PHI 637 SEM BMI 708 SEM Werner Ceusters and Barry Smith Lecture 6 Werner Ceusters Using Referent Tracking for building ontologies Classes Aug 31 Systems and techniques for representing biomedical data information and knowledge in ontologies WC ID: 931931
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Slide1
Advanced Topics in Biomedical OntologyPHI 637 SEM / BMI 708 SEM
Werner Ceusters
and Barry Smith
Slide2Lecture 6Werner Ceusters
Using Referent Tracking
for
building ontologies
Slide3Classes
Aug
31: Systems and techniques for representing biomedical data, information and knowledge in ontologies (WC)
Sept
7: Best practice principles for building domain ontologies, terms, and definitions (BS)
Sept
14: Basic Formal Ontology (BS) and the Ontology for General Medical Science (OGMS)Sept 21: Introduction to the Protégé ontology editor and add-on tools (Neil Otte)Sept 28: BFO, OGMS and the OBO Foundry (BS)Oct 5: Using referent tracking for building ontologies (WC)Oct 12: Team exercise: building an ontology (WC)Oct 19: Team exercise: review of term-paper abstracts (WC, BS)Oct 26: Principles for ontology change management in biomedical information systems (WC)Nov 2: Ontological principles for combining healthcare data in big data repositories (WC,BS)Nov 9: Team exercise: use OGMS to improve biomedical informatics resources (WC, BS)Nov 16: Evaluation of ontologies (WC, BS)Nov 30 and Dec 7: Student presentations.
Slide4Team exercise 1October 12: Building an ontology (WC)
class
participants will be divided into groups. The task for each group will
be:
to
identify some area in which ontology methods can be of value in understanding issues related to patient well-being, along the lines illustrated in the
pre-lecture readings. to propose terms and definitions which need to be added (or linked) to OGMS to create a corresponding ontology. to make the results available electronically by the end of class.
Slide5Pre-lecture reading testArp R, Smith B, Spear AD. Building Ontologies with Basic Formal Ontology. MIT Press, 2015, chapter 7.
Hogan
WR and Ceusters W. Diagnosis, misdiagnosis, lucky guess, hearsay, and more: an ontological analysis. Journal of Biomedical Semantics 2016;7(54).
Slide6As announced and agreed upon
Related Class
Assessment: evaluation of …
Final score %
A1
Aug 31
Advance reading test0%A2Sept 21Post-class assignment T28%A3
Oct 5Advance reading test3%
A4
Oct 5
Post-class
assignment T3
8%
A5
Oct 12Advance reading test3%A6Oct 19Individual reviews on abstracts (T5)5%A7Oct 19Group assessment of term paper abstract reviews5%A8Oct 26Post-class assignment T610%A9Nov 2Post-class assignment of Nov 2 (T9)8%A10Nov 30/Dec 7Final paper, including ontology components (T10)30%A11Nov 30/Dec 7Final PP presentation / discussion20%TOTAL100%
Slide7Q1. Definition of is_a (5%)
This BFO definition contains an implicit assumption. Which one?
Slide8Q2. (10%)Give the formal definition for C
continuant_part_of
D.
Slide9Q3.Which of the following relational properties apply to located_in
?
Transitive
Symmetric
Reflexive
Antisymmetric
5% for each correct property, -4% for wrong one, minimum: 0%.
Slide10Q4 (15%)What is different for patient p1 in Fig.2 as compared to Fig.1?
Fig. 1 Fig. 2
Slide11Q5. Assertions can fail at the level of reference and at the level of compound expression. Fill out what is the case for each scenario.
Failure
Type
Description
10%
Disease instantiates a different type than the stated type, but the stated type exists
10%
Disease instantiates a different type than stated, while the stated type of disease does not exist
10%
The disease instance does not exist
10%
The organism instance does not exist. In this case, there could not be a clinical picture properly inferred and thus it is not a misdiagnosis although it could still be an ICE.
10%
The disease inheres in a different organism than the one stated. For example, the doctor mistakenly ascribes Mr. Johnson’s hypertension to his twin.
10%A diagnosis of type 2 diabetes mellitus 5 years ago is wrong because the patient didn’t have the disease at that time, even though the patient has type 2 diabetes today. Also, a diagnosis that the patient has an upper respiratory tract infection today when in reality the infection resolved two weeks ago.
