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2016 IEEE Pacific Visualization Symposium (PacificVis) (2016)
Taipei, Taiwan
April 19, 2016 to April 22, 2016
ISSN: 2165-8773
ISBN: 978-1-5090-1451-4
pp: 244-248
Tsai-Ling Fung , University of California, Davis
Jia-Kai Chou , University of California, Davis
Kwan-Liu Ma , University of California, Davis
This paper presents a comparative study on personal visualizations of bibliographic data. We consider three designs for egocentric visualization: node-link diagrams, adjacency matrices, and botanical trees to depict one's academic career in terms of his/her publication records. Case studies are conducted to compare the effectiveness of resulting visualizations for conveying particular aspect of a researcher's bibliographic records. Based on our study, we find that node-link diagrams are better at revealing the overall distribution of certain attributes; adjacency matrices can convey more information with less clutter; and botanical trees are visually attractive and provide the best at a glance characterization of the mapped data, but mapping data to tree features must be carefully done to derive expressive visualization.

T. Fung, J. Chou and K. Ma, "A design study of personal bibliographic data visualization," 2016 IEEE Pacific Visualization Symposium (PacificVis)(PACIFICVIS), Taipei, Taiwan, 2016, pp. 244-248.
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