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Cody Dunne, Robert Gove, Ben Shneiderman, Judith Klavans, and Bonnie Dorr

Action Science Explorer: Interactive Data Visualization for Rapid Understanding of Scientific Literature. Cody Dunne, Robert Gove, Ben Shneiderman, Judith Klavans, and Bonnie Dorr.

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Cody Dunne, Robert Gove, Ben Shneiderman, Judith Klavans, and Bonnie Dorr

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  1. Action Science Explorer: Interactive Data Visualization for Rapid Understanding of Scientific Literature Cody Dunne, Robert Gove, Ben Shneiderman, Judith Klavans, and Bonnie Dorr • Overview: Action Science Explorer (ASE) supports users in rapidly generating surveys of academic literature. ASE uses: • bibliometric lexical link mining to create a citation network and citation context, • clustering and multi-document summarization to extract key points, • and potent network analysis and visualization tools. Reference Management & Reviewing Imported articles are shown in table view with metadata. A preview below the table shows the reference, abstract, and any user-assigned review for selected articles. Export References Easily export references to Word, OpenOffice, BibTeX, HTML, etc. Full Text PDF and Plain Text. Data Import Users load the results of a database query. Text w/Citation Links When clicked, each cited article is selected in all other views. Article Groups Group articles manually or by metadata into hierarchical, overlapping groups. • Citation Context • Each article has citations and the surrounding context for each from the citing paper, containing: • summaries, • critical reception, and • citations to follow-up articles. • Clicking on a citation context shows the citing paper’s full text. Search for Articles Use regular expressions to search metadata. Rank by Feature Select metadata or dynamically computed citation network statistics to rank articles. The ranking is shown in a list and colored by value. Multi-Document Summarization The citation context of all selected documents is automatically summarized. The short summary shows the key points from the total citation context. Filter Articles Use the double-ended slider to filter out articles in all views. Community-Finding Algorithm Topologically related papers are grouped using Newman’s fast heuristic and shown using convex hulls. Find Trends, Outliers, & Errors Use scatterplots to find interesting data. Citation Network Visualization Nodes show articles with edges between them showing citations. Nodes are arranged using a force-directed layout algorithm and colored by their ranking in the rank table. Get more information at www.cs.umd.edu/hcil/ase This work has been partially supported by the National Science Foundation grant IIS 0705832: "iOPENER: A Flexible Framework to Support Rapid Learning in Unfamiliar Research Domains" University of Maryland, Human-Computer Interaction Lab www.cs.umd.edu/hcil

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