VT - PowerPoint PPT Presentation

1 / 87
About This Presentation
Title:

VT

Description:

John Searle s Ontology of Social Reality Its Glory and Its ... ... vt – PowerPoint PPT presentation

Number of Views:121
Avg rating:3.0/5.0
Slides: 88
Provided by: BarryS185
Category:

less

Transcript and Presenter's Notes

Title: VT


1
VT
2
The First Industrial-Strength Philosophy
3
IFOMIS
  • Institute for Formal Ontology
  • and Medical Information Science
  • http//ifomis.de

4
Medicine
  • needs to find a way to enable the huge amounts
    of data resulting from formal trials and from
    informal clinical practice
  • to be (f)used together

5
The problem
  • Different communities of medical researchers use
    different and often incompatible category systems
    in expressing the results of their work

6
Example Medical Nomenclature
  • MeSH (Medical Subject Headings) blood is a
    tissue
  • SNoMed (Systematized Nomenclature of Medicine)
  • blood is a fluid

7
The solution
  • ONTOLOGY
  • Remover Ontology Impedance
  • But what does ontology mean?

8
Two alternative readings
  • Ontologies are oriented around terms or concepts
    currently popular IT conception
  • Ontologies are oriented around the entities in
    reality traditional philosophical conception,
    embraced also by IFOMIS

9
Ontology as a branch of philosophy
  • seeks to establish
  • the science of the kinds and structures of
    objects, properties, events, processes and
    relations in every domain of reality

10
Ontology a kind of generalized chemistry or
zoology
  • (Aristotles ontology grew out of biological
    classification)

11
Aristotle
worlds first ontologist

12
Worlds first ontology (from Porphyrys
Commentary on Aristotles Categories)
13
Linnaean Ontology
14
Medical Diagnostic Ontology
15
Ontology is distinguished from the special
sciences
it seeks to study all of the various types of
entities existing at all levels of granularity
16
and to establish how they hang together to form a
single whole (reality or being)
17
Sources for ontological theorizing
  • the study of ancient texts
  • thought experiments (we are philosophers, after
    all)
  • the development of formal theories
  • the results of natural science
  • now also
  • working with computers

18
The existence of computers
  • and of large databases
  • allows us to express old philosophical problems
    in a new light

19
Example The Gene Ontology (GO)
  • hormone GO0005179
  • digestive hormone GO0046659
  • peptide hormone GO0005180 adrenocorticotrop
    in GO0017043 glycopeptide hormone
    GO0005181 follicle-stimulating hormone
    GO0016913
  • subsumption (lower term is_a higher term)

20
as tree
  • hormone
  • digestive hormone peptide hormone
  • adrenocorticotropin
    glycopeptide hormone

  • follicle-stimulating hormone

21
GO
  • is very useful for purposes of standardization in
    the reporting of genetic information
  • but it is not much more than a telephone
    directory of standardized designations organized
    into hierarchies

22
GO deals with such basic ontological notions very
haphazardly
  • GOs three main term-hierarchies are
  • component, function and process
  • But GO confuses functions with structures, and
    also with executions of functions
  • and has no clear account of the relation between
    functions and processes

23
Moreover,
  • GO can in practice be used only by trained
    biologists
  • whether a GO-term stands in the subsumption
    relationship

24
A still more important problem
  • There exist multiple databases
  • GDB
  • Genome Database of Human Genome Project
  • GenBank
  • National Center for Biotechnology Information,
    Washington DC
  • etc.

25
What is a gene?
  • GDB a gene is a DNA fragment that can be
    transcribed and translated into a protein
  • GenBank a gene is a DNA region of biological
    interest with a name and that carries a genetic
    trait or phenotype
  • GO uses gene in its term hierarchy,
  • but it does not tell us which of these
    definitions is correct

26
How resolve such incompatibilities?
  • The Semantic Web Initiative
  • (Tim Berners-Lee, the inventor of the internet)
  • enforce terminological compatibility via
    standardized term hierarchies, with standardized
    definitions of terms
  • applied as meta-tags to websites

27
The Semantic Web
  • The Web is a vast edifice of heterogeneous data
    sources
  • Needs the ability to query and integrate across
    different conceptual systems

28
Metadata the new Silver Bullet
  • We agree on a metadata standard for washing
    machines as concerns size, capacity, energy
    consumption, water consumption, price
  • We create machine-readable databases of our
    inventories and put them on the net
  • A consumer can then query multiple sites
    simultaneously
  • and thereby search the Internet for highly
    specific, reliable, context-sensitive results

29
Cary Doctorow
  • A world of exhaustive, reliable metadata would
    be a utopia.

30
Problem 1 People lie
  • Meta-utopia is a world of reliable metadata.
  • But poisoning the well can confer benefits to
    the poisoners
  • Metadata exists in a competitive world. Some
    people are crooks. Some people are cranks.

