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Modeling arguments in scientific papers ArgDiaP 2014 05-23

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Paper: http://jodischneider.com/pubs/argdiap2014.pdf

We present a motivating scenario for using argumentation within a scientific knowledge base. Our goal is to transform natural language papers, with the manual work of expert curators, into elaborated claim-argument networks.

In ongoing work, we are focusing on creating Micropublications (Tim Clark, Paolo N. Ciccarese, Carole A. Goble http://arxiv.org/abs/1305.3506 ) through manual annotation. Currently we are engaging with pharmaceutical curators to envision the most appropriate way to record evidence for the next generation of the the Drug Interaction Knowledge Base.

Presented at The 12th ArgDiaP Conference "From Real Data to Argument Mining"
https://sites.google.com/site/argdiapen/12th-argdiap

Published in: Technology, Health & Medicine
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Modeling arguments in scientific papers ArgDiaP 2014 05-23

  1. 1. Jodi Schneider, Carol Collins, Lisa E Hines, John R Horn, and Richard Boyce 12th Argumentation, Dialogue, Persuasion conference (ArgDiaP 2014) Warsaw, Poland 2014-05-25
  2. 2. Are you taking any other medications?
  3. 3. Checks for known drug interactions
  4. 4. Prescribers consult drug interaction references… Medscape EpocratesMicromedex 2.0
  5. 5. …which are maintained by expert pharmacists Medscape EpocratesMicromedex 2.0
  6. 6. Goal: Support evidence-based updates to drug-interaction reference DBs • Make sense of the EVIDENCE – New clinical trials – Adverse drug event reports – Drug product labels – Updates to regulatory information (U.S. FDA,…) – … • Significant discrepancies between different drug-interaction reference DBs http://jama.jamanetwork.com/article.aspx?articleid=183454
  7. 7. Drug Interaction Knowledge Base (DIKB) - Boyce 2007-2009 – Hand-constructed knowledge base – Safety issues when 2 drugs are taken together – Focus is on EVIDENCE
  8. 8. Drug Interaction Knowledge Base (DIKB) - Boyce 2007-2009 – Hand-constructed knowledge base – Safety issues when 2 drugs are taken together – Focus is on EVIDENCE All assumptions are linked to evidence Enables the system to identify when
  9. 9. DIKB supports queries about assertions & evidence: • Get all assertions that are supported by a U.S. FDA regulatory guidance statement • Are the evidence use assumptions are concordant, unique, and non-ambiguous? • Which assertions are supported/refuted by just one type of evidence?
  10. 10. Limitations of DIKB v1.2 • Minimal argumentation model – swanco:citesAsSupportingEvidence – swanco:citesAsRefutingEvidence • Cannot recover the source text – Document-level citation – Quote & section citation preferrable • Level of detail – Want more detail on data, methods, materials
  11. 11. Record deeper relationships between assertions and evidence • Assertions – “there (is/is not) an interaction between A & B” – “Enzyme E reduces clearance of drug D by 25%” • Evidence – Scientific literature – Drug product labeling – U.S. FDA guidance documents
  12. 12. Micropublication: Claim + Support (e.g. Attribution) Micropublications: a Semantic Model for Claims, Evidence, Arguments and Annotations in Biomedical Communications Tim Clark, Paolo N. Ciccarese, Carole A. Goble http://arxiv.org/abs/1305.3506
  13. 13. Constructs claim-argument network across scientific papers Micropublications: a Semantic Model for Claims, Evidence, Arguments and Annotations in Biomedical Communications Tim Clark, Paolo N. Ciccarese, Carole A. Goble http://arxiv.org/abs/1305.3506
  14. 14. Model Data, Methods, Materials, References Micropublications: a Semantic Model for Claims, Evidence, Arguments and Annotations in Biomedical Communications Tim Clark, Paolo N. Ciccarese, Carole A. Goble http://arxiv.org/abs/1305.3506
  15. 15. Micropublications Ontology Micropublications: a Semantic Model for Claims, Evidence, Arguments and Annotations in Biomedical Communications Tim Clark, Paolo N. Ciccarese, Carole A. Goble http://arxiv.org/abs/1305.3506
  16. 16. What does this do for the DIKB • Network of claims with supports & challenges • Can record materials, methods, data • Quotes can be naturally linked into the graph • We can query for every mp:Claim that has no support. – An assumption (mp:Claim) – Can have its own support graph, specified once – We can query the support graph
  17. 17. "escitalopram does not inhibit CYP2D6" Support graph Challenge graph
  18. 18. Support graph
  19. 19. Methods Methods section of challenge graph
  20. 20. Textual quotes
  21. 21. • Evidence
  22. 22. Direct Annotation with Domeo http://swan.mindinformatics.org/ Paolo N Ciccarese
  23. 23. From individual documents to a searchable claim-argument network • "Pay as you go" annotation of source documents with Domeo & Micropublications • Generates claim-argument network – Supports & challenges – Materials, methods, data – Quotes linked into the graph – … within & across documents • Query support

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