Visual comparison for information visualization

  • Authors:

  • Michael Gleicher;Danielle Albers;Rick Walker;Ilir Jusufi;Charles D. Hansen;Jonathan C. Roberts

  • Affiliations:

  • Department of Computer Sciences, University of Wisconsin, Madison, Wl;Department of Computer Sciences, University of Wisconsin, Madison, Wl;School of Computer Science, Bangor University, Bangor, Gwynedd, UK;School of Computer Science, Physics and Mathematics, Linnaeus University, Växjö, Sweden;School of Computing and SCI Institute, University of Utah, Salt Lake City, UT;School of Computer Science, Bangor University, Bangor, Gwynedd, UK

  • Venue:
  • Information Visualization - Special issue on State of the Field and New Research Directions
  • Year:
  • 2011

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Abstract

Data analysis often involves the comparison of complex objects. With the ever increasing amounts and complexity of data, the demand for systems to help with these comparisons is also growing. IncreasingLy, information visuaLization tools support such comparisons explicitLy, beyond simply aLLowing a viewer to examine each object individually. In this paper, we argue that the design of information visualizations of complex objects can, and should, be studied in general, that is independently of what those objects are. As a first step in developing this general understanding of comparison, we propose a general taxonomy of visual designs for comparison that groups designs into three basic categories, which can be combined. To clarify the taxonomy and validate its completeness, we provide a survey of work in information visualization related to comparison. Although we find a great diversity of systems and approaches, we see that all designs are assembled from the building blocks of juxtaposition, superposition and explicit encodings. This initial exploration shows the power of our model, and suggests future challenges in developing a generaL understanding of comparative visualization and faciLitating the development of more comparative visualization tools.