Research Institute of Visual Computing

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Visual Comparison for Information Visualization

Authors: Michael Gleicher, Danielle Albers, Rick Walker, Ilir Jusufi, Charles D. Hansen, Jonathan C. Roberts

DOI: 10.1177/1473871611416549"


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 find 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.

Link to Paper


Prof Jonathan C Roberts

Prof Jonathan C Roberts

Jonathan is particularly interested in visual analytics, information visualization and exploratory visualization in a variety of topics (including Heritage, Oceanographic data, Social media)