Abstract
Making sense of complex objects is difficult, and typically requires the use of external representations to support cognitive demands while reasoning about the objects. Visualizations are one type of external representation that can be used to support sensemaking activities. In this paper, we investigate the role of two design strategies in making the interactive features of visualizations more supportive of users’ exploratory needs when trying to make sense of complex objects. These two strategies are visibility and complementarity of interactions. We employ a theoretical framework concerned with human–information interaction and complex cognitive activities to inform, contextualize, and interpret the effects of the design strategies. The two strategies are incorporated in the design of Polyvise, a visualization tool that supports making sense of complex four-dimensional geometric objects. A mixed-methods study was conducted to evaluate the design strategies and the overall usability of Polyvise. We report the findings of the study, discuss some implications for the design of visualization tools that support sensemaking of complex objects, and propose five design guidelines. We anticipate that our results are transferrable to other contexts, and that these two design strategies can be used broadly in visualization tools intended to support activities with complex objects and information spaces.
Highlights
Making sense of complex objects—both physical and abstract—is difficult
We report the findings of the study, discuss some implications for the design of visualization tools that support sensemaking of complex objects, and propose five design guidelines
We are not proposing that a minimalist approach is the only good design strategy; rather, we are suggesting that an additive minimalist approach could be an efficient and effective process to design and develop visualization tools dealing with complex objects
Summary
Objects are complex when they are composed of many constituent components that are arranged in complicated ways and have intricate interrelationships. One study suggests that variation, symmetry, part count, simpler part decomposability, intricate details, and topology are six factors that contribute towards visual shape complexity [1]. A rigorous characterization is outside the scope of this paper, a number of characteristics that contribute to objects’ complexity can be identified: number and types of constituent components, number and types of relationships among components, intricacy of relationships among components, symmetry, topology, and number of dimensions in which objects exist [1]. The specific degree of complexity is not of interest; yet, as will be discussed, the objects in our study were four-dimensional shapes, with hundreds or thousands of components of multiple types, and multiple hierarchical levels. We do not try to limit the scope of our work to specific degrees of complexity, but suggest that our findings are applicable in situations where information is too complex to be entirely visualized, and sensemaking of the visualized information is not straightforward
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