathbacterium causes experimental model of diseasenot normal cell is_a cellnot abnormal cell is_a cell

  • move from associative relations between meanings to ontological relations between the entities themselvessupplementing data mining approaches withbetter databetter annotationsbetter integrationthe possibility of strong logical reasoning

  • First crack in the wallDigital Anatomist Foundational Model of Anatomy (Department of Biological Structure, University of Washington, Seattle)

    Virtual Soldier Project: Reference Ontology of AnatomyReference Ontology of PhysiologyReference Ontology of Disease Pathways

  • Second Crack in the WallGene Ontology ConsortiumOpen Biological Ontologies

  • NCOR: National Center for Ontological ResearchBuffalo Center of Excellence in Bioinformatics)

    Stanford Medical Informatics (Protg 2000)

    Berkeley Drosophila Genome Project (Model Organism Phenotype Ontology Project)

  • NCOR: National Center for Ontological Researchplus industrial parners Ontology Works...

  • NCOR Methodologywork with content developers to ensure rigorous conformity with good principles of classification and definitionuse formally defined categories and relations to ensure interoperability and support automatic reasoning and to move beyond mere statistical / associative techniques

  • Goal in Biomedical Informaticsuse the methodology of formally defined relations and a common top-level ontology to bridge the granularity gap between genomics and proteomics data and phenotype (clinical, pharmacological, patient centered) data

    From molecules to diseases

  • Examples of simple formal-ontological structuresis_a hierarchiespart_of hierarchiesdependence relations

  • A Window on Reality

  • Medical Diagnostic Hierarchya hierarchy in the realm of diseases

  • Dependence RelationsOrganismsDiseases

  • A Window on RealityOrganismsDiseases

  • Pleural CavityInterlobar recessMesothelium of PleuraPleura(Wall of Sac)VisceralPleuraPleural SacParietal PleuraAnatomical SpaceOrganCavitySerous SacCavityAnatomicalStructureOrganSerous SacMediastinalPleuraTissueOrgan ComponentOrgan CavitySubdivisionSerous SacCavitySubdivisionpart_of is_a

  • A Window on Reality

  • We can reason across such hierarchies and combinationsbut only if the top-level categories and associated formal-ontological relations are well-defined and used consistently

  • Formal-Ontological Categories

    objectprocesssitelayerfragmentqualityfunctionrelationboundaryregion

  • Formal-Ontological Relations

    is_identical_tois_apart_ofdevelops_ fromderives_ from located_atdepends_onis_boundary_ofhas_participanthas_agentadjacent_tocontained_inprecedesis_functioning_ofhas_functionintends

  • To support integration of ontologiesrelational expressions such asis_a part_of... should be used in the same way by all the ontologies to be integratedNCOR goal

  • to define these relations properlywe need to take account of reality

    If we remain in the realm of concepts we will forever face problems of interoperability

  • to define these relations properlywe need to take account not of concepts, but of universals and instances in reality

  • Tom Gruber

    An ontology is a specification of a conceptualization

  • The Concept OrientationWork on biomedical ontologies grew out of work on medical dictionaries and thesauriled to the assumption that all that need be said about concepts can be said without appeal to time or instances. & fostered an impoverished regime of definitions

  • Concept in ontology runs together:the meaning that is shared in common by a collection of synonymous termsan idea shared in common in the minds of those who use synonymous terms (psycho-linguistic view)a universal, feature or property shared by entities in the world which fall under the concept

  • Problem of evaluationif an ontology is a mere specification of a conceptualization, then the distinction between good and bad ontologies loses its foothold in reality

  • There are more word meanings than there are types of entities in realityunicorndevil cancelled performanceavoided meetingprevented pregnancyimagined mammal ...

  • A is_a B =def. A is more specific in meaning than B

  • unicorn is_a one-horned mammalalien implant removal is_a surgical processChios energy healing is_a therapeutic process

  • This linguistic readingyields a more or less coherent reading of relations like: is_asynonymous_withassociated_to

  • but it fails miserably when it comes to relations of other typespart_of = def. composes, with one or more other physical units, some larger wholecontains =def. is the receptacle for fluids or other substances.

