Transcript Document

R T U New York State
Center of Excellence in
Bioinformatics & Life Sciences
MIE 2006 Workshop
Semantic Challenge for
Interoperable EHR Architectures
provided by EFMI WGs EHR - Security, Safety and Ethics Natural Language Understanding
Part 4: The role of terminology and ontology for
semantic interoperability
Tuesday August 29th, 2006
Werner Ceusters, MD
Ontology Research Group
Center of Excellence in Bioinformatics & Life Sciences
SUNY at Buffalo, NY
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R T U New York State
Center of Excellence in
Bioinformatics & Life Sciences
The word ‘Terminology’ has two meanings
1) The discipline of terminology management
–
synonymous with terminology work (used in ISO
704)
2) The set of designations used in the special
language of a subject field, such as the
terminology of medicine
–
–
Used in both the singular and plural
Used with an article in the singular: a terminology
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R T U New York State
Center of Excellence in
Bioinformatics & Life Sciences
Origin: Peirce, Ogden & Richards, Wüster
Unit of Thinking (Concept)
(Unit of Thought,
Unit of Knowledge)
Designation
(Symbol, Sign,
Term, Formula
etc.)
Referent
(Concrete Object,
Real Thing,
Conceived Object)
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R T U New York State
Center of Excellence in
Bioinformatics & Life Sciences
Fundamental Activities of Terminology Work
• Identifying ‘concepts’ and ‘concept relations’;
– Analyzing and modeling concept systems on the basis of
identified concepts and concept relations;
– Establishing representations of concept systems through concept
diagrams;
– Crafting concept-oriented definitions;
– Attributing designations (predominantly terms) to each concept
in one or more languages; and,
– Recording and presenting terminological data, principally in
terminological entries stored in print and electronic media
(terminography).
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Center of Excellence in
Bioinformatics & Life Sciences
Why terminologies ?
• As such ?
– Fixing/stabilizing the language within a domain and a
linguistic community;
– Unambiguous communication.
• In Healthcare Information Technology ?
– Semantic Indexing;
– Information exchange and linking between
heterogeneous systems;
– Terminologies as basis for documentation through
coding and classification
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R T U New York State
Center of Excellence in
Bioinformatics & Life Sciences
From terminology to ontology
• Concept/terminology-based systems make implicit
knowledge explicit
• Ontologies aim to push explicitness further:
– reasoning by machines
• Classification
• Prediction
• Triggering of alerts
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R T U New York State
Center of Excellence in
Bioinformatics & Life Sciences
The word ‘Ontology’ has two meanings
• Ontology: the science of what entities exist and
how they relate to each other
• An ontology: a representation of some domain
which
– (1) is intelligible to a domain expert
– (2) is formalized in a way that allows it to support
automatic information processing
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R T U New York State
Center of Excellence in
Bioinformatics & Life Sciences
Within the context of ‘an ontology’,
the word ‘domain’ has two meanings
• For most computer scientists:
– An agreed upon conceptualization about which man
and machine can communicate using an agreed upon
vocabulary
• For philosophical ontologists:
– A portion of reality
• Still allowing for a variety of entities to be recognised by one
school and refuted by another one
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Center of Excellence in
Bioinformatics & Life Sciences
Ontology based on Unqualified Realism
• Accepts the existence of
– a real world outside mind and language
– a structure in that world prior to mind and language
(universals / particulars)
• Rejects ontology as a matter of agreement on
‘conceptualizations’
• Uses reality as a benchmark for testing the quality
of ontologies as artifacts by building appropriate
logics with referential semantics (rather than
model-theoretic)
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Center of Excellence in
Bioinformatics & Life Sciences
Important to distinguish 3 fundamentally
different levels (e.g. in healthcare)
1. the reality on the side of the patient;
2. the cognitive representations of this reality
embodied in observations and interpretations on
the part of patients, clinicians and others;
3. the publicly accessible concretizations of such
cognitive representations in representational
artifacts of various sorts, of which ontologies,
terminologies and EHRs are examples.
