1. Sharing Ontologies in the Biomedical Domain Alexa T. McCray National Library of Medicine National Institutes of Health Department of Health & Human Services USA SOFG November 19, 2002

2. Unified Medical Language (UMLS) System Problem the UMLS is attempting to solve: - Provide integrated access to biomedical information in disparate biomedical information systems Bibliographic, factual databases, decision support systems, knowledge-based systems

3. UMLS Knowledge Sources (2002) Metathesaurus - 871,000 concepts - 2.1 million strings Specialist lexicon & lexical programs - 180,000 lexical entries - Java-based lexical tools Semantic Network - 134 semantic types, 54 relationships

4. Metathesaurus Integrates more than 60 families of vocabularies - multiple translations (MeSH, ICPC, WHOART) - multiple versions (ICD: 9-10; DSM IIIR) Vocabularies vary in nature, size, scope

5. UMLS Vocabularies Developed for varying purposes - Information retrieval (MeSH) - Coding medical records (CPT) - Epidemiology (ICD) - Decision support (AI/Rheum) Coverage - Specific specialty (PDQ, DSM, NANDA) - Specific field of study (Digital Anatomist)

6. Broad Coverage Vocabularies SNOMED - Large clinical vocabulary MeSH - 19,000 terms - Anatomy, biology, physiology, organisms, disease, chemicals - Molecular biology & genetics Cytogenetics, medical genetics, genetic recombination, mutations

7. Variety of Conceptualizations Different representations of the domain of interest - List of basic concepts in the domain - Concepts together with relationships among the concepts Taxonomic relationships Non-hierarchical relationships - Concepts, relationships, constraints on interpretation

8. Mapping Issues Same string, different meaning Different string, same meaning - Unrecognized synonymy Different string, similar meaning - Unrecognized relationship Implicit rules, conventions Implicit hierarchies - Variety of relationships

9. Common UMLS Representation One concept, multiple terms and strings - renal cell carcinoma CUI: C0007134, LUI: L0007134, SUI:S0425056 - renal cell carcinomas CUI: C0007134, LUI: L0007134, SUI:S0081526 - hypernephroma CUI: C0007134, LUI: L0020489, SUI:S0420320 - Grawitz tumor CUI: C0007134, LUI: L0018219, SUI:S0375417

10. SPECIALIST lexicon More than 180,000 lexical items in the biomedical domain Word properties - morphology - orthography - syntax Developed for natural language processing applications

11. Lexical tools Manage lexical variation - Perform lexical transformations Generate inflectional variants, normalized forms Depend on SPECIALIST lexicon Used for preliminary algorithmic mapping as new vocabularies are added

12. UMLS Semantic Network Upper level ontology for the UMLS - Provides overarching conceptual framework for all UMLS concepts Each concept assigned to one or more semantic types Internal structure of constituent vocabularies also maintained

13. Semantic Network 134 semantic types: broad categories - Disease or Syndrome - Body Part, Organ, or Organ Component 54 semantic relationships - hierarchical: is a kind of (isa) - non-hierarchical (location_of, caused_by)

14. Semantic Network Semantic types - 2 major hierarchies Entity - Physical Object - Conceptual Entity Event - Activity - Phenomenon or Process

15. Body System Body Space or Junction Body Location or Region Entity Physical ObjectConceptual Entity Substance Idea or Concept Functional Concept Spatial Concept Body Substance Embryonic Structure Fully Formed Anatomical Structure Body Part, Organ or Organ Component TissueCell Component Gene or Genome Anatomical Structure Congenital Abnormality Acquired Abnormality Anatomical Abnormality Portion of the Entity Hierarchy

16. UMLS Semantic Network Relationships

17. Semantic Network Relationship between a pair of semantic types is a possible link between the concepts assigned to those semantic types - Relationship may or may not hold at the concept level A child semantic type inherits properties from its parents

18. A Portion of the UMLS Semantic Network

19. UMLS Coverage of the Genomic Domain Some genomic terminology in existing vocabularies Integrated NCBI organism taxonomy - Over 100,000 organism names Coverage determined by publicly available sequences Currently working with GO consortium to integrate Gene Ontology Conducting experiments with mapping Online Mendelian Inheritance in Man (OMIM)

20. UMLS Knowledge Source Server (UMLSKS) Provides Internet access to all UMLS Knowledge Sources - Web interface - API UMLS Knowledge Source Server – Vers. 2.0 - Java-based object model - Flexible output facilities XML-encoded data

25. URL’s for the UMLS project http://umlsinfo.nlm.nih.gov/ http://umlsks.nlm.nih.gov/