Designing for a Bigger Picture: Towards a Macrosyntax for Information Visualizations

Information visualizations can amplify human cognition by transferring strenuous cognitive operations with abstract data into visual reasoning processes with external graphic representations. Cognitive scientists have conceptualized the internal representations emerging in such distributed cognitive systems as mental models, whose structures and dynamics are modeled on the basis of the external representations. While visual-syntactical rules for the construction of simple representations are well defined by different visualization methods and can be relatively easily internalized by the user, an essential question remains how to synthesize coherent macromodels from multiple views. To address this question from a mental models perspective, we assemble and discuss visual coherence techniques, which assist users in assembling “bigger pictures” of complex, abstract subject matters. As such we contribute to a macrosyntax for information visualizations, to more systematically support macrocognitive synthesis and reasoning operations. We delineate and exemplify three different strategies of coherence techniques: methods to support the initial construction of mental models, methods to support the sequential integration of information, and methods to support the synchronous integration of local insights into a global representation.