1. 1 Workshop 7.00 Welcoming Remarks 7.15 Barry Smith (Buffalo, NY) 7.40 Lindsay Cowell (Duke University, NC) 8.05 Nigam Shah (Stanford University, CA) 8.30 Break 8.40 Dave Parrish (Immune Tolerance Network, PA) 9.05 Yannick Legre (Healthgrid, France)

2. 2 The OBO Foundry: From Basic Biology to Genomic Medicine Barry Smith University at Buffalo National Center for Biomedical Ontology http://ontology.buffalo.edu/smith

3. 3

4. 4 where in the body ? where in the cell ? what kind of disease process ?

5. 5 UMLS, Semantic Web, Moby, wikis, etc.  let a million flowers bloom  integration relies on post hoc mappings how create broad-coverage semantic annotation systems for biomedicine?

6. 6 for science create an evolutionary path towards evidence-based terminology a new approach

7. 7 a shared portal for 60+ ontologies (low regimentation) http://obo.sourceforge.net First step (2001)

8. 8

9. Second step (2004): logic-based reform efforts GO linked to other OBO ontologies id: CL:0000062 name: osteoblast def: "A bone-forming cell which secretes an extracellular matrix. Hydroxyapatite crystals are then deposited into the matrix to form bone." is_a: CL:0000055 relationship: develops_from CL:0000008 relationship: develops_from CL:0000375 GO Cell type New Definition + = Osteoblast differentiation: Processes whereby an osteoprogenitor cell or a cranial neural crest cell acquires the specialized features of an osteoblast, a bone-forming cell which secretes extracellular matrix.

10. 10 The OBO Foundry http://obofoundry.org/ Third step (2006)

11. 11 a family of interoperable gold standard biomedical reference ontologies to serve the annotation of  model organism databases  scientific literature  clinical data  experimental resultshttp://obofoundry.org/

12. 12 Foundry developers have agreed in advance to accept a common set of principles designed to ensure  compatibility  interoperability  formal robustnesshttp://obofoundry.org/

13. 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) Building out fron the original GO http://obofoundry.org/

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

15. 15 OntologyScopeURLCustodians Cell Ontology (CL) cell types from prokaryotes to mammals obo.sourceforge.net/cgi- bin/detail.cgi?cell Jonathan Bard, Michael Ashburner, Oliver Hofman Chemical Entities of Bio- logical Interest (ChEBI) molecular entitiesebi.ac.uk/chebi Paula Dematos, Rafael Alcantara Common Anatomy Refer- ence Ontology (CARO) anatomical structures in human and model organisms (under development) Melissa Haendel, Terry Hayamizu, Cornelius Rosse, David Sutherland, Foundational Model of Anatomy (FMA) structure of the human body fma.biostr.washington. edu JLV Mejino Jr., Cornelius Rosse Functional Genomics Investigation Ontology (FuGO) design, protocol, data instrumentation, and analysis fugo.sf.netFuGO Working Group Gene Ontology (GO) cellular components, molecular functions, biological processes www.geneontology.orgGene Ontology Consortium Phenotypic Quality Ontology (PaTO) qualities of anatomical structures obo.sourceforge.net/cgi -bin/ detail.cgi? attribute_and_value Michael Ashburner, Suzanna Lewis, Georgios Gkoutos Protein Ontology (PrO) protein types and modifications (under development)Protein Ontology Consortium Relation Ontology (RO) relationsobo.sf.net/relationshipBarry Smith, Chris Mungall RNA Ontology (RnaO) three-dimensional RNA structures (under development)RNA Ontology Consortium Sequence Ontology (SO) properties and features of nucleic sequences song.sf.netKaren Eilbeck

16. 16  Disease Ontology (DO)  Biomedical Image Ontology (BIO)  Upper Biomedical Ontology (OBO UBO)  Environment Ontology (EnvO)  Systems Biology Ontology (SBO) Under consideration: http://obofoundry.org/

17. 17 CRITERIA  The ontology is open and available to be used by all.  The ontology is in, or can be instantiated in, a common formal language.  The developers of the ontology agree in advance to collaborate with developers of other OBO Foundry ontology where domains overlap. CRITERIA http://obofoundry.org/

18. 18 CRITERIA  UPDATE: The developers of each ontology commit to its maintenance in light of scientific advance, and to soliciting community feedback for its improvement.  ORTHOGONALITY: They commit to ensuring that there is community convergence on a single controlled vocabulary for each domain http://obofoundry.org/

