1. Limning the CTS Ontology Landscape Barry Smith http://ontology.buffalo.edu/smith 1

2. Basic science (e.g. pharma data) Hospital #1 data Hospital #2 data Lab#1 data Clinic #1 data HIPAA Basic science data Data Warehouse Public Non-public What exists translation 2

3. With thanks to Tom Beale, Ocean Informatics Enterprise Comprehensive Basic Components EHR Multimedia genetics workflow identity Clinical ref data Clinical models terms Security / access control realtime gateway telemedicine HILS other provider UPDATE QUERY demographics guidelines protocols Interactions DS Local modelling notifications DSSPAS billing portal Allied health patient PAYER Msg gateway Imaging lab ECG etc Path lab LAB Secondary users Online drug, Interactions DB Online archetypes Online terminology Online Demographic registries Patient Record

4. Basic science (e.g. pharma data) Hospital #1 data Hospital #2 data Lab#1 data Clinic #1 data HIPAA Basic science data Data Warehouse Public Non-public What every CTS institution would like to have translation 4

5. Basic science (e.g. pharma data) Hospital #1 data Hospital #2 data Lab#1 data Clinic #1 data HIPAA Basic science data Data Warehouse Public Non-public More (and better?) EHR data translation 5 “Meaningful Use” Coding Systems

6. Basic science (e.g. pharma data) Hospital #1 data Hospital #2 data Lab#1 data Clinic #1 data HIPAA Basic science data Data Warehouse Public Non-public Strategies to overcome the complexity and incompatibility of coding schemes of EHRs translation 6 “Meaningful Use” Coding Systems i2b2 (with ontology cells) HOM (Health Ontology Mapper

7. Coding schemes and terminologies ICD, SNOMED, … – are slow to change – do not interoperate well with structured basic biology data – are not fully open source – are tied to multiple competing EHR systems – are not optimized for research And therefore – do not support translation 7

8. Hospital #1 data Hospital #2 data Roswell data Clinic #1 data HIPAA Basic science data Data Warehouse Public Basic science (e.g. pharma data) Non-public It is generally recognized that ontologies must play some part in the solution to these problems i2b2 (with ontology cells) HOM (Health Ontology Mapper 8 Gene Ontology

9. Hospital #1 data Hospital #2 data Roswell data Clinic #1 data HIPAA Basic science data Data Warehouse Public Basic science (e.g. pharma data) Non-public Proposed solution: extend the Gene Ontology with a consistent set of small, agile, open ontology modules for clinical domains 9 Open Biomedical Ontologies Foundry

10. RELATION TO TIME GRANULARITY CONTINUANTOCCURRENT INDEPENDENTDEPENDENT ORGAN AND ORGANISM Organism (NCBI Taxonomy) Anatomical Entity (FMA, CARO) Organ Function (FMP, CPRO) Phenotypic Quality (PaTO) Biological Process (GO) CELL AND CELLULAR COMPONENT Cell (CL) Cellular Component (FMA, GO) Cellular Function (GO) MOLECULE Molecule (ChEBI, SO, RnaO, PrO) Molecular Function (GO) Molecular Process (GO) Open Biomedical Ontologies (OBO) Foundry (First Draft) 10

11. OBO Foundry approach extended into other domains 11 NIF StandardNeuroscience Information Framework ISF OntologiesIntegrated Semantic Framework OGMS and ExtensionsOntology for General Medical Science IDO ConsortiumInfectious Disease Ontology cROPCommon Reference Ontologies for Plants

12. OGMS and Its Extensions Ontology of Medically Relevant Social EntitiesOntology of Medically Relevant Social Entities (OMRSE) Vital Sign OntologyVital Sign Ontology (VSO) Mental Diseases Examples of OGMS applied to specific diseases. Oral Health and Disease ontology Infectious Disease OntologyInfectious Disease Ontology (IDO) http://code.google.com/p/ogms/ 12

13. IDO and Its Extensions IDO – Brucellosis IDO – Dengue Fever IDO – Influenza IDO – Malaria IDO – Staphylococcus Aureus Bacteremia IDO - Vector Surveillance and Management VO – Vaccine Ontology 13

14. Hospital #1 data Hospital #2 data Roswell data Clinic #1 data HIPAA Data Warehouse Public Basic science (e.g. pharma data) Non-public Alzheimer’s Disease Staph Aureus Bacteremia Using OGMS as basis, create small ontologies for specific clinical domains Sleep Dis- orders 14 Open Biomedical Ontologies Foundry Basic science data

15. Hospital #1 data Hospital #2 data Roswell data Clinic #1 data HIPAA Basic science data Data Warehouse Basic science (e.g. pharma data) Non-public Extend this approach to the workings of the CTS institution itself Clinical Neurology Cancer Pathology etc. Resource data Publications, patents, equipment, samples, expertise, grants, lab activities, clinical research activities, clinical trials Semi-public 15

16. Hospital #1 data Hospital #2 data Roswell data Clinic #1 data HIPAA Data Warehouse Basic science (e.g. pharma data) Non-public Extend this approach to the workings of the CTS institution itself Clinical Trial Ontology Consent Ontology etc. Resource data Publications, patents, equipment, samples, expertise, grants, lab activities, clinical research activities, clinical trials Semi-public 16 OBI : Ontology for Biomedical Investigations OGMS Open Biomedical Ontologies Foundry