Invited presentation at the French Medical Semantic Web workshop 2010 in Nimes. Presentation done in several seminars since then.

1. BioPortal ontologies et ressources de données biomédicales à portée de main… Clement Jonquet& BioPortal team jonquet@stanford.edu Atelier Web Sémantique Médical, Nîmes, France - 8 Juin 2010 1

2. Présentation de la présentation Merci pour cette opportunité Contribution de tout le groupe NCBO (~20 pers.) Plan Présentation générale Ce qu’on peut faire avec BioPortal (démo?) Discussion Article de référence N. F. Noy, N. H. Shah, P. L. Whetzel, B. Dai, M. Dorf, N. B. Griffith, C. Jonquet, D. L. Rubin, M. Storey, C. G. Chute, M. A. Musen. BioPortal: ontologies and integrated data resourcesat the click of a mouse. NucleicAcidsResearch, 37:170–173, May 2009. 2

3. Biologist have adopted ontologies To provide canonical representation of scientific knowledge To annotate experimental data to enable interpretation, comparison, and discovery across databases To facilitate knowledge-based applications for Decision support Natural language-processing Data integration But ontologies are: spread out, in different formats, of different size, with different structures 3

4. What is BioPortal? Web repository for biomedical ontologies – “ one stop shop” Make ontologies accessible and usable – abstraction on format, locations, structure, etc. Users can publish, download, browse, search, comment, align ontologies and use them for annotations both online and via a web services API. Community-based ontology development, alignment, and evaluation Figures: 200+ ontologies (OWL, OBO, UMLS) ~ 1.7 million terms ~ 2 million mappings 22 annotated biomedical resources ~ 10 milliards annotations 4

5. What are we trying to do You’ve built an ontology, how do you let the world know? You need an ontology, where do you go o get it? How do you know whether an ontology is any good? How do you find resources that are relevant to the domain of the ontology (or to specific terms)? How could you leverage your ontology to enable new science? 5

6. Community-based ontology repository http://bioportal.bioontology.org 6

7. BioPortal features Library of ontologies (support browsing, visualizing, versioning, metrics, views) Search ontologies, resources Peer review: comments and discussion Mapping Annotate data 7

8. Library of biomedical ontologies 8

9. Ontology metadata 9

10. Ontology metrics 10 Statistics Conformance to Best practices

11. Ontology views 11 Specific subset Other languages

12. Ontology search 12 Keywords & options Ontologies to use

13. Ontology browsing 13

14. Ontology visualizing 14

15. Ontology notes 15

16. Ontology mappings 16

18. Created by users

19. Provenance17

20. How mappings are useful? Navigation mechanism, linking one ontology to another Annotating & query expansion in search Allows to include synonyms defined in other ontologies Use for finding “important” or “reference” ontologies If everyone maps to NCI Thesaurus, it must be important Accessible through web services & RDF to be used in other applications 18

21. Ontology-based annotation workflow 19 First, direct annotations are created by recognizing concepts in raw text, Second, annotations are semantically expanded using knowledge of the ontologies, Third, all annotations are scored according to the context in which they have been created.

23. Data integration problem

24. Translational discoveries are prevented

25. Good examples

26. GO annotations

27. PubMed (biomedical literature) indexed with Mesh headingsAnnotate data with ontology concepts Horizontal approach Annotation challenge 20 RESOURCES ONTOLOGIES

28. NCBO Annotator in BioPortal 21

29. Code Word & Firefox add-ins to call the Annotator Service? Excel UIMA platform Specific UI NCBO Annotator service Multiple ways to access

31. The index can be used to enhance search & data integration23 [DILS 08] [BMC BioInfo09] [IC 10]

32. Ex: annotation of a GEO element 24

33. Ontology-based search (1/2) Example of resource available (name and description) Number of annotations in the NCBO Resource Index Ontology concept/term browsed Title and URL link to the original element Context in which an element has been annotated ID of an element 25

34. Ontology-based search (2/2) 26 Ontology concept(s) to use for search Keyword to search Biomedical resources to query Resource elements found

36. 28 Good use of the semantics (2/2)

37. Ontology recommendation 29

38. The BioPortal technology All BioPortal data is accessible through REST services BioPortal user interface accesses the repository through REST services as well For example: http://bioportal.bioontology.org/visualize/40401/?conceptid=D008545 http://rest.bioontology.org/bioportal/concepts/40401/?conceptid=D008545 The BioPortal technology is domain-independent BioPortal code is open-source Technology stack includes: Protégé, LexGrid, MySQL, Hibernate, Spring, J2EE, Ruby-on-Rails 30

39. Other installations of BioPortal 31

40. BioPortal’s future Better support of Semantic Web standards Done: provide URI for every concept in the ontology TBD: ontologies & annotations available through a SPARQL endpoint Development of a biomedical mega-thesaurus based on ontology mappings Merge ontology editing & publishing Scalability Distributed architecture Enhance views/modularization e.g., different languages 32

41. Conclusion BioPortal is allowing NCBO to experiment with new models for Dissemination of knowledge on the Web Integration and alignment of online content Knowledge visualization and cognitive support Peer review of online content Exciting context of research & application for both CS and Biomedical informatics BioPortal is a good illustration of biomedical semantic web application Please try it and join us! 33

43. Natasha Noy, Mark Musen, Nigam Shah, Patricia Whetzel, Adrien Coulet, Paea Le Pendu, Michael Dorf, Cherie Youn, Paul Alexander, Sean Falconer

44. @ NCBO, somewhere else

45. Peggy Storey, Chris Callendar, Christopher Chute, Pradip Kanjamala, JyotiPathak, Jim Buntrock

46. and many others34

47. MerciNational Center for BioMedical Ontologyhttp://www.bioontology.orgBioPortal, biomedical ontology repositoryhttp://bioportal.bioontology.orgContact mejonquet@stanford.edu 35

48. Develop a mega-thesaurus Group mapped concept s from different ontologies to create a single concept Similar to the approach taken by NLM with UMLS Metathesaurus manual vs. automatic 36

49. Integration of ontology editing and publishing Enable users to go seamlessly between ontology editing and publishing Notes created in BioPortal are visible in an ontology editor User accounts and roles shared among BioPortal and ontology editors Users don’t need to be aware of the difference: they just get their work done 37

51. Web content must be semantically described using ontologies

52. Semantic annotations help to structure the web

53. Annotation is not an easy task

54. Automatic vs. manual

55. Lack of annotation tools (convenient, simple to use and easily integrated into automatic processes)

56. Today’s web content (& public data available through the web) mainly composed of unstructured text38

58. Getting access to all is hard: formats, locations, APIs

59. Lack of tools that easily access all ontologies (domain)

60. Users do not always know the structure of an ontology’s content or how to use it in order to do the annotations themselves

61. Lack of tools to do the annotations automatically

62. Boring additional task without immediate reward for the user39

64. Large scale – to scale up for many resources and ontologies

65. Automatic – to keep precision and accuracy

66. Easy to use and to access – to prevent the biomedical community from getting lost

67. Customizable – to fit very specific needs

68. Smart – to leverage the knowledge contained in ontologies40