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AO and Annotation Tool for AOC



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AO and Annotation Tool for AOC

  1. 1. OAC Workshop, March 24, 2011<br />History and Overview of AO (Annotation Ontology) <br />Paolo Ciccarese, PhD<br /><br />Mass General Hospital<br />Harvard Medical School<br />
  2. 2. MIND Informatics Group<br />Focusing on online scientific communities:<br />AlzSWAN( <br /> <br />PDOnline(<br />SCF Genomic Experiments Repository<br /> ( <br />Neuropathic Pain Forum <br /> (with Harvard NeuroDiscovery Center)<br />We work with pharmaceutical companies, publishers and NIH funded projects. We are heavily involved with W3C HCLS. Director Tim Clark.<br />
  3. 3. AlzSWAN (SWAN for Alzheimer’s Disease)<br /><br />+ Online since beginning 2008<br />+ Approx. 2400 manually curated statements about Alzheimer Disease<br />+ Linked to approx. 2550 publications<br />-Not fully document centric and missing the link to the original document fragments<br />
  4. 4. Our current goal is to enable…<br />
  5. 5. …individual scientists to<br />visually and effectively annotate (better semantically annotate) any digital resource and resource fragment, while performing their regular activities<br />decide to keep the annotation private or share it with colleagues, groups, communities or the web<br />run text mining and entities recognition algorithms on scientific documents and benefit from crowdsourcing their curation<br />efficiently search and reuse the annotation<br />retrieve additional content (mashups)<br />
  6. 6. …scientific communities curators to<br />annotate scientific publications and resources<br />publish such annotation to their members and trigger valuable discussions and feedback<br />use such annotation to link their internal content or external resources (mashups)<br />embed the stand off annotation in the actual document as part of the content (publication process)<br />benefit from annotation produced by related and trusted communities <br />
  7. 7. …text mining providers to <br />provide the results to users in a standardized way, displaying them on top of the documents<br />collect feedback from users that can provide judgment on the accuracy of such results<br />use the feedback to improve their services<br />
  8. 8. …everybody tobenefit from the network effect <br />including ontologists, data miners …<br />
  9. 9. Our recipe<br />AO (Annotation Ontology)<br />SWAN Framework<br />SWAN Annotation Tool (which integrates with PubMed, BioPortal, AntibodyRegistry, AlzSWAN, UIMA, TextPresso, SIOC, CiTO/FaBiO, ORB and other W3C HCLS efforts…)<br />Semantic Search<br />Bibliographic Management<br />Hypothesis Management<br />…<br /><br />
  10. 10. Annotation Ontology (AO)<br />OWL  vocabulary for representing and sharing annotation of digital resources and their fragments<br />First version on May 2009, current on May 2010<br />Who already <br />uses AO<br />The Living Document<br />Project<br />Tags4Lab Project<br />
  11. 11. Some AO Design Principles<br />Traceability: completeness of the information about every step of the annotation process <br />Orthogonality: designed to leverage existing domain ontologies, the way they are<br />Extensibility: designed with extension points because nothing is complete, ever<br />Full list:<br /><br />
  12. 12. A simplified view of AO<br /><ul><li>AO annotates:</li></ul>Resources: documents (HTML, PDF, Word, Excel), Images, <br /> Databases, Web Services... (and their fragments)<br /><ul><li>With (or without) a:</li></ul>Topic: free text, structured text, URIs, RDF entities, <br /> RDF graphs, domain ontologies…<br /><ul><li>Tracing:</li></ul>Provenance: who created what, when, with what<br /> software, with what expectations… <br />
  13. 13. Annotating a document<br />AlzSWAN:<br />aof:annotatesDocumentsubPropertyOfann:annotates<br />
  14. 14. Annotating a document fragment [1]<br />
  15. 15. Annotating a document fragment [2]<br />Protein Ontology – PRO: <br />
  16. 16. Annotating a Claim [1]<br />
  17. 17. Annotating a Claim [2]<br />Icons by: Everaldo Coelho and Agapeh<br />
  18. 18. SWAN Ontology 2.0:<br />
  19. 19. Claim into triples (nanopublications)<br /><><br />Event of type GO "chaperone binding"<br />rdfs:label<br />rdf:type<br /><><br /><prefix:actor_1><br /><><br />rdf:type<br />rdfs:label “Beta amyloid”<br /><prefix:target_1><br /><><br />rdf:type<br />rdfs:label “Membrane protein”<br /><><br /><prefix:location_1><br />rdf:type<br />rdfs:label “Plasma membrane”<br />G8<br />From:<br />Triples provided by Nigam Shah<br />
  20. 20. Integrating with the ecosystem<br />
  21. 21. It might look complicated but…<br />you can do all this and more, visually and with minimum effort, with the <br />SWAN Annotation Tool<br />a customizable and extensible web application… not only for biomedicine<br />Image source:<br />
  22. 22. Bibliography Management<br />See screencast:<br />
  23. 23. Annotation Provenance <br />See screencast:<br />
  24. 24. Semantic Tags or Qualifiers [1]<br />
  25. 25. Semantic Tags or Qualifiers [2]<br />
  26. 26. Semantic Tags or Qualifiers [2]<br />
  27. 27. Semantic Tags or Qualifiers [2]<br />
  28. 28. Antibodies Annotation [1]<br />See screencast:<br />
  29. 29. Antibodies Annotation [2]<br />See screencast:<br /> search<br />
  30. 30. Text Mining Results Curation [1]<br />
  31. 31. Text Mining Results Curation [2]<br />
  32. 32. Additional resources on the SWAN Annotation Tool<br />NIF Webinar recording (full demo March 15, 2011)<br /><br />Slides on Text Mining Results curation <br /><br />Screencasts about integration with Utopia<br /><br /><br />Screencast of new features in build 7<br /><br />

Editor's Notes

  • The topic can be an antibody (NIF Antibody registry)
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