1. Animating the reference terminology – showing classifiers at work
Ed Cheetham, Principal Terminology Specialist

2. Introduction
In addition to being hand-curated, SNOMED CT’s content is also (re-)organised, and its development quality assured, by the use of a description logic (DL) classifier.

3. What is description logic? [Spackman 2008]
Mathematical viewpoint:
A family of logics characterized by Formal set-theoretic semantics
Proofs of correctness and completeness of computation
Proofs of algorithmic complexity (PSpace, NP-complete, NExpTime, etc)
Knowledge representation viewpoint:
A set of constructs for representing terminological knowledge
Algorithms and their implementations for performing:
Subsumption (testing pairs of expressions to see whether one is a subtype of the other & vice versa)
Classification (structuring a set of expressions according to their subsumptionrelationships)

4. DL-based classification – simply put...
AND, OR, NOT, Roles, Role hierarchies
Agree ‘set of constructs’ [operators, roles]
Make certain properties of content formally explicit
‘Stated relationships
Decide whether content is sufficiently defined in such terms
Fully defined/primitive
‘Run’ classifier
Defined – what are kinds of ‘me’? What am I a kind of?
Primitive – what am I a kind of?
Appendectomy Is_A Excision procedure AND
Has_method=Excision AND
Has_site=Appendix
Appendectomy Fully defined
Operation GI tract Fully defined
Excision, Appendix Primitive
Total
Is A
Role
Stated
778435
525350
253085
Inferred
611737
423459

5. Protégé: http://protege.stanford.edu/
Illustrative modular ontology showing stated view of ‘appendectomy’
Protégé:
Use does not indicate endorsement, but extremely valuable to illustrate points discussed

6. Illustrative modular ontology showing inferred (post-classification) view of ‘appendectomy’

7. Screen grab of protégé OWL viz plugin – stated view of illustrative appendectomy data

8. Screen grab of protégé OWL viz plugin – inferred view of illustrative appendectomy data

9. Gephi: http://gephi.org/
Transition slide to introduce Gephi forced directed layout of appendectomy example
Gephi:
Use does not indicate endorsement, but extremely valuable to illustrate points discussed

10. Example classes illustrated...

11. And role relations (to structures) ...

12. And role relations (to methods) ...

13. And alternative (abstract class)

14. Blue lines = stated and inferred
Red lines = stated (removed as redundant)
Slide introducing animation of pre-post classification of appendectomy using Gephi to display (actual classification done elsewhere).
Animation slide cannot be included due to file size.
Green lines = inferred

15. Slide introducing animation of pre-post classification of appendectomy & appendicitis using Gephi to display (actual classification done elsewhere).
Animation slide cannot be included due to file size.

16. Example classes...

17. Example classes...

18. Conclusions
DL-based classification is an intrinsic part of SNOMED CT development
Necessary QA feature of large KR product
Based on ‘what it is told’ and the expressivity of the other ‘constructs’, content is ruthlessly reorganised
New ‘inferred’ knowledge (reclassification)
Sometimes intended, sometimes unintended