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What I’m Working On: Social Semantic Argumentation, Library Linked Data, Ontologies for Reading & Writing Science Jodi Schneider DERI Social Semantic Information Spaces Stream Meeting 2010-12-13 Galway, Ireland
My Background Liberal Arts - Great Books Math Automatic theorem proving, Knot theory, PDE’s of traffic flow Psychology Online identity - subpersonalities, image (Goffman) Self-surveillance, Persuasive uses of technology (‘captology’) Libraries + technology FRBR – what is a book? entity/relationship model Code4Lib – library technologists, digital librarians, semweb “library values for the Internet” Hobbies tagging, radio, reading… 2
DERI Hats Ph.D. Student Argumentation on the Social Semantic Web Standardization Work W3C Library Linked Data Incubator Group W3C Health Care & Life Sciences – Scientific Discourse Task Force
Argumentation
Social Semantic Web 5
WWW: Detect Contentious Issues Ennals, R., Trushkowsky, B., & Agosta, J. M. (2010). Highlighting Disputed Claims on the Web. In WICOW at WWW 2010.
Social Web: Summarize + Map
Semantic Web: Use Arg Schemes Zablith, F. (2007). ArgDF: Arguments on the Semantic Web (Master's). The British University in Dubai & The University of Edinburgh.
Social Semantic Web: Analyze
Different types of argument
Types of argumentation sites Issue networking Explore the agreements, disagreements, and rationales Get a view of the issues and possibilities Funneling Brainstorm, categorize, vote, … Get to consensus Reputation Compete to find the best answers Get experts, repository of answers
Cognitive Coherence Relations Polarity Positive vs. Negative Source of coherence Semantic vs. Pragmatic Type Addition or Cause or Sequence Comparativeness Comparison  vs. Concurring
Cognitive Coherence Relations
W3C Library Linked Data Incubator Group “incubate” for 1 year Goal: Report on library adoption of Linked Data So far: 40+ use cases in clusters: Bibliographic data Authority data Vocabulary alignment Archives & heterogeneous data Citations Digital objects CKAN data collection
W3C HCLS – Scientific Discourse Task Force Longterm, ongoing activity Goal: A SemWeb platform for biomedical discourse Previous outcomes: SWAN, SWAN/SIOC Current focus: Annotation Ontology  –provenance-aware Mark and connect non-SemWeb docs  Models of Rhetorical structure coarse-grained middle-grained Bibliographic Ontologies (align/integrate SWAN citations) “Scientific Article of the Future” – provenance, data,
Ontology-aware reading? http://www.ihop-net.org screenshot from Renear & Palmer. Science 2009: “Strategic Reading, Ontologies, and the Future of Scientific Publishing.” 325:828-832.
Thank You! Questions & Comments? jodi.schneider@deri.org

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DERI Stream Meeting 2010: What I'm working on

  • 1. What I’m Working On: Social Semantic Argumentation, Library Linked Data, Ontologies for Reading & Writing Science Jodi Schneider DERI Social Semantic Information Spaces Stream Meeting 2010-12-13 Galway, Ireland
  • 2. My Background Liberal Arts - Great Books Math Automatic theorem proving, Knot theory, PDE’s of traffic flow Psychology Online identity - subpersonalities, image (Goffman) Self-surveillance, Persuasive uses of technology (‘captology’) Libraries + technology FRBR – what is a book? entity/relationship model Code4Lib – library technologists, digital librarians, semweb “library values for the Internet” Hobbies tagging, radio, reading… 2
  • 3. DERI Hats Ph.D. Student Argumentation on the Social Semantic Web Standardization Work W3C Library Linked Data Incubator Group W3C Health Care & Life Sciences – Scientific Discourse Task Force
  • 6. WWW: Detect Contentious Issues Ennals, R., Trushkowsky, B., & Agosta, J. M. (2010). Highlighting Disputed Claims on the Web. In WICOW at WWW 2010.
  • 8. Semantic Web: Use Arg Schemes Zablith, F. (2007). ArgDF: Arguments on the Semantic Web (Master's). The British University in Dubai & The University of Edinburgh.
  • 10. Different types of argument
  • 11. Types of argumentation sites Issue networking Explore the agreements, disagreements, and rationales Get a view of the issues and possibilities Funneling Brainstorm, categorize, vote, … Get to consensus Reputation Compete to find the best answers Get experts, repository of answers
  • 12. Cognitive Coherence Relations Polarity Positive vs. Negative Source of coherence Semantic vs. Pragmatic Type Addition or Cause or Sequence Comparativeness Comparison vs. Concurring
  • 14. W3C Library Linked Data Incubator Group “incubate” for 1 year Goal: Report on library adoption of Linked Data So far: 40+ use cases in clusters: Bibliographic data Authority data Vocabulary alignment Archives & heterogeneous data Citations Digital objects CKAN data collection
  • 15. W3C HCLS – Scientific Discourse Task Force Longterm, ongoing activity Goal: A SemWeb platform for biomedical discourse Previous outcomes: SWAN, SWAN/SIOC Current focus: Annotation Ontology –provenance-aware Mark and connect non-SemWeb docs Models of Rhetorical structure coarse-grained middle-grained Bibliographic Ontologies (align/integrate SWAN citations) “Scientific Article of the Future” – provenance, data,
  • 16. Ontology-aware reading? http://www.ihop-net.org screenshot from Renear & Palmer. Science 2009: “Strategic Reading, Ontologies, and the Future of Scientific Publishing.” 325:828-832.
  • 17. Thank You! Questions & Comments? jodi.schneider@deri.org

Hinweis der Redaktion

  1. philosophy, history of math/sci, linguistics, literature, The Presentation of Self in Everyday Life, text message for health promotion
  2. Inquiry and Pedagogical and Information-seeking dialogues are almost entirely knowledge-based, while knowledge plays only a minor role in Negotiation (aiming at a harmonious settlement) and Quarrel (beneficial mainly for venting emotions). Knowledge plays some role in the remaining three types: in Debate, airing arguments (rather than settling them) is of primary importance; in Deliberation and Persuasion, opinion and belief have a large role. In the following, we focus primarily on knowledge-based argumentation.
  3. Cognitive Coherence Relations consist of 4 basic attributes: * source:  semantic vs. pragmatic* type: addition or sequence or type* comparativeness: comparison vs. concurring * polarity: positive vs. negativeThis results in 17 categories ('type' isn't quite binary, though I think you could create a super-category to contain 'addition' and 'sequence').
  4. Use of LD principles and perspectiveSuggest further steps
  5. “Evolve this over time into a more general facility for many types of scientific discourse, and which is linked to key biological categories specified by ontologies.“
  6. For iHop see A Gene Network for Navigating the Literature. Hoffmann, R., Valencia, A. Nature Genetics 36, 664 (2004).