Slide12Answers
Slide13Q1. Definition of is_a
This BFO definition contains an implicit assumption. Which one?
A and B are
occurrent
universals (5%)
Slide14Q2.Give the formal definition for C continuant_part_of
D.
10%
Slide15Q3Which of the following relational properties apply to located_in ?
Transitive (5%)
Symmetric (-4%)
Reflexive (5%)
Antisymmetric (-4%)
Slide16Q4What is different for patient p1 in Fig.2 as compared to Fig.1?
in Fig.2 the diagnosis is wrong. (15%)
Fig. 1 Fig. 2
Slide17Q5. Assertions can fail at the level of reference and at the level of compound expression. Fill out what is the case for each scenario.
Failure
Type
Description
CE (10%)
Disease instantiates a different type than the stated type, but the stated type exists
R (10%)
Disease instantiates a different type than stated, while the stated type of disease does not exist
R (10%)
The disease instance does not exist
R (10%)
The organism instance does not exist. In this case, there could not be a clinical picture properly inferred and thus it is not a misdiagnosis although it could still be an ICE.
CE (10%)
The disease inheres in a different organism than the one stated. For example, the doctor mistakenly ascribes Mr. Johnson’s hypertension to his twin.
CE (10%)A diagnosis of type 2 diabetes mellitus 5 years ago is wrong because the patient didn’t have the disease at that time, even though the patient has type 2 diabetes today. Also, a diagnosis that the patient has an upper respiratory tract infection today when in reality the infection resolved two weeks ago.
Slide18Review of the essentials of Referent Tracking
Slide19Representing specific entities
explicit
reference
to the individual entities relevant to the accurate description of some portion of reality, ...
Ceusters W, Smith B. Strategies for Referent Tracking in Electronic Health Records. J Biomed Inform. 2006 Jun;39(3):362-78.
Slide20Representing specific entities
explicit
reference
to the individual entities relevant to the accurate description of some portion of reality, ...
Ceusters W, Smith B. Strategies for Referent Tracking in Electronic Health Records. J Biomed Inform. 2006 Jun;39(3):362-78.
Slide21Portions of realityentities (= particulars, = instances),
e
.g.: me, my life;
r
elations,
e.g.: the 3-place parthood relation between me, my nose, and the temporal region at which it holds,types, universals, e.g. Nose,defined classes, e.g. Crooked Nose, configurations,e.g. my nose now being part of me.
Slide22Method: IUI assignment
Introduce
an
Instance
Unique
Identifier (IUI) for each relevant particular (individual) entity
Ceusters W, Smith B. Strategies for Referent Tracking in Electronic Health Records. J Biomed Inform. 2006 Jun;39(3):362-78.
235
78
5678
321
322
666
427
Slide23Identifiers and pseudo-identifiers
Representation
Reality
ID-a
ID-b
Entity-1
ID-cEntity-2ID-dEntity-3ID-eEntity-4ID-fEntity-5
Slide24Identifiers and pseudo-identifiers
Representation
Reality
ID-a
ID-b
Entity-1
ID-cEntity-2ID-dEntity-3ID-eEntity-4ID-fEntity-5
Pseudo-identifiers:
ID-a: denotes nothing
ID-b: denotes ambiguously
Singularly unique identifier: ID-c
Non-singularly unique identifiers: ID-f, ID-d, ID-e
Slide25Reality representation
https://www.statnews.com/2016/03/24/appendix-cancer-treatment/
Slide26Reality through representation
https://www.statnews.com/2016/03/24/appendix-cancer-treatment/
t
his man
t
his man
#1
#1
Slide27Reality and representation
https://www.statnews.com/2016/03/24/appendix-cancer-treatment/
t
his man
t
his man
#1
#1
t
his picture part
#2
isAbout
at t
Slide28Reality and
representation
t
his heart
t
his heart
#12
#12
t
his picture part
#245
isAbout
at t
Slide29ConventionThrough x one sees x
.
x stands proxy for
x
.
Alternative: ‘x’ stands proxy for x.
