Content
Data comparison in various domains can be effectively supported by visual analytics solutions combining interactive visualization and algorithmic analysis. The design of such solutions should match the comparison problem at hand: the input data and the task specification. This requires several choices from algorithm to visual design and interaction. Such design choices also need to consider human perception capabilities. Our tutorial presents how the differences in data and task characterizations influence visual-analytical solution designs. We will first present a conceptual framework, which defines a set of dimensions along which the comparison problem is defined. We then show how this specification influences the comparative solution design both in theory and using real world examples. Our tutorial provides visualization designers with a means to systematize domain problem analysis and to learn which algorithms, visual designs and interactions to use when, also taking into consideration human perception and cognition capabilities. The tutorial is held at a beginner to an intermediate level.
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