31
Problem 2 People are lazy
  • Half the pages on Geocities are called Please
    title this page

32
Problem 3 People are stupid
  • The vast majority of the Internet's users
  • (even those who are native speakers of English)
  • cannot spell or punctuate
  • Will internet users suddenly and en masse learn
    to accurately categorize their information
    according to whatever DL-hierarchy they're
    supposed to be using?

33
Problem 4 Metrics influence results
  • raw MHz scores privilege Intel's CISC chips over
    Motorola's RISC chips.
  • Every player in a metadata standards body will
    want to emphasize their high-scoring axes

34
Problem 5 Multiple descriptions
  • We impart information
  • He chatters
  • They gossip
  • Requiring everyone to use the same vocabulary to
    describe their material denudes the cognitive
    landscape, enforces homogeneity in ideas.

35
Problem 6 Ontology Impedance
  • semantic mismatch between ontologies being
    merged
  • This problem recognized in Semantic Web
    literature
  • http//ontoweb.aifb.uni-karlsruhe.de/About/Deliver
    ables/ontoweb-del-7.6-swws1.pdf

36
Solution 1 treat it as (inevitable) impedance
  • and learn to find ways to cope with the
    disturbance which it brings
  • Suggested here
  • http//ontoweb.aifb.uni-karls-ruhe.de/Ab-out/Deliv
    erables/ontoweb-del-7.6-swws1.pdf

37
Solution 2 resolve the impedance problem on a
case-by-case basis
  • Suppose two databases are put on the web.
  • Someone notices that "where" in the friends
    table and "zip" in a places table mean the same
    thing.
  • http//www.w3.org/DesignIssues/Semantic.html

38
Both solutions fail
  • treating mismatches as impedance inappropriate
    in an area like medicine
  • and ignores the problem of error propagation
  • 2. resolving impedance on a case-by-case basis
    defeats the very purpose of the Semantic Web

39
Problem 5 Multiple descriptions
  • Requiring everyone to use the same vocabulary to
    describe their material not always practicable
    especially in the medical domain

40
Clinicians
  • often do not use category systems at all they
    use unstructured text
  • from which useable data has to be extracted in a
    further step
  • Reasons for this every case is different, much
    patient data is context-dependent

41
Proposed IFOMIS solution
  • distinguish two separate tasks
  • - the task of developing computer applications
    capable of running in real time
  • the task of developing an expressively rich
    framework of a sort which will allow us to
    resolve incompatibilities between definitions

42
different terminology systems
43
need not interconnect at all
for example they may relate to entities of
different granularity
44
we cannot make incompatible terminology-systems
interconnect
just by looking at concepts, or knowledge or
language
45
we cannot make incompatible terminology-systems
interconnect
or by staring at the terminology systems
themselves
46
to decide which of a plurality of competing
definitions to accept
we need some tertium quid
47
we need, in other words,
to take the world itself into account
48
BFO
  • basic formal ontology

49
BFO
  • ontology is defined not as the standardization
    or specification of conceptualizations
  • (not as a branch of knowledge or concept
    engineering)
  • but as an inventory of the entities existing in
    reality

50
The BFO framework
  • will solve the problem of ontological impedance
    and provide tools for quality-control on the
    output of computer applications

51
BFO not a computer application
  • but a Reference Ontology
  • (something like old-fashioned metaphysics)

52
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

53
Reference Ontology
  • a theory of the tertium quid
  • called reality
  • needed to hand-callibrate database/terminology
    systems

54
Methodology
  • Get ontology right first
  • (realism descriptive adequacy rather powerful
    logic)
  • solve tractability problems later

55
A reference ontology
  • is a theory of reality
  • But how is this possible?
  • How can we get beyond our concepts?

56
Answer
  • draw on 2 millennia of philosophical research
  • pertaining to realism, scepticism, error, theory
    change, and the language/concept/world relation
  • pertaining to the structure of reality itself at
    different levels of granularity
  • APPLY THE RESULTS TO THE DOMAIN OF MEDICAL REALITY

57
try to find ways to look at the same objects at
different levels of granularity
58
and also
  • look not at concepts, representations, of a
    passive observer
  • but rather at agents (clinicians) acting in the
    world
  • taking account of the tacit knowledge of reality
    which the domain experts possess
  • GO useable only by biologists, because only they
    know how given terms function in given contexts

59
The Reference Ontology Community
  • IFOMIS (Leipzig)
  • Laboratories for Applied Ontology (Trento/Rome,
    Turin)
  • Foundational Ontology Project (Leeds)
  • Ontology Works (Baltimore)
  • Ontek Corporation (Buffalo/Leeds)
  • Language and Computing (LC) (Belgium/Philadelphia
    )

