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Understanding Scientific Literature Networks: Case Study Evaluations of Integrating Visualizations and Statistics

dc.contributor.advisorShneiderman, Benen_US
dc.contributor.authorGove, Robert Paulen_US
dc.description.abstractInvestigators frequently need to quickly learn new research domains in order to advance their research. This thesis presents five contributions to understanding how software helps researchers explore scientific literature networks. (1) A taxonomy which summarizes capabilities in existing bibliography tools, revealing patterns of capabilities by system type. (2) Six participants in two user studies evaluate Action Science Explorer (ASE), which is designed to create surveys of scientific literature and integrates visualizations and statistics. Users found document-level statistics and attribute rankings to be convenient when beginning literature exploration. (3) User studies also identify users' questions when exploring academic literature, which include examining the evolution of a field, identifying author relationships, and searching for review papers. (4) The evaluations suggest shortcomings of ASE, and this thesis outlines improvements to ASE and lists user requirements for bibliographic exploration. (5) I recommend strategies for evaluating bibliographic exploration tools based on experiences evaluating ASE.en_US
dc.titleUnderstanding Scientific Literature Networks: Case Study Evaluations of Integrating Visualizations and Statisticsen_US
dc.contributor.publisherDigital Repository at the University of Marylanden_US
dc.contributor.publisherUniversity of Maryland (College Park, Md.)en_US
dc.contributor.departmentComputer Scienceen_US
dc.subject.pqcontrolledComputer Scienceen_US
dc.subject.pqcontrolledInformation Scienceen_US
dc.subject.pqcontrolledInformation Technologyen_US
dc.subject.pquncontrolledempirical evaluationen_US
dc.subject.pquncontrolledgraphical user interfacesen_US
dc.subject.pquncontrolledinformation visualizationen_US
dc.subject.pquncontrolledliterature explorationen_US

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