1. Advanced Topics in Biomedical Ontology PHI 637 SEM / BMI 708 SEM
Werner Ceusters and Barry Smith

2. Lecture 6 Werner Ceusters
Using Referent Tracking
for
building ontologies

3. Classes
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.

4. Team exercise 1 October 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.

5. Pre-lecture reading test
Arp 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).

6. As announced and agreed upon
Related Class
Assessment: evaluation of …
Final score % A1
Aug 31
Advance reading test 0% A2
Sept 21
Post-class assignment T2 8% A3
Oct 5 3% A4
Post-class assignment T3 A5
Oct 12 A6
Oct 19
Individual reviews on abstracts (T5) 5% A7
Group assessment of term paper abstract reviews A8
Oct 26
Post-class assignment T6
10% A9
Nov 2
Post-class assignment of Nov 2 (T9)
A10
Nov 30/Dec 7
Final paper, including ontology components (T10)
30%
A11
Final PP presentation / discussion
20%
TOTAL
100%

7. Q1. Definition of is_a (5%)
This BFO definition contains an implicit assumption. Which one?

8. Give the formal definition for C continuant_part_of D.
Q2. (10%)
Give the formal definition for C continuant_part_of D.

9. Q3. 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%.

10. Q4 (15%)
What is different for patient p1 in Fig.2 as compared to Fig.1? Fig. 1 Fig. 2

11. Q5. 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
Disease instantiates a different type than stated, while the stated type of disease does not exist
The disease instance does not exist
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.
The disease inheres in a different organism than the one stated. For example, the doctor mistakenly ascribes Mr. Johnson’s hypertension to his twin.
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.

12. Answers

13. Q1. Definition of is_a
This BFO definition contains an implicit assumption. Which one?  A and B are occurrent universals (5%)

14. Give the formal definition for C continuant_part_of D. 10%
Q2.
Give the formal definition for C continuant_part_of D. 10%

15. Q3 Which of the following relational properties apply to located_in ?
Transitive (5%)
Symmetric (-4%)
Reflexive (5%)
Antisymmetric (-4%)

16. Q4
What 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

17. Q5. 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
The disease instance does not exist
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.
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.

18. Review of the essentials of Referent Tracking

19. Representing 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 Jun;39(3):

20. Representing 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 Jun;39(3):

21. Portions of reality entities (= particulars, = instances),
e.g.: me, my life;
relations,
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.

22. Method: IUI assignment
Introduce an Instance Unique Identifier (IUI) for each relevant particular (individual) entity
235 78
5678
321
322
666
427
Ceusters W, Smith B. Strategies for Referent Tracking in Electronic Health Records. J Biomed Inform Jun;39(3):

23. Identifiers and pseudo-identifiers
Representation
Reality
ID-a
ID-b
Entity-1
ID-c
Entity-2
ID-d
Entity-3
ID-e
Entity-4
ID-f
Entity-5

24. Identifiers and pseudo-identifiers
Representation
Reality
ID-a
ID-b
Entity-1
ID-c
Entity-2
ID-d
Entity-3
ID-e
Entity-4
ID-f
Entity-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

25. Reality representation

26. Reality through representation
this man
this man #1 #1

27. Reality and representation
this man
this picture part
this man #1 #2 #1
isAbout at t

28. Reality and representation
this heart
this picture part
this heart
#12
#245
#12
isAbout at t

29. Convention Through x one sees x. x stands proxy for x.
Alternative: ‘x’ stands proxy for x.

30. Configurations through Referent Tracking
When x or y is a continuant:
x relation y at t
Otherwise:
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

31. Extending ‘at’ with other time-specifiers

32. Referent tracking assertions
When x or y is a continuant:
Through: x relation y at t
One sees: x relation y at t
Otherwise:
Through: x relation y
One sees: x relation y

33. Examples 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

34. ‘#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

35. ‘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

36. Identifier assignment
You 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.

37. Identifier assignment
You 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

38. Identifier assignment
You 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
t2 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.

39. Do 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

40. Do 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
We will be able to tell when at least one of the twins dies:
If only one: no.
If both at the same time: yes.

41. Capacities 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

42. Careful 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 t2 How does t1 relates to #2 ?

43. Careful 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 t2 How does t2 relates to #3 ?

44. Remember
Through: #1 partOf #2 at t1
One sees: #1 partOf #2 at t1

45. Referent tracking assertions are real
Through: #1 partOf #2 at t1
One sees: #1 partOf #2 at t1

46. Referent tracking assertions are real
Through: #1 partOf #2 at t1
One sees: #1 partOf #2 at t1
Thus we can assign identifiers to these assertions:
#3 stands proxy for #1 partOf #2 at t1
And 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).

47. Use of Referent Tracking
Above 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!

48. Time not visible anymore BFO-ontologies
C isa C1 = [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]
then there is some c1 such that
c1 instance_of C1 at t
and c continuant_part_of c1 at t.

49. You must keep time in mind when crafting definitions!
‘Persistent idiopathic facial pain (PIFP)’
= ‘persistent facial pain with varying presentations …’
persistent
facial pain
presentation
type1
type3
type2
types t1 t2 t3 t1 t2 t3 t1 t2 t3
my pain
his pain
her pain
parti-
culars

50. You must keep time in mind when crafting definitions!
‘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.

51. Tracking aggregates and extensionsB
types
instanceOf at t1
particulars

52. Tracking aggregates and extensionsB
types
instanceOf at t2
instanceOf at t1 and t2
instanceOf at t1
particulars

53. Tracking aggregates and extensionsB
types
instanceOf at t2
instanceOf at t1 and t2
instanceOf at t1
particulars

54. In class exercise

55. Today’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 on Oct 3, 2017.

56. Today’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 on Oct 3, 2017.

57. Task
Develop 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?

58. After-class exercise
Read 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