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Center of Excellence in
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Relevance for EHR & Semantic Interoperability
The conceptualist approach
R
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Ontology
EHR
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R T U New York State
Center of Excellence in
Bioinformatics & Life Sciences
Relevance for EHR & Semantic Interoperability
The realist approach
R
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K A
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Ontology
EHR
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R T U New York State
Center of Excellence in
Bioinformatics & Life Sciences
For the latter, thus …
• An ontology is
a representation of some
pre-existing domain of reality which
– (1) reflects the properties of the entities within its
domain in such a way that there obtains a systematic
correlation between reality and the representation
itself,
– (2) is intelligible to a domain expert
– (3) is formalized in a way that allows it to support
automatic information processing
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R T U New York State
Center of Excellence in
Bioinformatics & Life Sciences
For the latter, thus …
• An ontology should be a representation of some
pre-existing domain of reality which
– (1) reflects the properties of the entities within its
domain in such a way that there obtains a systematic
correlation between reality and the representation
itself,
– (2) is intelligible to a domain expert
– (3) is formalized in a way that allows it to support
automatic information processing
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R T U New York State
Center of Excellence in
Bioinformatics & Life Sciences
And accept that everything may change:
1. changes in the underlying reality:
• Latex allergy did not exist 200 years ago.
2. changes in our (scientific) understanding:
• Psychoses with hallucinations did exist 600 years ago
but some of them were thought to be diabolic
possessions.
3. reassessments of what is considered to be
relevant for inclusion (notion of purpose).
4. encoding mistakes introduced during data entry
or ontology development.
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Center of Excellence in
Bioinformatics & Life Sciences
Today’s biggest problem: a confusion between
“terminology” and “ontology”
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R T U New York State
Center of Excellence in
Bioinformatics & Life Sciences
For example: some SNOMED definitions
• “Disorders are concepts in which there is an explicit or
implicit pathological process causing a state of disease
which tends to exist for a significant length of time under
ordinary circumstances.”
• But also: “Concepts are unique units of thought”.
• Thus: Disorders are unique units of thoughts in which
there is a pathological process …???
• And thus: to threat all diseases in the world at once we
simply should stop thinking ?????????
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New York State
R T U Important
to
differentiate between
Lexical, semantic and ontological relations
Center of Excellence in
Bioinformatics & Life Sciences
urine
gall bladder
gall
gallbladder
inflammation
bladder
urinary
bladder
biliary cystitis
urine
inflammation
gall
cystitis
inflammation
urinary
bladder
gallbladder
gallbladder
inflammation
urinary bladder
inflammation
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Center of Excellence in
Algorithms
exploiting
thisSciences
distinction
Bioinformatics
& Life
were used to
detect mistakes in several terminologies and ontologies
Ceusters W, Smith B, Kumar A,
Dhaen C.
Mistakes in Medical Ontologies:
Where Do They Come From and
How Can They Be Detected?
in: Pisanelli DM (ed) IOS Press,
Studies in Health Technology and
Informatics, vol 102, 2004.
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Center of Excellence in
Bioinformatics & Life Sciences
One conclusion:
• 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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R T U New York State
Center of Excellence in
Bioinformatics & Life Sciences
Why not ?
• 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.
– Pluto is still the same thing as before although we don’t call it a
‘planet’ anymore
• Language can make strings of words look as if it were
terms
– “Middle lobe of left lung”
– “prevented abortion”
– “cancelled X-Ray”
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Center of Excellence in
Bioinformatics & Life Sciences
What to do about it ? (1)
• Research:
– Revision of the appropriatness of concept-based
terminology for specific purposes
– Relationship between models and that part of reality
that the models want to represent
– Adequacy of current tools and languages for
representation
– Boundaries between terminology and ontology and the
place of each in semantic interoperability in healthcare
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R T U New York State
Center of Excellence in
Bioinformatics & Life Sciences
What to do about it ? (2)
• Training and awareness
– Make people more critical wrt terminology and
ontology promisses
• What is needed must be based on needs, not on the
popularity of a new paradigm
• But in a system, it’s not just your own needs, it is each
component’s needs !
– Towards “an ontology of ontologies”
• First description
• Then quality criteria
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