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Science map metaphors: a comparison of network versus hexmap-based visualizations

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Abstract

Most maps of science use a network layout; few use a landscape metaphor. Human users are trained in reading geospatial maps, yet most have a hard time reading even simple networks. Prior work using general networks has shown that map-based visualizations increase recall accuracy of data. This paper reports the result of a comparison of two comparable renderings of the UCSD map of science that are: the original network layout and a novel hexmap that uses a landscape metaphor to layout the 554 subdisciplines grouped into 13 color-coded disciplines of science. Overlaid are HITS metrics that show the impact and transformativeness of different scientific subdisciplines. Both maps support the same interactivity, including search, filter, zoom, panning, and details on demand. Users performed memorization, search, and retrieval tasks using both maps. Results did not show any significant differences in how the two maps were remembered or used by participants. We conclude with a discussion of results and planned future work.

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Fig. 1

Explore the interactive version at http://cns.iu.edu/econ-p/ucsdmap

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Explore the interactive version at http://cns.iu.edu/econ-p/hexmap

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Notes

  1. The original UCSD network map was designed for print. The hexmap leverages the interactive functionality of the web. For print uses, the UCSD network map excels because all data is present at a single glance. The hexmap is more exploratory, inviting the users to interact with the initially visible data to explore details. A good example are the few Health Professional nodes that intrude on the Medical Specialties continent. On the hexmap, we can hover over the Medical Specialties nodes to see their names, see what connections to Medical Specialties and Health Professionals exists, and even click to find publications to determine why it is spatially similar to Medical Specialties. While the UCSD network map doesn’t prevent this, the hexmap was designed to promote this functionality.

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Acknowledgements

The authors would like to thank Joseph Staudt, Huifeng Yu, Robert Light, Gerald Marschke, and Bruce Weinberg from the HITS metrics team for their expert comments on the design and functionality of the two visualizations. Michael Frisby and David Endicott from the Social Science Research Commons at Indiana University Bloomington provided data analysis support. Börner, Simpson, and Bueckle are partially supported by the National Institutes of Health under awards P01 AG039347 and U01CA198934 and the National Science Foundation under award EAGER 1566393, NCN CP Supplement 1553044, and AISL 1713567. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation. This study was accepted by the Human Subjects Office of Indiana University Bloomington as meeting the criteria of exempt research as described in the Federal regulations at 45 CFR 46.101(b), paragraph 2. The Human Subjects Office accepted the use of an information sheet.

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Authors and Affiliations

  1. Cyberinfrastructure for Network Science Center, School of Informatics, Computing, and Engineering, Indiana University, Bloomington, IN, USA

    Katy Börner, Adam H. Simpson & Andreas Bueckle

  2. Indiana University Network Science Institute, Bloomington, IN, USA

    Katy Börner

  3. Cognitive Science Program, Indiana University, Bloomington, IN, USA

    Katy Börner & Robert L. Goldstone

  4. Department of Psychological and Brain Sciences, Indiana University, Bloomington, IN, USA

    Robert L. Goldstone

Authors
  1. Katy Börner
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  2. Adam H. Simpson
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  3. Andreas Bueckle
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  4. Robert L. Goldstone
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Correspondence to Katy Börner.

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Börner, K., Simpson, A.H., Bueckle, A. et al. Science map metaphors: a comparison of network versus hexmap-based visualizations. Scientometrics 114, 409–426 (2018). https://doi.org/10.1007/s11192-017-2596-3

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