Slide30Configurations through Referent Tracking
When x or y is a continuant:
x
relation
y
at tOtherwise: x relation y Where:x is a particular,relation (at) is a relation between x, y (and t),y is a particular or a type,
t is a BFO:temporal_region,x relation y at
t
is a configuration,
x
relation
y
is
a configuration.portions of reality
Slide31Extending ‘at’ with other time-specifiers
Slide32Referent tracking assertionsWhen x or y is a continuant:
Through: x
relation
y
at
t
One sees: x relation y at tOtherwise:Through: x relation y One sees: x relation y
Slide33Examples of Referent Tracking assertions #1 participantOf
#2
at t1
#2
instanceOf
DiagnosticProcess #1 participantOf #3 at t2 #3 instanceOf Life #1 participantOf #4 at t3 #4 instanceOf SurgicalProcedure #4 precededBy #2 #4 partOf #3 t3 partOf t2
Slide34‘#n’: (globally) singularly unique identifiers #1
participantOf
#2
at t1
#2
instanceOf DiagnosticProcess #1 participantOf #3 at t2 #3 instanceOf Life #1 participantOf #4 at t3 #4 instanceOf SurgicalProcedure #4 precededBy #2 #4 part of #3 t3 partOf t2
Slide35‘tn’: (globally) unique identifiers
#1
participantOf
#2
at t1
#2
instanceOf
DiagnosticProcess
#1
participantOf
#3 at t2 #3 instanceOf Life #1 participantOf #4 at t3 #4 instanceOf SurgicalProcedure #4 precededBy #2 #4 part of #3 t3 partOf t2
Slide36Identifier assignmentYou can only assign an identifier to something existing.
However, besides the existence of the entity, what or how it is precisely does not need to be known.
Slide37Identifier assignmentYou can only assign an identifier to something existing.
However, besides the existence of the entity, what or how it is precisely does not need to be known.
#1
participantOf
#3 at t2
#3
instanceOf
Life
Slide38Identifier assignmentYou can only assign an identifier to something existing.
However, besides the existence of the entity, what or how it is precisely does not need to be known.
#1
participantOf
#3 at t2
#3
instanceOf
Lifet2 can be used as ID for the temporal region during which #1 participates in his life even if nothing is known (yet) about the length of t2.
Slide39Do t1 and t2 denote distinct temporal regions? #1 participantOf
#2
at t1
#2
instanceOf
Life #3 participantOf #4 at t2 #4 instanceOf Life #5 instanceOf MonoZygoticTwinBrotherHood #5 inheresIn #1 at t1 #5 inheresIn #3 at t2
Slide40Do t1 and t2 denote distinct temporal regions? #1 participantOf
#2 at t1
#2
instanceOf
Life
#3
participantOf #4 at t2 #4 instanceOf Life #5 instanceOf MonoZygoticTwinBrotherHood #5 inheresIn #1 at t1 #5 inheresIn #3 at t2We will be able to tell when at least one of the twins dies:If only one: no.If both at the same time: yes.
Slide41Capacities for reasoners #1 participantOf
#2
at t1
#2
instanceOf DiagnosticProcess #1 participantOf #3 at t2 #3 instanceOf Life #1 participantOf #4 at t3 #4 instanceOf SurgicalProcedure #4 precededBy #2 #4 partOf #3 t3 partOf t2
Slide42Careful though ! #1 participantOf
#2
at t1
#2
instanceOf
DiagnosticProcess #1 participantOf #3 at t2 #3 instanceOf Life #1 participantOf #4 at t3 #4 instanceOf SurgicalProcedure #4 precededBy #2 #4 partOf #3 t3 partOf t2How does t1 relates to #2 ?
Slide43Careful though ! #1 participantOf
#2
at t1
#2
instanceOf
DiagnosticProcess #1 participantOf #3 at t2 #3 instanceOf Life #1 participantOf #4 at t3 #4 instanceOf SurgicalProcedure #4 precededBy #2 #4 partOf #3 t3 partOf t2How does t2 relates to #3 ?
Slide44RememberThrough: #1 partOf #2
at
t1
One sees:
#1
partOf
#2 at t1
Slide45Referent tracking assertions are realThrough: #1 partOf #2
at
t1
One sees:
#1
partOf
#2 at t1
Slide46Referent tracking assertions are realThrough: #1 partOf #2
at
t1
One sees:
#1
partOf
#2 at t1Thus we can assign identifiers to these assertions:#3 stands proxy for #1 partOf #2 at t1And we can write:#3 isAbout #1 at t3,#3 isAbout #2 at t3, …This is important for referent tracking systems which keep track of the faithfulness of its representations, but not for today’s exercise (and the assignment).
