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Workshop

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).

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Workshop

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  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 Break8.40 Dave Parrish (Immune Tolerance Network, PA)9.05 Yannick Legre (Healthgrid, France)

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

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

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

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

  7. 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 = 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. New Definition

  8. Third step (2006) The OBO Foundryhttp://obofoundry.org/

  9. a family of interoperable gold standard biomedical reference ontologies to serve the annotation of • model organism databases • scientific literature • clinical data • experimental results http://obofoundry.org/

  10. Foundry developers have agreed in advance to accept a common set of principles designed to ensure • compatibility • interoperability • formal robustness http://obofoundry.org/

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

  12. CRITERIA • The ontology isopenand 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 collaboratewith developers of other OBO Foundry ontology where domains overlap. CRITERIA http://obofoundry.org/

  13. 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 CRITERIA http://obofoundry.org/

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

  15. CRITERIA • 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. http://obofoundry.org/

  16. CRITERIA • 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 http://obofoundry.org/

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

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

  19. 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

  20. 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 ...

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

  22. 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

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

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

  25. 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

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

  27. 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”

  28. RCT: Concept • Concept • Administrative-concept • Publication-concept • Study-site • Person • Intervention-concept • Blinding-concept • Intervention-step • Intervention

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

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

  31. OBI Top Level

  32. OBO Occurrent

  33. CTO

  34. CTO Continuant

  35. CTO Occurrent

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

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