  • for how can concepts, on the linguistic reading, figure as relata of relations like: part_ofadjacent_toconnected_to

  • connected_to =def. Directly attached to another physical unit as tendons are connected to muscles. How can a meaning or concept be directly attached to another physical unit as tendons are connected to muscles ?

  • is_ahuman is_a mammal

    all instances of the universal human are as a matter of necessity instances of the universal mammal

  • EvaluationGood ontologies are those whose general terms correspond to universals in reality, and thereby also to corresponding instances.

  • Kinds of relations

    : is_a, part_of, ...

    : this explosion instance_of the universal explosion

    : Marys heart part_of Mary

  • Instance-level relationspart_ofis_located_athas_participanthas_agentearlier. . .

  • part_of

    For instances:part_of = instance-level parthood (for example between Mary and her heart)

    For universals:A part_of B =def. given any instance a of A there is some instance b of B such that a part_of b

  • transformation_of

  • transformation_offetus transformation_of embryo adult transformation_of child

    C2 transformation_of C1 =def. any instance of C2 was at some earlier time an instance of C1

  • derives_fromc derives_from c1 =def c and c1 are non-identicaland exist in continuous succession

  • the new component detaches itself from the initial component, which itself continues to exist C c at t C c at t C1c1 at t1c at t1 C1c1 at tthe initial component ceases to exist with the formation of the new component

  • two initial components fuse to form a new component C c at tC1 c1 at t1C'c' at t

  • Functionsyour heart has the function: to pump blood=your heart is predisposed (has the potential or casual power) to realize a process of the type pumping blood.

    has_agent (instance-level relation)p is_functioning_of c p has_agent c

  • Example: Spatially Coinciding Objects with thanks to Maureen Donnelly

  • Two entities coincide (partially) when they overlap (share parts)my hand coincides with my body the European Union coincides with the British Commonwealth (United Kingdom Malta, Cyprus)

  • Some entities coincide even though they share no parts

    any material object coincides with its spatial regiona portion of food coincides with my stomach cavity

  • Holes may coincide with material objects

    The hole in the chunk of amber coincides completely with, but does not overlap, the encapsulated insect which fills it Sometimes holes and objects are moving independently (a bullet flying through a railway carriage moving through a tunnel)

  • Layersco-located objectsThe region layer

  • Layered Ontology of LakesL1. a region layerL2. a lake layer, consisting of a certain concave portion of the earths surface together with a body of waterL3. a fish layer L4. a chemical contaminant layer

  • Layered Epidemiology OntologyL1. a two-dimensional region layer in some undisclosed locationL2. a topographical layer, consisting of mountains, valleys, deserts, gulliesL3. a storm-system occupying sub-regions of L2 L4: an airborne cloud of smallpox virus particles.

  • Layered Mereology= modified General Extensional Mereology (GEM)

  • Parthood (P)Parthood is a partial ordering:

    (P1) Pxx (reflexive)(P2) Pxy & Pyx -> x = y (antisymmetric)(P3) Pxy & Pyz -> Pxz (transitive)(P4) ~Pxy -> $z(Pzx & ~Ozy) (the remainder principle: if x is not part of y, then x has a part that does not overlap y)

  • co-located objectsThe region layer

  • The Region Functionr(x) = the region at which x is exactly located.

    r is a new primitive

    r maps (collapses) entities on all higher layers onto the region layer

  • Axioms for the region function, e.g.

    (R3) Pxy P r(x)r(y)

  • Some TheoremsRy r(y) = y (every region is located at itself)

    (x & x( Rx) &"y (Oyz $x (f & Oyx))) Rz (every sum of regions is a region)

  • Defined RelationsECxy =: Cxy & ~ Oxy (x and y are externally connected)

    Axy =: EC(r(x), r(y)) (x and y abut)

  • To

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