Data visualizations are versatile tools for gaining cognitive access to large amounts of data and for making complex relation-ships in data understandable. This paper proposes a method for assessing data visualizations according to the purposes theyfulfill in domain-specific data analysis settings. We introduce a framework that gets configured for a given analysis domainand allows to choose data visualizations in a methodically justified way, based on analysis questions that address differentaspects of data to be analyzed. Based on the concepts addressed by the analysis questions, the framework provides systematicguidance for determining which data visualizations are able to serve which conceptual analysis interests. In a second step ofthe method, we propose to follow a data-driven approach and to experimentally compare alternative data visualizations fora particular analytical purpose. More specifically, we propose to use eye tracking to support justified decisions about whichof the data visualizations selected with the help of the framework are most suitable for assessing the analysis domain in acognitively efficient way. We demonstrate our approach of how to come from analytical purposes to data visualizations usingthe example domain of Process Modeling Behavior Analysis. The analyses are performed on the background of representativeanalysis questions from this domain.
Jens Gulden, Andrea Burattin, Amine A. Andaloussi, Barbara Weber
10 Jul 2019