Slide47Use of Referent TrackingAbove all:
Representation of what is the case for particulars in some portion of reality:
Electronic healthcare systems
Gazetteers
Product or system maintenance systems.
But also:
As an aid to build application ontologies.Forces you to think better about temporal aspects!
Slide48Time not visible anymore BFO-ontologiesC isa
C
1 = [
def
for continuants]
for all c, t, if c instance_of C at t then c instance_of C1 at t. C continuant_part_of C1 = [def] for all c, t, if c instance_of C at t
then there is some c1 such that c1 instance_of C1 at t
and
c
continuant_
part_of
c1 at t.
Slide49You must keep time in mind when crafting definitions!‘Persistent idiopathic facial pain (PIFP)
’
= ‘
persistent facial pain with varying presentations …’
t
1
t
2
t
3
t
1
t
2
t
3
t
1
t
2
t
3
t
1
t
2
t
3
t
1
t
2
t
3
t
1
t
2
t
3
persistent
facial pain
presentation
type1
presentation
type3
presentation
type2
types
my pain
his pain
her pain
parti
-
culars
Slide50‘Persistent idiopathic facial pain (PIFP)’ = ‘persistent facial pain with varying presentations …’
if the description is about types, then the
three
particular
pains fall under PIFP.if the description is about (arbitrary) particulars, then only her pain falls under PIFP.
You must keep time in mind when crafting definitions!
Slide51Tracking aggregates and extensions
types
particulars
A
i
nstanceOf
at t1
B
Slide52Tracking aggregates and extensions
types
particulars
A
i
nstanceOf
at t1
B
i
nstanceOf
at t2
i
nstanceOf
at t1 and t2
Slide53Tracking aggregates and extensions
types
particulars
A
i
nstanceOf
at t1
B
i
nstanceOf
at t2
i
nstanceOf
at t1 and t2
Slide54In class exercise
Slide55Today’s analysis domain (1)What are headache disorders?Headache disorders, characterized by recurrent headache, are among the most common disorders of the nervous system. Headache itself is a painful and disabling feature of a small number of primary headache disorders, namely migraine, tension-type headache, and cluster headache. Headache can also be caused by or occur secondarily to a long list of other conditions, the most common of which is medication-overuse headache.
WHO. Headache disorders. Fact sheet. Updated
April
2016.
Retrieved
from http://www.who.int/mediacentre/factsheets/fs277/en
/ on Oct 3, 2017.
Slide56Today’s analysis domain (2)Tension-type headache (TTH)TTH is the most common primary headache disorder.
Episodic TTH
, occurring
on fewer than 15 days per month, is reported by more than 70% of some populations.
Chronic TTH, occurring on more than 15 days per month, affects 1-3% of adults.
TTH often begins during the teenage years, affecting three women to every two men.
Its mechanism may be stress-related or associated with musculoskeletal problems in the neck.Episodic TTH attacks usually last a few hours, but can persist for several days.Chronic TTH can be unremitting and is much more disabling than episodic TTH.This headache is described as pressure or tightness, often like a band around the head, sometimes spreading into or from the neck.WHO. Headache disorders. Fact sheet. Updated April 2016.Retrieved from http://www.who.int/mediacentre/factsheets/fs277/en/ on Oct 3, 2017.
Slide57TaskDevelop an application ontology for all types of entities instantiations of which on the side of the patient need to be assayed to be able to be used in an interpretive process to determine the disease course of a patient with TTH up to the level of granularity provided by the domain description.
Build the
isa
– taxonomy plus other relations.
How many possible disease course types are there for TTH at the provided level of granularity?
Slide58After-class exerciseRead the alert fatigue paper and
propose terms and definitions which need to be
mapped
to OGMS to create an ontology to address alert fatigue in EHRs. Due date:
Oct 11;
*
Or: terms and definitions for entities mapped to OGMS needed for some alert mechanism relevant to your project. * prior agreement needed