Challenges in Making Data Understandable to Computers

1. MHI501 – Introduction to Health InformaticsKey Challenges for MHI in making data understandable tocomputersSUNY at Buffalo - December 5, 2007 Werner CEUSTERS Center of Excellence in Bioinformatics and Life Sciences University at Buffalo, NY, USA http://www.org.buffalo.edu/RTU

2. A digital copy of the world Ultimate goal

3. The requirements are the challenges • R1: A faithful representation of reality • R2 … of everything that is digitally registered, what is generic scientific theories what is specific what individual entities exist and how they relate • R3: … throughout reality’s entire history, • R4 … which is computable in order to … … allow queries over the world’s past and present, … make predictions, … fill in gaps, … identify mistakes, ...

4. In fact … the ultimate crystal ball

5. The ‘binding’ wall How to do it right ?

6. The requirements are the challenges • R1: A faithful representation of reality • R2 … of everything that is digitally registered, what is generic scientific theories what is specific what individual entities exist and how they relate • R3: … throughout reality’s entire history, • R4 … which is computable in order to … … allow queries over the world’s past and present, … make predictions, … fill in gaps, … identify mistakes, ...

7. R1: A faithful representation of reality … … recognizes three levels: • The (first order) reality which exists ‘as it is’ prior to a cognitive agent’s perception thereof; • the cognitive representations of this reality embodied in observations and interpretations on the part of cognitive agents; • the publicly accessible concretizations constructed through cognitive insights as artifacts representing first order reality of which ontologies, terminologies and data repositories are examples. Smith B, Kusnierczyk W, Schober D, Ceusters W. Towards a Reference Terminology for Ontology Research and Development in the Biomedical Domain. Proceedings of KR-MED 2006, November 8, 2006, Baltimore MD, USA

8. Get down that wall Basic Formal Ontology: teaches us how to build an adequate grid. Granular Partition Theory: relates the copy to reality.

9. But … • This is not part of mainstream thinking • Dominant prevailing paradigm: • Focus on ‘concepts’ (and don’t ask what ‘concepts’ actually are) • Leave it to computer scientists and data modeling consultants

10. The requirements are the challenges • R1: A faithful representation of reality • R2 … of everything that is digitally registered, what is generic scientific theories what is specific what individual entities exist and how they relate • R3: … throughout reality’s entire history, • R4 … which is computable in order to … … allow queries over the world’s past and present, … make predictions, … fill in gaps, … identify mistakes, ...

11. The reality: a digital copy of part of the world Applying the grid does not give a distorted representation of reality, but only an incomplete representation !!!

12. Key issue: keeping track of what the bits denote

13. Key issue: keeping track of what the bits denote • Images are no good: • Are too complex particulars in their own right that stand in another sort of relation to the part of reality that they depict. • Terms / names ? Middle-East Madagascar Katrina

14. Names are inadequate representational units • “JFK” “Enola Gay” • “Barry Smith” “George Bush”

15. denotes denotes denotes Relationship managed in the RTS IUI: Instance Unique Identifiers 5241 89023 109427

16. Referent Tracking System Components • Referent Tracking Software Manipulation of statements about facts and beliefs • Referent Tracking Datastore: • IUI repository A collection of globally unique singular identifiers denoting particulars • Referent Tracking Database A collection of facts and beliefs about the particulars denoted in the IUI repository Manzoor S, Ceusters W, Rudnicki R. Implementation of a Referent Tracking System. International Journal of Healthcare Information Systems and Informatics 2007;2(4):41-58.

17. But … • Not yet tested in real life • Difficult to understand • Societal barriers: • Big Brother complex • N(ot) I(nvented) H(ere) syndrome • Publication bias

18. The requirements are the challenges • R1: A faithful representation of reality • R2 … of everything that is digitally registered, what is generic scientific theories what is specific what individual entities exist and how they relate • R3: … throughout reality’s entire history, • R4 … which is computable in order to … … allow queries over the world’s past and present, … make predictions, … fill in gaps, … identify mistakes, ...

19. Eternal memory

20. Accept that everything may change: • changes in the underlying reality: • Particulars come, change and go • changes in our (scientific) understanding: • The plant Vulcan does not exist • reassessments of what is considered to be relevant for inclusion (notion of purpose). • encoding mistakes introduced during data entry or ontology development.

21. But … • Current computational and representational facilities are unsatisfactory

22. The requirements are the challenges • R1: A faithful representation of reality • R2 … of everything that is digitally registered, what is generic scientific theories what is specific what individual entities exist and how they relate • R3: … throughout reality’s entire history, • R4 … which is computable in order to … … allow queries over the world’s past and present, … make predictions, … fill in gaps, … identify mistakes, ...