60
Domains of Current Work
  • IFOMIS Leipzig Medicine, Bioinformatics
  • Laboratories for Applied Ontology
  • Trento/Rome Ontology of Cognition/Language
  • Turin Law
  • Foundational Ontology Project Space, Physics
  • Ontology Works Genetics, Molecular Biology
  • Ontek Corporation Biological Systematics
  • Language and Computing Natural Language
    Understanding

61
Recall
  • GDB a gene is a DNA fragment that can be
    transcribed and translated into a protein
  • Genbank a gene is a DNA region of biological
    interest with a name and that carries a genetic
    trait or phenotype

62
Ontology
  • fragment, region, name, carry, trait,
    type
  • ... part, whole, function, inhere,
    substance
  • are ontological terms in the sense of traditional
    (philosophical) ontology

63
BFO
  • not just a system of categories
  • but a formal theory
  • with definitions, axioms, theorems
  • designed to provide the resources for reference
    ontologies for specific domains
  • of sufficient richness that terminological
    incompatibilities can be resolved intelligently
    rather than by brute force

64
Two basic oppositions
  • Granularity (of molecules, genes, cells, organs,
    organisms ...)
  • SNAP vs. SPAN

65
SNAP vs. SPAN
  • Two different ways of existing in time
  • continuing to exist (of organisms, their
    qualities, roles, functions, conditions)
  • occurring (of processes)
  • SNAP vs. SPAN Anatomy vs. Physiology

66
SNAP Entities existing in toto at a time
67
Three kinds of SNAP entities
  1. Independent Substances, Objects, Things
  2. Dependent Qualities, Functions, Conditions,
    Roles
  3. Spatial regions

68
SNAP Dependent
69
SNAP-Spatial Region
70
SNAP-Independent
71
SPAN Entities occurring in time
72
SPAN Dependent (Processes)
73
SPAN Spatiotemporal Regions
74
Realization (SNAP-SPAN)
  • the execution of a plan
  • the expression of a function
  • the exercise of a role
  • the realization of a disposition
  • the course of a disease
  • the application of a therapy

75
SNAP dependent entities and their SPAN
realizations
  • plan
  • function
  • role
  • disposition
  • disease
  • therapy

76
SNAP dependent entities and their SPAN
realizations
  • execution
  • expression
  • exercise
  • realization
  • course
  • application

SPAN
77
More examples
  • performance of a symphony
  • projection of a film
  • expression of an emotion
  • utterance of a sentence
  • increase of body temperature
  • spreading of an epidemic
  • extinguishing of a forest fire
  • movement of a tornado

78
BFO SNAP/SPAN Theory of Granular Partitions
  • theory of universals and instances
  • theory of part and whole
  • theory of boundaries
  • theory of functions, powers, qualities, roles
  • theory of environments, contexts
  • theory of spatial and spatiotemporal regions

79
MedO medical domain ontology
  • universals and instances and normativity
  • theory of part and whole and absence
  • theory of boundaries/membranes
  • theory of functions, powers, qualities, roles,
    (mal)functions, bodily systems
  • theory of environments inside and outside the
    organism
  • theory of spatial and spatiotemporal regions
    anatomical mereotopology

80
MedO medical domain ontology
  • theory of granularity relations between
  • molecule ontology
  • gene ontology
  • cell ontology
  • anatomical ontology
  • etc.

81
IFOMIS project
  • collaborate with LC to show how an ontology
    constructed on the basis of philosophical
    principles can help in overhauling and validating
    LCs large terminology-based medical ontology
    LinkBase

82
Testing the BFO/MedO approach
  • within a software environment for NLP of
    unstructured patient records
  • collaborating with
  • Language and Computing nv (www.landcglobal.be)

83
LC
  • LinKBase worlds largest terminology-based
    ontology
  • with mappings to UMLS, SNOMED, etc.
  • LinKFactory suite for developing and managing
    large terminology-based ontologies

84
LinKBase
  • LinKBase still lacking a formal theory
  • BFO and MedO designed to add better reasoning
    capacity
  • by tagging LinKBase domain-entities with
    corresponding BFO/MedO categories
  • by constraining links within LinKBase according
    to the theory of granular partitions

85
LCs long-term goal
  • Transform the mass of unstructured patient
    records into a gigantic medical experiment

86
IFOMISs long-term goal
  • Build a robust high-level BFO-MedO framework
  • THE WORLDS FIRST INDUSTRIAL-STRENGTH PHILOSOPHY
  • which can serve as the basis for an
    ontologically coherent unification of medical
    knowledge and terminology

87
END
  • http//ontologist.com
Write a Comment
User Comments (0)
About PowerShow.com