Readability Metrics for Network Visualization

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  • This image shows a subset of the ACL Anthology Network of academic papers that deal with dependency parsing. There are five coordinated views depicted here. The left side is your reference manager (JabRef, similar to Endnote, Mendeley, etc.) that gives a list of papers and their abstracts, BibTeX, doi/url/PDF links and the like and allows you to search, sort, group, and import papers. The middle window is the citation network visualization (SocialAction) which shows the node-link diagram for the citation network. Automatically generated clusters (Newman's fast heuristic) are shown with convex hulls and rankings by statistical measures like in-degree, betweenness centrality, and the like are shown in the left 1/3 and color coded in the visualization.The bottom-middle pane displays the text of incoming citations for the selected papers. It was automatically extracted from each paper that cites the selected paper. Selected papers are highlighted in yellow in the network visualization and shown with white backgrounds instead of gray in the reference manager. The lime colored selection of in-cite text is a citation we want to see the context of in the citing paper, which is shown in the top-right. The selection is highlighted in lime there as well, and other automatically extracted citations are shown in orange and purple and can be clicked on to select the target papers.The bottom-right pane shows an automatically generated summary of the in-cite text of the selected papers using a currently poor summarization algorithm.
  • This image shows a subset of the ACL Anthology Network of academic papers that deal with dependency parsing. There are five coordinated views depicted here. The left side is your reference manager (JabRef, similar to Endnote, Mendeley, etc.) that gives a list of papers and their abstracts, BibTeX, doi/url/PDF links and the like and allows you to search, sort, group, and import papers. The middle window is the citation network visualization (SocialAction) which shows the node-link diagram for the citation network. Automatically generated clusters (Newman's fast heuristic) are shown with convex hulls and rankings by statistical measures like in-degree, betweenness centrality, and the like are shown in the left 1/3 and color coded in the visualization.The bottom-middle pane displays the text of incoming citations for the selected papers. It was automatically extracted from each paper that cites the selected paper. Selected papers are highlighted in yellow in the network visualization and shown with white backgrounds instead of gray in the reference manager. The lime colored selection of in-cite text is a citation we want to see the context of in the citing paper, which is shown in the top-right. The selection is highlighted in lime there as well, and other automatically extracted citations are shown in orange and purple and can be clicked on to select the target papers.The bottom-right pane shows an automatically generated summary of the in-cite text of the selected papers using a currently poor summarization algorithm.
  • This image shows a subset of the ACL Anthology Network of academic papers that deal with dependency parsing. There are five coordinated views depicted here. The left side is your reference manager (JabRef, similar to Endnote, Mendeley, etc.) that gives a list of papers and their abstracts, BibTeX, doi/url/PDF links and the like and allows you to search, sort, group, and import papers. The middle window is the citation network visualization (SocialAction) which shows the node-link diagram for the citation network. Automatically generated clusters (Newman's fast heuristic) are shown with convex hulls and rankings by statistical measures like in-degree, betweenness centrality, and the like are shown in the left 1/3 and color coded in the visualization.The bottom-middle pane displays the text of incoming citations for the selected papers. It was automatically extracted from each paper that cites the selected paper. Selected papers are highlighted in yellow in the network visualization and shown with white backgrounds instead of gray in the reference manager. The lime colored selection of in-cite text is a citation we want to see the context of in the citing paper, which is shown in the top-right. The selection is highlighted in lime there as well, and other automatically extracted citations are shown in orange and purple and can be clicked on to select the target papers.The bottom-right pane shows an automatically generated summary of the in-cite text of the selected papers using a currently poor summarization algorithm.
  • Readability Metrics for Network Visualization