19. 19 CRITERIA  IDENTIFIERS: The ontology possesses a unique identifier space within OBO.  VERSIONING: The ontology provider has procedures for identifying distinct successive versions.  The ontology includes textual definitions for all terms. CRITERIA http://obofoundry.org/

20. 20  CLEARLY BOUNDED: The ontology has a clearly specified and clearly delineated content.  DOCUMENTATION: The ontology is well- documented.  USERS: The ontology has a plurality of independent users. CRITERIA http://obofoundry.org/

21. 21  COMMON ARCHITECTURE: The ontology uses relations which are unambiguously defined following the pattern of definitions laid down in the OBO Relation Ontology.* * Smith et al., Genome Biology 2005, 6:R46 CRITERIA http://obofoundry.org/

22. 22 Ontology of Biomedical Investigations with thanks to Trish Whetzel (FuGO Working Group) FuGO = Functional Genomics Investigation Ontology OBI née FuGO http://obofoundry.org/

23. 23 controlled vocabulary for biomedical investigations including  protocols  instrumentation  material  data  types of analysis and statistical tools applied to the data OBI http://obofoundry.org/

24. 24 OBI Collaborating Communities Crop sciences Generation Challenge Programme (GCP), Environmental genomics MGED RSBI Group, www.mged.org/Workgroups/rsbi Genomic Standards Consortium (GSC), www.genomics.ceh.ac.uk/genomecatalogue HUPO Proteomics Standards Initiative (PSI), psidev.sourceforge.net Immunology Database and Analysis Portal, www.immport.org Immune Epitope Database and Analysis Resource (IEDB), http://www.immuneepitope.org/home.do International Society for Analytical Cytology, http://www.isac-net.org/ Metabolomics Standards Initiative (MSI), Neurogenetics, Biomedical Informatics Research Network (BIRN), Nutrigenomics MGED RSBI Group, www.mged.org/Workgroups/rsbi Polymorphism Toxicogenomics MGED RSBI Group, www.mged.org/Workgroups/rsbi Transcriptomics MGED Ontology Group

25. 25 Clinical Trial Ontology To serve merger of data schemas To serve flexibility of collaborative clinical trial research To serve design and management of clinical trials To serve data access and reuse – send me all trials which...

26. 26 Randomized controlled trials http://rctbank.ucsf.edu/ontology/outline/index.htm RCT Schema – a ‘frame-based ontology’ supporting TrialBank RCT

27. 27 RCT Top-Level Class Hierarchy Root –Secondary-study –Trial-details –Trial –Concept Generic-concept Population-concept Protocol-concept Design-concept Outcome-concept Administrative-concept Intervention-concept

28. 28 RCT: Trial Details Trial-details Erratum Publication-details Conclusion-details Background-details Stopping-details Retraction-details Correction-details Fraud-details

29. 29 –Concept Generic-concept –Term-information –Time-entity –Rule-concept –Situation Population-concept –Subgroup –Population –Recruitment Protocol-concept –Follow-up-activity RCT: Concept

30. 30

31. 31 Ontology vs. Schema Separate development of medical ontologies and terminologies such as SNOMED and medical information models and database schemas Rector, et al., Binding Ontologies and Coding Systems to Electronic Health Records and Messages

32. 32 Ontology vs. Schema diabetes => disease diabetes => string temperature => quality temperature => integer

33. 33 Valid Specifications for data structures “Valid diabetic data structures have: a topic of code for diabetes, a diagnosis code that is diabetes or one of its subcodes, and a brittleness code that is one of the subcodes for diabetic brittlenes and nothing else” Ontology “All diabetes are metabolic diseases” “John has diabetes & it is brittle and long- standing”

34. 34 –Concept Administrative-concept –Publication-concept –Study-site –Person Intervention-concept –Blinding-concept –Intervention-step –Intervention RCT: Concept

35. 35 Two kinds of entities occurrents (processes, events, happenings) continuants (objects, qualities, states...) You are a continuant Your life is an occurrent

36. 36 An instrument is a continuant A protocol is a continuant A trial is an occurrent A selection process is an occurrent Two kinds of entities

37. 37 OBI Top Level

38. 38 OBO Occurrent

39. 39 CTO

40. 40 CTO Continuant

41. 41 CTO Occurrent

42. 42 Clinical Trial Ontology Working Group http://www.bioontology.org/wiki/ Workshop on May 16-17, 2007

43. 43