Rapid understanding of scientific paper collections: integrating statistics, text analysis, and visualization

Keeping up with rapidly growing research fields, especially when there aremultiple interdisciplinary sources, requires substantial effort for researchers,
program managers, or venture capital investors. Current theories and tools
are directed at finding a paper or website, not gaining an understanding of
the key papers, authors, controversies, and hypotheses. This report presents
an effort to integrate statistics, text analytics, and visualization in a multiple
coordinated window environment that supports exploration. Our prototype
system, Action Science Explorer (ASE), provides an environment for demon-
strating principles of coordination and conducting iterative usability tests of
them with interested and knowledgeable users. We developed an under-
standing of the value of reference management, statistics, citation context
extraction, natural language summarization for single and multiple docu-
ments, filters to interactively select key papers, and network visualization to
see citation patterns and identify clusters. The three-phase usability study
guided our revisions to ASE and led us to improve the testing methods.