    1. 1. iOpener Workbench: Tools for Rapid Understanding of Scientific Literature<br />Cody Dunne, Ben Shneiderman, Bonnie Dorr & Judith Klavans<br />{cdunne, ben, bonnie}@cs.umd.edu, jklavans@umd.edu<br />27th Annual Human-Computer Interaction Lab Symposium<br />May 27-28, 2010College Park, MD<br />
    2. 2. iOpener Workbench<br />
    3. 3. Contribution<br />Infrastructure for rapidly summarizing scientific endeavor<br />Integrate statistics, visualization, reference management, and automatic summarization<br />Multiple coordinated views<br />
    4. 4. Use Cases<br />Learn about new fields<br />Understand how communities form<br />Analyze citation patterns within communities<br />Easily explore & export all papers in a community<br />
    5. 5. What we integrate<br />Potent network analysis tool – SocialAction<br />Citation network statistics & visualization<br />Automatic community detection & visualization<br />Reference & document management – JabRef<br />Powerful reference manager with extensive features for search, grouping, review, annotation, and export<br />Document view with citation linking & highlight<br />Automatically generated summaries<br />Citationtext, keywords, abstracts<br />
    6. 6. What can you do with a graph?<br />Statistics, lists, and text is helpful, but<br />Visualizations show unexpected trends, clusters, gaps, outliers<br />Data cleaning & verification<br />“Information visualization answers questions you didn't know you had” – Ben S.<br />
    7. 7. Importance of Survey Articles<br />Rapidly expanding disciplines<br />Large volume of scientific publications<br />Increasing cross-disciplinary research<br />Need for accurate surveys of previous work<br />Short summaries<br />In-depth historical notes<br />Multiple users<br />Scientists<br />Students & Educators<br />Government decision makers<br />
    8. 8. iOPENER<br />NSF Info Integration & Informatics program <br />Information Organization for PENningExpositions on Research<br />
    9. 9. Components<br />Bibliometriclexical link mining<br />Automatic summarization techniques<br />Visualization tools for structure and content<br />
    10. 10. Ongoing Work<br />Increase preprocessing of citation texts to vastly improve trimmer summary comprehension<br />Preliminary case studies with UMD student domain experts<br />Dependency parsing subset of the ACL Anthology Network (AAN)<br />
    11. 11. Coming Soon<br />Multi-dimensional in-depth long-term case studies<br />longitudinal case studies with domain experts using their data<br />close participant observation<br />Software & generated surveys publicly available and presented to academia and wider audiences<br />
    12. 12. iOpener Workbench<br />Infrastructure to aid rapid summarization of scientific literature<br />Integrates<br />Statistics<br />Visualization<br />Reference management<br />Automatic summarization<br />
    13. 13. iOpener Workbench: Tools for Rapid Understanding of Scientific Literature<br />Cody Dunne, Ben Shneiderman, Bonnie Dorr & Judith Klavans<br />{cdunne, ben, bonnie}@cs.umd.edu, jklavans@umd.edu<br />tangra.si.umich.edu/clair/iopener<br />This work has been partially supported by NSF grant "iOPENER: A Flexible Framework to Support Rapid Learning in Unfamiliar Research Domains", jointly awarded to UMD and UMich as IIS 0705832. <br />
    14. 14. Network Analysis<br />
    15. 15. Reference Manager<br />
    16. 16. Document & Citation View<br />
    17. 17. Summarization<br />
    18. 18. Features – Network analysis<br />SocialAction (Perer, Shneiderman)<br />Citation networkvisualization <br />Force-directed placement (by linkages)<br />Scatterplots of paper attributes & statistics<br />Statistics ranktables<br />Categorial and numerical range coloring<br />Automatic community detection <br />Newman '04 fast heuristic<br />
    19. 19. Features – Reference Manager<br />Search by field with simple regex<br />abstract|keywords=nonprojective and year = 2008<br />Grouping-- automatic, search results, manual<br />DOI/URL, fulltext (annotated PDF, plain text)<br />Metadata, abstracts<br />User generated reviews<br />BibTeX, Word, OpenOfficeintegration<br />HTML, EndNote export<br />
    20. 20. Document view - features<br />Citation links<br />Highlighting<br />
    21. 21. Summarization - Features<br />Automatically generated summariesCitationtext, keywords, abstracts<br />Working to substantially improve coherence & relevance<br />

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